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Kellner E, Sekula P, Lipovsek J, Russe M, Horbach H, Schlett CL, Nauck M, Völzke H, Kroencke T, Bette S, Kauczor HU, Keil T, Pischon T, Heid IM, Peters A, Niendorf T, Lieb W, Bamberg F, Büchert M, Reichardt W, Reisert M, Köttgen A. Automated Segmentation of the Kidney From MR Imaging—an Analysis of Data From the German National Cohort Health Study (Nako Gesundheitsstudie). Dtsch Arztebl Int 2024:arztebl.m2024.0040. [PMID: 38530931 DOI: 10.3238/arztebl.m2024.0040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
BACKGROUND Population-wide research on potential new imaging biomarkers of the kidney depends on accurate automated segmentation of the kidney and its compartments (cortex, medulla, and sinus). METHODS We developed a robust deep-learning framework for kidney (sub-)segmentation based on a hierarchical, three-dimensional convolutional neural network (CNN) that was optimized for multi-scale problems of combined localization and segmentation. We applied the CNN to abdominal magnetic resonance images from the population-based German National Cohort (NAKO) study. RESULTS There was good to excellent agreement between the model predictions and manual segmentations. The median values for the body-surface normalized total kidney, cortex, medulla, and sinus volumes of 9934 persons were 158, 115, 43, and 24 mL/m2. Distributions of these markers are provided both for the overall study population and for a subgroup of persons without kidney disease or any associated conditions. Multivariable adjusted regression analyses revealed that diabetes, male sex, and a higher estimated glomerular filtration rate (eGFR) are important predictors of higher total and cortical volumes. Each increase of eGFR by one unit (i.e., 1 mL/min per 1.73 m2 body surface area) was associated with a 0.98 mL/m2 increase in total kidney volume, and this association was significant. Volumes were lower in persons with eGFR-defined chronic kidney disease. CONCLUSION The extraction of image-based biomarkers through CNN-based renal sub-segmentation using data from a population-based study yields reliable results, forming a solid foundation for future investigations.
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Thapa A, Cowell A, Peters A, Noble DJ, James A, Lamb C, Grose D, Vohra S, Schipani S, Mactier K, Mackenzie J, Srinivasan D, Laws K, Moleron R, Niblock P, Soh FY, Paterson C, Wilson C. The UK Divide: Does Having a Pembrolizumab-Chemotherapy Option in Head and Neck Cancer Matter? Real-world Experience of First-line Palliative Pembrolizumab Monotherapy and Pembrolizumab-Chemotherapy Combination in Scotland. Clin Oncol (R Coll Radiol) 2024; 36:287-299. [PMID: 38395634 DOI: 10.1016/j.clon.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/21/2023] [Accepted: 02/08/2024] [Indexed: 02/25/2024]
Abstract
AIMS The Scottish Medical Consortium recently approved first-line pembrolizumab monotherapy or in combination with chemotherapy for head and neck squamous cell carcinoma in the palliative setting, contrasting with the decision made by the National Institute for Health and Care Excellence, who approved monotherapy alone in England and Wales. The aim of this study was to provide real-world performance data for first-line pembrolizumab-containing treatments for head and neck squamous cell carcinoma in the palliative setting in Scotland. MATERIALS AND METHODS We analysed the electronic records of patients who started pembrolizumab-containing treatment between 1 March 2020 and 30 September 2021. Outcomes included overall survival, progression-free survival (PFS), the duration of response and the disease control rate. Data were compared with the KEYNOTE-048 study and clinical factors were evaluated for association with survival. RESULTS Our cohort included 91 patients (median follow-up 10.8 months). Patient characteristics were similar to those in the KEYNOTE-048 study, although our cohort had a higher proportion of patients with newly diagnosed, non-metastatic disease. For patients receiving monotherapy (n = 76), 12- and 24-month overall survival were 45% and 27%, respectively. For patients receiving pembrolizumab-chemotherapy (n = 15), 12-month overall survival was 60% (24-month overall survival had not yet been reached). Experiencing one or more immune-related adverse event (irAE; versus no irAEs), of any grade, was associated with favourable overall survival and PFS for patients receiving monotherapy in both univariable Log-rank analysis (median overall survival 17.4 months versus 8.6 months, respectively, P = 0.0033; median PFS 10.9 months versus 3.0 months, respectively, P < 0.0001) and multivariable analysis (Cox proportional hazards regression: overall survival hazard ratio 0.31, P = 0.0009; PFS hazard ratio 0.17, P < 0.0001). CONCLUSION Our real-world data support the KEYNOTE-048 study findings and the value of combination treatment options. Additionally, our data show that irAEs of any grade, as reported in routine clinical records, are associated with better outcomes in this patient group, adding to the growing body of evidence showing that irAEs are generally a positive marker of programmed death-ligand 1 (PD-L1) inhibitor response.
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Affiliation(s)
- A Thapa
- College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK
| | - A Cowell
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - A Peters
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - D J Noble
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK; Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - A James
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - C Lamb
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - D Grose
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - S Vohra
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - S Schipani
- Beatson West of Scotland Cancer Centre, Glasgow, UK
| | - K Mactier
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - J Mackenzie
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - D Srinivasan
- Department of Clinical Oncology, Edinburgh Cancer Centre, Western General Hospital, Edinburgh, UK
| | - K Laws
- Aberdeen Royal Infirmary, Aberdeen, UK
| | - R Moleron
- Aberdeen Royal Infirmary, Aberdeen, UK
| | | | - F-Y Soh
- Raigmore Hospital, Inverness, UK
| | - C Paterson
- Beatson West of Scotland Cancer Centre, Glasgow, UK.
| | - C Wilson
- Beatson West of Scotland Cancer Centre, Glasgow, UK.
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Hajek A, Becher H, Brenner H, Holleczek B, Katzke V, Kaaks R, Minnerup H, Karch A, Baurecht H, Leitzmann M, Peters A, Gastell S, Ahrens W, Haug U, Nimptsch K, Pischon T, Michels KB, Dorrn A, Klett-Tammen CJ, Castell S, Willich SN, Keil T, Schipf S, Meinke-Franze C, Harth V, Obi N, König HH. Personality and the use of cancer screenings - Results of the German National Cohort. Prev Med Rep 2024; 41:102677. [PMID: 38533391 PMCID: PMC10963220 DOI: 10.1016/j.pmedr.2024.102677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/28/2024] Open
Abstract
Objective To determine the association between personality characteristics and use of different cancer screenings. Methods We used data from the German National Cohort (NAKO; mean age was 53.0 years (SD: 9.2 years)) - a population-based cohort study. A total of 132,298 individuals were included in the analyses. As outcome measures, we used (self-reported): stool examination for blood (haemoccult test, early detection of bowel cancer), colonoscopy (screening for colorectal cancer), skin examination for moles (early detection of skin cancer), breast palpation by a doctor (early detection of breast cancer), x-ray examination of the breast ("mammography", early detection of breast cancer), cervical smear test, finger examination of the rectum (early detection of prostate cancer), and blood test for prostate cancer (determination of Prostate-Specific Antigen level). The established Big Five Inventory-SOEP was used to quantify personality factors. It was adjusted for several covariates based on the Andersen model. Unadjusted and adjusted multiple logistic regressions were computed. Results A higher probability of having a skin examination for moles, for example, was associated with a higher conscientiousness (OR: 1.07, p < 0.001), higher extraversion (OR: 1.03, p < 0.001), higher agreeableness (OR: 1.02, p < 0.001), lower openness to experience (OR: 0.98, p < 0.001) and higher neuroticism (OR: 1.07, p < 0.001) among the total sample. Depending on the outcome used, the associations slightly varied. Conclusions Particularly higher levels of extraversion, neuroticism and conscientiousness are associated with the use of different cancer screenings. Such knowledge may help to better understand non-participation in cancer screening examinations from a psychological perspective.
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Affiliation(s)
- André Hajek
- Department of Health Economics and Health Services Research, University Medical Center Hamburg-Eppendorf, Hamburg Center for Health Economics, Hamburg, Germany
| | - Heiko Becher
- Heidelberg University Hospital, Heidelberg Institute of Global Health, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Saarland Cancer Registry, Saarbrücken, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Heike Minnerup
- Institute for Epidemiology and Social Medicine, Faculty of Medicine, University of Münster, Münster, Germany
| | - André Karch
- Institute for Epidemiology and Social Medicine, Faculty of Medicine, University of Münster, Münster, Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, 93053 Regensburg, Germany
| | - Michael Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, 93053 Regensburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Sylvia Gastell
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
| | - Ulrike Haug
- Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Max Delbrueck Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
- Charité - Universitaetsmedizin Berlin, Corporate Member of Freie Universitaet Berlin, Humboldt-Universitaet zu Berlin, Berlin, Germany
| | - Karin B. Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Anja Dorrn
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | | | - Stefanie Castell
- Department for Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Stefan N. Willich
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- State Institute of Health I, Bavarian Health and Food Safety Authority, Erlangen, Germany
| | - Sabine Schipf
- Institute for Community Medicine, Department SHIP/Clinical-Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
| | - Claudia Meinke-Franze
- Institute for Community Medicine, Department SHIP/Clinical-Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
| | - Volker Harth
- Institute for Occupational and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hans-Helmut König
- Department of Health Economics and Health Services Research, University Medical Center Hamburg-Eppendorf, Hamburg Center for Health Economics, Hamburg, Germany
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Shugaa Addin N, Niedermayer F, Thorand B, Linseisen J, Seissler J, Peters A, Rospleszcz S. Association of serum magnesium with metabolic syndrome and the role of chronic kidney disease: A population-based cohort study with Mendelian randomization. Diabetes Obes Metab 2024; 26:1808-1820. [PMID: 38361465 DOI: 10.1111/dom.15497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/25/2024] [Accepted: 01/31/2024] [Indexed: 02/17/2024]
Abstract
OBJECTIVES To assess the association of serum magnesium with prevalent and incident metabolic syndrome (MetS) and its individual components in the general population and to examine any effect modification by chronic kidney disease (CKD) status. METHODS We analysed longitudinal data from the population-based KORA F4/FF4 study, including 2996 participants (387 with CKD) for cross-sectional analysis and 1446 participants (88 with CKD) for longitudinal analysis. Associations with MetS, as well as single components of MetS, were assessed by adjusted regression models. Nonlinearity was tested by restricted cubic splines and analyses were stratified by CKD. Causality was evaluated by two-sample Mendelian randomization (MR). RESULTS Serum magnesium (1 SD) was inversely associated with prevalent MetS (odds ratio [OR] 0.90, 95% confidence interval [CI] 0.83, 0.98). The association was more pronounced in individuals with CKD (OR 0.75, 95% CI 0.59, 0.94). Among MetS components, serum magnesium was negatively associated with elevated fasting glucose (OR 0.78, 95% CI 0.71, 0.88) and, again, this association was more pronounced in individuals with CKD (OR 0.67, 95% CI 0.53, 0.84). Serum magnesium was not associated with incident MetS or its components. Restricted cubic spline analysis revealed a significant nonlinear inverse relationship of serum magnesium with MetS and elevated fasting glucose. MR analysis suggested an inverse causal effect of serum magnesium on MetS (OR 0.91, 95% CI 0.85, 0.97). CONCLUSION Serum magnesium is associated with prevalent, but not incident MetS, and this effect is stronger in individuals with CKD. MR analysis implies a potential, albeit weak, causal role of magnesium in MetS.
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Affiliation(s)
- Nuha Shugaa Addin
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Fiona Niedermayer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
- Partner Site München-Neuherberg, German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Jakob Linseisen
- Chair of Epidemiology, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
| | - Jochen Seissler
- Partner Site München-Neuherberg, German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Diabetes Research Group, LMU-Klinikum; Medizinische Klinik und Poliklinik IV, München, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
- Partner Site München-Neuherberg, German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK e.V.), Munich Heart Alliance, München, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
- German Centre for Cardiovascular Research (DZHK e.V.), Munich Heart Alliance, München, Germany
- Department of Diagnostic and Interventional Radiology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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5
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Holz A, Obi N, Ahrens W, Berger K, Bohn B, Brenner H, Fischer B, Fricke J, Führer A, Gastell S, Greiser KH, Harth V, Heise JK, Holleczek B, Keil T, Klett-Tammen CJ, Leitzmann M, Lieb W, Meinke-Franze C, Michels KB, Mikolajczyk R, Nimptsch K, Peters A, Pischon T, Riedel O, Schikowski T, Schipf S, Schmidt B, Schulze MB, Stang A, Hellwig K, Riemann-Lorenz K, Heesen C, Becher H. Childhood and adolescence factors and multiple sclerosis: results from the German National Cohort (NAKO). BMC Neurol 2024; 24:123. [PMID: 38614986 PMCID: PMC11015562 DOI: 10.1186/s12883-024-03620-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 04/02/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Multiple Sclerosis (MS) represents the most common inflammatory neurological disease causing disability in early adulthood. Childhood and adolescence factors might be of relevance in the development of MS. We aimed to investigate the association between various factors (e.g., prematurity, breastfeeding, daycare attendance, weight history) and MS risk. METHODS Data from the baseline assessment of the German National Cohort (NAKO) were used to calculate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for the association between childhood and adolescence factors and risk of MS. Analyses stratified by sex were conducted. RESULTS Among a total of 204,273 participants, 858 reported an MS diagnosis. Male sex was associated with a decreased MS risk (HR 0.48; 95% CI 0.41-0.56), while overweight (HR 2.03; 95% CI 1.41-2.94) and obesity (HR 1.89; 95% CI 1.02-3.48) at 18 years of age compared to normal weight were associated with increased MS risk. Having been breastfed for ≤ 4 months was associated with a decreased MS risk in men (HR 0.59; 95% CI 0.40-0.86) compared to no breastfeeding. No association with MS risk was observed for the remaining factors. CONCLUSIONS Apart from overweight and obesity at the age of 18 years, we did not observe considerable associations with MS risk. The proportion of cases that can be explained by childhood and adolescence factors examined in this study was low. Further investigations of the association between the onset of overweight and obesity in childhood and adolescence and its interaction with physical activity and MS risk seem worthwhile.
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Affiliation(s)
- Anja Holz
- Institute of Medical Biometry and Epidemiology (IMBE), University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246, Hamburg, Germany.
- Institute of Tumor Biology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
| | - Nadia Obi
- Institute of Medical Biometry and Epidemiology (IMBE), University Medical Center Hamburg-Eppendorf (UKE), Martinistr. 52, 20246, Hamburg, Germany
- Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
- University Bremen, Bremen, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | | | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Beate Fischer
- Institute for Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Julia Fricke
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Amand Führer
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Sylvia Gastell
- NAKO Study Center, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Karin Halina Greiser
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Volker Harth
- Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | | | | | - Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- State Institute of Health I, Bavarian Health and Food Safety Authority, Erlangen, Germany
| | - Carolina J Klett-Tammen
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
| | - Michael Leitzmann
- Institute for Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Claudia Meinke-Franze
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Karin B Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Katharina Nimptsch
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Tobias Pischon
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Oliver Riedel
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Tamara Schikowski
- IUF - Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, Medical Faculty, University Duisburg-Essen, Essen, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Andreas Stang
- Institute for Medical Informatics, Biometry and Epidemiology, Medical Faculty, University Duisburg-Essen, Essen, Germany
- School of Public Health, Department of Epidemiology Boston University, 715 Albany Street, Talbot Building, Boston, MA, 02118, USA
| | - Kerstin Hellwig
- Katholisches Klinikum Bochum, Neurology Clinic, Clinic of Ruhr-Universität Bochum, Bochum, Germany
| | - Karin Riemann-Lorenz
- Center for Molecular Neurobiology Hamburg (ZMNH), Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Christoph Heesen
- Center for Molecular Neurobiology Hamburg (ZMNH), Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Department of Neurology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Heiko Becher
- Institute of Global Health, University Hospital Heidelberg, Heidelberg, Germany
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Bui H, Keshawarz A, Wang M, Lee M, Ratliff SM, Lin L, Birditt KS, Faul JD, Peters A, Gieger C, Delerue T, Kardia SLR, Zhao W, Guo X, Yao J, Rotter JI, Li Y, Liu X, Liu D, Tavares JF, Pehlivan G, Breteler MMB, Karabegovic I, Ochoa-Rosales C, Voortman T, Ghanbari M, van Meurs JBJ, Nasr MK, Dörr M, Grabe HJ, London SJ, Teumer A, Waldenberger M, Weir DR, Smith JA, Levy D, Ma J, Liu C. Association analysis between an epigenetic alcohol risk score and blood pressure. medRxiv 2024:2024.02.29.24303545. [PMID: 38464320 PMCID: PMC10925472 DOI: 10.1101/2024.02.29.24303545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day ( p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP ( p = 4.64E-07), 0.68 mm Hg higher DBP ( p = 0.006), and an odds ratio of 1.78 for HTN ( p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 ( p = 0.002) and 0.50 ( p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
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7
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Stein MJ, Fischer B, Bohmann P, Ahrens W, Berger K, Brenner H, Günther K, Harth V, Heise JK, Karch A, Klett-Tammen CJ, Koch-Gallenkamp L, Krist L, Lieb W, Meinke-Franze C, Michels KB, Mikolajczyk R, Nimptsch K, Obi N, Peters A, Pischon T, Schipf S, Schmidt B, Stang A, Thierry S, Willich SN, Wirkner K, Leitzmann MF, Sedlmeier AM. Differences in Anthropometric Measures Based on Sex, Age, and Health Status: Findings From the German National Cohort (NAKO). Dtsch Arztebl Int 2024:arztebl.m2024.0016. [PMID: 38377337 DOI: 10.3238/arztebl.m2024.0016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
BACKGROUND Obesity is a worldwide health problem. We conducted detailed analyses of anthropometric measures in a comprehensive, population-based, current cohort in Germany. METHODS In the German National Cohort (NAKO), we analyzed cross-sectional data on body-mass index (BMI), waist and hip circumference, subcutaneous (SAT) and visceral adipose tissue (VAT) as measured by ultrasound, and body fat percentage. The data were stratified by sex, age, and self-reported physicians' diagnoses of cardiovascular diseases (CVD), metabolic diseases (MetD), cardiometabolic diseases (CMD), and cancer. RESULTS Data were available from 204 751 participants (age, 49.9 ± 12.8 years; 50.5% women). Body size measures generally increased with age. Men had a higher BMI, larger waist circumference, and more VAT than women, while women had a larger hip circumference, more SAT, and a higher body fat percentage than men. For example, the mean BMI of participants over age 60 was 28.3 kg/m2 in men and 27.6 kg/m2 in women. CVD, MetD, and CMD were associated with higher anthropometric values, while cancer was not. For example, the mean BMI was 25.3 kg/m2 in healthy women, 29.4 kg/m2 in women with CMD, and 25.4 kg/m2 in women with cancer. CONCLUSION Obesity is widespread in Germany, with notable differences between the sexes in anthropometric values. Obesity was more common in older participants and those with chronic diseases other than cancer. Elevated values were especially common in multimorbid individuals.
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Weber A, van Hees VT, Stein MJ, Gastell S, Steindorf K, Herbolsheimer F, Ostrzinski S, Pischon T, Brandes M, Krist L, Marschollek M, Greiser KH, Nimptsch K, Brandes B, Jochem C, Sedlmeier AM, Berger K, Brenner H, Buck C, Castell S, Dörr M, Emmel C, Fischer B, Flexeder C, Harth V, Hebestreit A, Heise JK, Holleczek B, Keil T, Koch-Gallenkamp L, Lieb W, Meinke-Franze C, Michels KB, Mikolajczyk R, Kluttig A, Obi N, Peters A, Schmidt B, Schipf S, Schulze MB, Teismann H, Waniek S, Willich SN, Leitzmann MF, Baurecht H. Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO). Sci Rep 2024; 14:7927. [PMID: 38575636 PMCID: PMC10995156 DOI: 10.1038/s41598-024-58461-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/29/2024] [Indexed: 04/06/2024] Open
Abstract
Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.
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Affiliation(s)
- Andrea Weber
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | | | - Michael J Stein
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Sylvia Gastell
- NAKO Study Center, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Karen Steindorf
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Florian Herbolsheimer
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Stefan Ostrzinski
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Mirko Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Lilian Krist
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
| | - Michael Marschollek
- Hannover Medical School, Peter L. Reichertz Institute for Medical Informatics, Carl-Neuberg-Strasse 1, 30625, Hannover, Germany
| | - Karin Halina Greiser
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Berit Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Carmen Jochem
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Anja M Sedlmeier
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christoph Buck
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Stefanie Castell
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Carina Emmel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Beate Fischer
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Claudia Flexeder
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Volker Harth
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Seewartenstraße 10, 20459, Hamburg, Germany
| | - Antje Hebestreit
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Jana-Kristin Heise
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
| | | | - Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- State Institute of Health I, Bavarian Health and Food Safety Authority, Erlangen, Germany
| | - Lena Koch-Gallenkamp
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Claudia Meinke-Franze
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Karin B Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexander Kluttig
- Institute for Medical Epidemiology, Biometrics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Seewartenstraße 10, 20459, Hamburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Henning Teismann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Sabina Waniek
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Stefan N Willich
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
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Schepp M, Freuer D, Wawro N, Peters A, Heier M, Teupser D, Meisinger C, Linseisen J. Association of the habitual dietary intake with the fatty liver index and effect modification by metabotypes in the population-based KORA-Fit study. Lipids Health Dis 2024; 23:99. [PMID: 38575962 PMCID: PMC10993479 DOI: 10.1186/s12944-024-02094-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 03/26/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is an emerging threat for public health with diet being a major risk factor in disease development and progression. However, the effects of habitual food consumption on fatty liver are still inconclusive as well as the proposed role of the individuals' metabolic profiles. Therefore, the aim of our study is to examine the associations between diet and NAFLD with an emphasis on the influence of specific metabotypes in the general population. METHODS A total of 689 participants (304 men and 385 women) of the KORA-Fit (S4) survey, a follow-up study of the population-based KORA cohort study running in the Region of Augsburg, Germany, were included in this analysis. Dietary information was derived from repeated 24-h food lists and a food frequency questionnaire. The intake of energy and energy-providing nutrients were calculated using the national food composition database. The presence of fatty liver was quantified by the fatty liver index (FLI), and metabotypes were calculated using K-means clustering. Multivariable linear regression models were used for the analysis of habitual food groups and FLI; for the evaluation of macronutrients, energy substitution models were applied. RESULTS A higher consumption of nuts and whole grains, and a better diet quality (according to Alternate Healthy Eating Index and Mediterranean Diet Score) were associated with lower FLI values, while the intake of soft drinks, meat, fish and eggs were associated with a higher FLI. The isocaloric substitution of carbohydrates with polyunsaturated fatty acids was associated with a decreased FLI, while substitution with monounsaturated fatty acids and protein showed increased FLI. Statistically significant interactions with the metabotype were observed for most food groups. CONCLUSION The consumption of plant-based food groups, including nuts and whole grains, and diet quality, were associated with lower FLI values, whereas the intake of soft drinks and products of animal origin (meat, fish, eggs) were associated with a higher FLI. The observed statistically significant interactions with the metabotype for most food groups could help to develop targeted prevention strategies on a population-based level if confirmed in independent prospective studies.
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Affiliation(s)
- M Schepp
- University of Augsburg, University Hospital Augsburg, EpidemiologyAugsburg, Germany.
| | - D Freuer
- University of Augsburg, University Hospital Augsburg, EpidemiologyAugsburg, Germany
| | - N Wawro
- University of Augsburg, University Hospital Augsburg, EpidemiologyAugsburg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - A Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - M Heier
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- KORA Study Centre, University Hospital Augsburg, Augsburg, Germany
| | - D Teupser
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany
| | - C Meisinger
- University of Augsburg, University Hospital Augsburg, EpidemiologyAugsburg, Germany
| | - J Linseisen
- University of Augsburg, University Hospital Augsburg, EpidemiologyAugsburg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
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Badpa M, Schneider A, Schwettmann L, Thorand B, Wolf K, Peters A. Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study. Environ Epidemiol 2024; 8:e302. [PMID: 38617422 PMCID: PMC11008658 DOI: 10.1097/ee9.0000000000000302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 02/12/2024] [Indexed: 04/16/2024] Open
Abstract
Introduction Type 2 diabetes (T2D) is a major public health concern, and various environmental factors have been associated with the development of this disease. This study aimed to investigate the longitudinal effects of multiple environmental exposures on the risk of incident T2D in a German population-based cohort. Methods We used data from the KORA cohort study (Augsburg, Germany) and assessed exposure to air pollutants, traffic noise, greenness, and temperature at the participants' residencies. Cox proportional hazard models were used to analyze the associations with incident T2D, adjusting for potential confounders. Results Of 7736 participants included in the analyses, 10.5% developed T2D during follow-up (mean: 15.0 years). We found weak or no association between environmental factors and the risk of T2D, with sex and education level significantly modifying the effects of air pollutants. Conclusion Our study contributes to the growing body of literature investigating the impact of environmental factors on T2D risks and suggests that the impact of environmental factors may be small.
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Affiliation(s)
- Mahnaz Badpa
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Lars Schwettmann
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Munich, Germany
- Department of Health Services Research, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
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Claessen H, Narres M, Heier M, Kvitkina T, Linkohr B, Wolff G, Roden M, Icks A, Peters A. Sex-specific trends in incidence of first myocardial infarction among people with and without diabetes between 1985 and 2016 in a German region. Cardiovasc Diabetol 2024; 23:110. [PMID: 38555466 PMCID: PMC10981819 DOI: 10.1186/s12933-024-02179-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 02/26/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND The reduction of myocardial infarction (MI) and narrowing the gap between the populations with and without diabetes are important goals of diabetes care. We analyzed time trends for sex-specific incidence rates (IR) of first MI (both non-fatal MI and fatal MI) as well as separately for first non-fatal MI and fatal MI in the population with and without diabetes. METHODS Using data from the KORA myocardial infarction registry (Augsburg, Germany), we estimated age-adjusted IR in people with and without diabetes, corresponding relative risks (RR), and time trends from 1985 to 2016 using Poisson regression. RESULTS There were 19,683 people with first MI (34% fatal MI, 71% men, 30% with diabetes) between 1985 and 2016. In the entire study population, the IR of first MI decreased from 359 (95% CI: 345-374) to 236 (226-245) per 100,000 person years. In men with diabetes, IR decreased only in 2013-2016. This was due to first non-fatal MI, where IR in men with diabetes increased until 2009-2012, and slightly decreased in 2013-2016. Overall, fatal MI declined stronger than first non-fatal MI corresponding to IRs. The RR of first MI substantially increased among men from 1.40 (1.22-1.61) in 1985-1988 to 2.60 (2.26-2.99) in 1997-2000 and moderately decreased in 2013-2016: RR: 1.75 (1.47-2.09). Among women no consistent time trend for RR was observed. Time trends for RR were similar regarding first non-fatal MI and fatal MI. CONCLUSIONS Over the study period, we found a decreased incidence of first MI and fatal MI in the entire study population. The initial increase of first non-fatal MI in men with diabetes needs further research. The gap between populations with and without diabetes remained.
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Affiliation(s)
- Heiner Claessen
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Auf´m Hennekamp 65, 40225, Düsseldorf, Germany.
- Institute for Health Services Research and Health Economics, Center for Health and Society, Faculty of Medicine, Heinrich Heine University, Düsseldorf, Germany.
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
| | - Maria Narres
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Auf´m Hennekamp 65, 40225, Düsseldorf, Germany
- Institute for Health Services Research and Health Economics, Center for Health and Society, Faculty of Medicine, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- KORA Study Centre, University Hospital, Augsburg, Germany
| | - Tatjana Kvitkina
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Auf´m Hennekamp 65, 40225, Düsseldorf, Germany
- Institute for Health Services Research and Health Economics, Center for Health and Society, Faculty of Medicine, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Georg Wolff
- Clinic of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty of the Heinrich, Heine University, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, University Hospital, Düsseldorf, Germany
- Institute for Clinical Diabetology, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, German Diabetes Center, Düsseldorf, Germany
| | - Andrea Icks
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Auf´m Hennekamp 65, 40225, Düsseldorf, Germany
- Institute for Health Services Research and Health Economics, Center for Health and Society, Faculty of Medicine, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
- DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
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Niedermayer F, Schauberger G, Rathmann W, Klug SJ, Thorand B, Peters A, Rospleszcz S. Clusters of longitudinal risk profile trajectories are associated with cardiometabolic diseases: Results from the population-based KORA cohort. PLoS One 2024; 19:e0300966. [PMID: 38547172 PMCID: PMC10977748 DOI: 10.1371/journal.pone.0300966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 03/07/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Multiple risk factors contribute jointly to the development and progression of cardiometabolic diseases. Therefore, joint longitudinal trajectories of multiple risk factors might represent different degrees of cardiometabolic risk. METHODS We analyzed population-based data comprising three examinations (Exam 1: 1999-2001, Exam 2: 2006-2008, Exam 3: 2013-2014) of 976 male and 1004 female participants of the KORA cohort (Southern Germany). Participants were followed up for cardiometabolic diseases, including cardiovascular mortality, myocardial infarction and stroke, or a diagnosis of type 2 diabetes, until 2016. Longitudinal multivariate k-means clustering identified sex-specific trajectory clusters based on nine cardiometabolic risk factors (age, systolic and diastolic blood pressure, body-mass-index, waist circumference, Hemoglobin-A1c, total cholesterol, high- and low-density lipoprotein cholesterol). Associations between clusters and cardiometabolic events were assessed by logistic regression models. RESULTS We identified three trajectory clusters for men and women, respectively. Trajectory clusters reflected a distinct distribution of cardiometabolic risk burden and were associated with prevalent cardiometabolic disease at Exam 3 (men: odds ratio (OR)ClusterII = 2.0, 95% confidence interval: (0.9-4.5); ORClusterIII = 10.5 (4.8-22.9); women: ORClusterII = 1.7 (0.6-4.7); ORClusterIII = 5.8 (2.6-12.9)). Trajectory clusters were furthermore associated with incident cardiometabolic cases after Exam 3 (men: ORClusterII = 3.5 (1.1-15.6); ORClusterIII = 7.5 (2.4-32.7); women: ORClusterII = 5.0 (1.1-34.1); ORClusterIII = 8.0 (2.2-51.7)). Associations remained significant after adjusting for a single time point cardiovascular risk score (Framingham). CONCLUSIONS On a population-based level, distinct longitudinal risk profiles over a 14-year time period are differentially associated with cardiometabolic events. Our results suggest that longitudinal data may provide additional information beyond single time-point measures. Their inclusion in cardiometabolic risk assessment might improve early identification of individuals at risk.
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Affiliation(s)
- Fiona Niedermayer
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Gunther Schauberger
- Chair of Epidemiology, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), München-Neuherberg, Neuherberg, Germany
- Department for Biometrics and Epidemiology, German Diabetes Research Institute, Leibniz Institute for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Stefanie J. Klug
- Chair of Epidemiology, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Neuherberg, Germany
| | - Annette Peters
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Susanne Rospleszcz
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Pott J, Kheirkhah A, Gadin JR, Kleber ME, Delgado GE, Kirsten H, Forer L, Hauck SM, Burkhardt R, Scharnagl H, Loeffler M, März W, Thiery J, Gieger C, Peters A, Silveira A, Hooft FV, Kronenberg F, Scholz M. Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis. Biol Sex Differ 2024; 15:26. [PMID: 38532495 DOI: 10.1186/s13293-024-00602-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/13/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player of lipid metabolism with higher plasma levels in women throughout their life. Statin treatment affects PCSK9 levels also showing evidence of sex-differential effects. It remains unclear whether these differences can be explained by genetics. METHODS We performed genome-wide association meta-analyses (GWAS) of PCSK9 levels stratified for sex and statin treatment in six independent studies of Europeans (8936 women/11,080 men respectively 14,825 statin-free/5191 statin-treated individuals). Loci associated in one of the strata were tested for statin- and sex-interactions considering all independent signals per locus. Independent variants at the PCSK9 gene locus were then used in a stratified Mendelian Randomization analysis (cis-MR) of PCSK9 effects on low-density lipoprotein cholesterol (LDL-C) levels to detect differences of causal effects between the subgroups. RESULTS We identified 11 loci associated with PCSK9 in at least one stratified subgroup (p < 1.0 × 10-6), including the PCSK9 gene locus and five other lipid loci: APOB, TM6SF2, FADS1/FADS2, JMJD1C, and HP/HPR. The interaction analysis revealed eight loci with sex- and/or statin-interactions. At the PCSK9 gene locus, there were four independent signals, one with a significant sex-interaction showing stronger effects in men (rs693668). Regarding statin treatment, there were two significant interactions in PCSK9 missense mutations: rs11591147 had stronger effects in statin-free individuals, and rs11583680 had stronger effects in statin-treated individuals. Besides replicating known loci, we detected two novel genome-wide significant associations: one for statin-treated individuals at 6q11.1 (within KHDRBS2) and one for males at 12q24.22 (near KSR2/NOS1), both with significant interactions. In the MR of PCSK9 on LDL-C, we observed significant causal estimates within all subgroups, but significantly stronger causal effects in statin-free subjects compared to statin-treated individuals. CONCLUSIONS We performed the first double-stratified GWAS of PCSK9 levels and identified multiple biologically plausible loci with genetic interaction effects. Our results indicate that the observed sexual dimorphism of PCSK9 and its statin-related interactions have a genetic basis. Significant differences in the causal relationship between PCSK9 and LDL-C suggest sex-specific dosages of PCSK9 inhibitors.
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Affiliation(s)
- Janne Pott
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
| | - Azin Kheirkhah
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Jesper R Gadin
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Solna, Sweden
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Holger Kirsten
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Stefanie M Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ralph Burkhardt
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Hubert Scharnagl
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Markus Loeffler
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
- SYNLAB Academy, Synlab Holding Deutschland GmbH, Mannheim and Augsburg, Germany
| | - Joachim Thiery
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
- Faculty of Medicine, University of Kiel, Kiel, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angela Silveira
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Solna, Sweden
| | - Ferdinand Van't Hooft
- Division of Cardiovascular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Solna, Sweden
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
- LIFE Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
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Nang EEK, Nangia VB, Nankap M, Narake S, Narayan KMV, Nardone P, Naseri T, Nathalie M, Neal WA, Neelapaichit N, Nejatizadeh A, Nekkantti C, Nelis K, Nenko I, Neovius M, Nervi F, Ng TP, Nguyen CT, Nguyen ND, Nguyen QN, Ni MY, Nicolescu R, Nie P, Nieto-Martínez RE, Nikitin YP, Ning G, Ninomiya T, Nishi N, Nishtar S, Noale M, Noboa OA, Nogueira H, Nordendahl M, Nordestgaard BG, Norton KI, Noto D, Nowak-Szczepanska N, Nsour MA, Nuhoğlu I, Nunes B, Nurk E, Nuwaha F, Nyirenda M, O'Neill TW, O'Reilly D, Obreja G, Ochimana C, Ochoa-Avilés AM, Oda E, Odili AN, Oh K, Ohara K, Ohlsson C, Ohtsuka R, Olafsson Ö, Oldenburg B, Olinto MTA, Oliveira IO, Omar MA, Omar SM, Onat A, Ong SK, Onland-Moret NC, Ono LM, Onodugo O, Ordunez P, Ornelas R, Ortiz AP, Ortiz PJ, Osler M, Osmond C, Ostojic SM, Ostovar A, Otero JA, Ottendahl CB, Otu A, Overvad K, Owusu-Dabo E, Oyeyemi AY, Oyeyemi AL, Paccaud FM, Padez CP, Pagkalos I, Pahomova E, de Paiva KM, Pająk A, Pajula N, Palloni A, Palmieri L, Pan WH, Panda-Jonas S, Pandey A, Pang Z, Panza F, Paoli M, Papadopoulou SK, Papandreou D, Pareja RG, Park SW, Park S, Parnell WR, Parsaeian M, Pascanu IM, Pasquet P, Patel ND, Pattussi M, Pavlyshyn H, Pechlaner R, Pećin I, Pednekar MS, Pedro JM, Peer N, Peixoto SV, Peltonen M, Pereira AC, Peres MA, Perez-Londoño A, Pérez CM, Peterkova V, Peters A, Petkeviciene J, Petrauskiene A, Petrovna Kovtun O, Pettenuzzo E, Peykari N, Pfeiffer N, Phall MC, Pham ST, Phiri FP, Pichardo RN, Pierannunzio D, Pierre-Marie P, Pigeot I, Pikhart H, Pilav A, Piler P, Pilotto L, Pistelli F, Pitakaka F, Piwonska A, Pizarro AN, Plans-Rubió P, Platonova AG, Poh BK, Pohlabeln H, Polka NS, Pop RM, Popkin BM, Popovic SR, Porta M, Posch G, Poudyal A, Poulimeneas D, Pouraram H, Pourfarzi F, Pourshams A, Poustchi H, Price AJ, Price JF, Prista A, Providencia R, Puder JJ, Pudule I, Puhakka S, Puiu M, Punab M, Qadir MS, Qasrawi RF, Qiao Q, Qorbani M, Quintana HK, Quiroga-Padilla PJ, Quoc Bao T, Rach S, Radic I, Radisauskas R, Rahimikazerooni S, Rahman M, Rahman M, Raitakari O, Raj M, Rajabov T, Rakhmatulloev S, Rakovac I, Ramachandra Rao S, Ramachandran A, Ramadan OPC, Ramires VV, Ramirez-Zea M, Ramke J, Ramos E, Ramos R, Rampal L, Rampal S, Ramsay SE, Rangelova LS, Rarra V, Rascon-Pacheco RA, Rashidi MM, Rech CR, Redon J, Reganit PFM, Regecová V, Renner JDP, Repasy JA, Reuter CP, Revilla L, Reynolds A, Rezaei N, Rezaianzadeh A, Rho Y, Ribas-Barba L, Ribeiro R, Riboli E, Rigo F, Rigotti A, Rinaldo N, Rinke de Wit TF, Risérus U, Rito AI, Ritti-Dias RM, Rivera JA, Roa RG, Robinson L, Roccaldo R, Rodrigues D, Rodriguez-Perez MDC, Rodríguez-Villamizar LA, Rodríguez AY, Roggenbuck U, Rohloff P, Rohner F, Rojas-Martinez R, Rojroongwasinkul N, Romaguera D, Romeo EL, Rosario RV, Rosengren A, Rouse I, Rouzier V, Roy JGR, Ruano MH, Rubinstein A, Rühli FJ, Ruidavets JB, Ruiz-Betancourt BS, Ruiz-Castell M, Ruiz Moreno E, Rusakova IA, Rusek W, Russell Jonsson K, Russo P, Rust P, Rutkowski M, Saamel M, Saar CG, Sabanayagam C, Sabbaghi H, Sacchini E, Sachdev HS, Sadjadi A, Safarpour AR, Safi S, Safiri S, Saghi MH, Saidi O, Saieva C, Sakata S, Saki N, Šalaj S, Salanave B, Salazar Martinez E, Salhanova A, Salmerón D, Salomaa V, Salonen JT, Salvetti M, Samoutian M, Sánchez-Abanto J, Sánchez Rodríguez I, Sandjaja, Sans S, Santa-Marina L, Santacruz E, Santos DA, Santos IS, Santos LC, Santos MP, Santos O, Santos R, Santos TR, Saramies JL, Sardinha LB, Sarrafzadegan N, Sathish T, Saum KU, Savva S, Savy M, Sawada N, Sbaraini M, Scazufca M, Schaan BD, Schaffrath Rosario A, Schargrodsky H, Schienkiewitz A, Schindler K, Schipf S, Schmidt B, Schmidt CO, Schmidt IM, Schneider A, Schnohr P, Schöttker B, Schramm S, Schramm S, Schröder H, Schultsz C, Schultz G, Schulze MB, Schutte AE, Sebert S, Sedaghattalab M, Selamat R, Sember V, Sen A, Senbanjo IO, Sepanlou SG, Sequera G, Serra-Majem L, Servais J, Ševčíková Ľ, Sewpaul R, Shalnova S, Shamah-Levy T, Shamshirgaran SM, Shanthirani CS, Sharafkhah M, Sharma SK, Sharman A, Shaw JE, Shayanrad A, Shayesteh AA, Shengelia L, Shi Z, Shibuya K, Shimizu-Furusawa H, Shimony T, Shiri R, Shrestha N, Si-Ramlee K, Siani A, Siantar R, Sibai AM, Sidossis LS, Silitrari N, Silva AM, Silva CRDM, Silva DAS, Silva KS, Sim X, Simon M, Simons J, Simons LA, Sjöberg A, Sjöström M, Skoblina EV, Skoblina NA, Slazhnyova T, Slowikowska-Hilczer J, Slusarczyk P, Smeeth L, So HK, Soares FC, Sobek G, Sobngwi E, Sodemann M, Söderberg S, Soekatri MYE, Soemantri A, Sofat R, Solfrizzi V, Solovieva YV, Somi MH, Sonestedt E, Song Y, Soofi S, Sørensen TIA, Sørgjerd EP, Sossa Jérome C, Soto-Rojas VE, Soumaré A, Sousa-Poza A, Sovic S, Sparboe-Nilsen B, Sparrenberger K, Spencer PR, Spinelli A, Spiroski I, Staessen JA, Stamm H, Stang A, Starc G, Staub K, Stavreski B, Steene-Johannessen J, Stehle P, Stein AD, Steinsbekk S, Stergiou GS, Stessman J, Stevanović R, Stieber J, Stöckl D, Stokwiszewski J, Stoyanova E, Stratton G, Stronks K, Strufaldi MW, Sturua L, Suárez-Medina R, Suarez-Ortegón MF, Suebsamran P, Sugiyama M, Suka M, Sulo G, Sun CA, Sun L, Sund M, Sundström J, Sung YT, Sunyer J, Suriyawongpaisal P, Sweis NWG, Swinburn BA, Sy RG, Sylva RC, Szponar L, Tabone L, Tai ES, Takuro F, Tambalis KD, Tammesoo ML, Tamosiunas A, Tan EJ, Tang X, Tanrygulyyeva M, Tanser F, Tao Y, Tarawneh MR, Tarp J, Tarqui-Mamani CB, Taxová Braunerová R, Taylor A, Taylor J, Tchibindat F, Te Velde S, Tebar WR, Tell GS, Tello T, Tessema M, Tham YC, Thankappan KR, Theobald H, Theodoridis X, Thomas N, Thorand B, Thrift AG, Tichá Ľ, Timmermans EJ, Tjandrarini DH, Tjonneland A, Tolonen HK, Tolstrup JS, Tomaszewski M, Topbas M, Topór-Mądry R, Torheim LE, Tornaritis MJ, Torrent M, Torres-Collado L, Toselli S, Touloumi G, Traissac P, Tran TTH, Tremblay MS, Triantafyllou A, Trichopoulos D, Trichopoulou A, Trinh OTH, Trivedi A, Tshepo L, Tsigga M, Tsintavis P, Tsugane S, Tuitele J, Tuliakova AM, Tulloch-Reid MK, Tullu F, Tuomainen TP, Tuomilehto J, Twig G, Tynelius P, Tzala E, Tzotzas T, Tzourio C, Udoji N, Ueda P, Ugel E, Ukoli FAM, Ulmer H, Unal B, Usupova Z, Uusitalo HMT, Uysal N, Vaitkeviciute J, Valdivia G, Vale S, Valvi D, van Dam RM, van den Born BJ, Van der Heyden J, van der Schouw YT, Van Herck K, Van Lippevelde W, Van Minh H, Van Schoor NM, van Valkengoed IGM, Vanderschueren D, Vanuzzo D, Varbo A, Varela-Moreiras G, Vargas LN, Varona-Pérez P, Vasan SK, Vasques DG, Vatasescu R, Vega T, Veidebaum T, Velasquez-Melendez G, Velika B, Verloigne M, Veronesi G, Verschuren WMM, Victora CG, Viegi G, Viet L, Vik FN, Vilar M, Villalpando S, Vioque J, Viriyautsahakul N, Virtanen JK, Visser M, Visvikis-Siest S, Viswanathan B, Vladulescu M, Vlasoff T, Vocanec D, Vollenweider P, Völzke H, Vourli G, Voutilainen A, Vrijheid M, Vrijkotte TGM, Vuletić S, Wade AN, Waldhör T, Walton J, Wambiya EOA, Wan Bebakar WM, Wan Mohamud WN, Wanderley Júnior RDS, Wang C, Wang H, Wang MD, Wang N, Wang Q, Wang X, Wang YX, Wang YW, Wannamethee SG, Wareham N, Wartha O, Weber A, Wedderkopp N, Weghuber D, Wei W, Weres A, Werner B, Westbury LD, Whincup PH, Wichstrøm L, Wickramasinghe K, Widhalm K, Widyahening IS, Więcek A, Wild PS, Wilks RJ, Willeit J, Willeit P, Williams J, Wilsgaard T, Wirth JP, Wojtyniak B, Woldeyohannes M, Wolf K, Wong-McClure RA, Wong A, Wong EB, Wong JE, Wong TY, Woo J, Woodward M, Wu FC, Wu HY, Wu J, Wu LJ, Wu S, Wyszyńska J, Xu H, Xu L, Yaacob NA, Yamborisut U, Yan L, Yan W, Yang L, Yang X, Yang Y, Yardim N, Yasuharu T, Yépez García M, Yiallouros PK, Yngve A, Yoosefi M, Yoshihara A, Yotov Y, You QS, You SL, Younger-Coleman NO, Yu YL, Yu Y, Yusof SM, Yusoff AF, Zaccagni L, Zafiropulos V, Zainuddin AA, Zakavi SR, Zamani F, Zambon S, Zampelas A, Zamrazilová H, Zapata ME, Zargar AH, Zaw KK, Zayed AA, Zdrojewski T, Żegleń M, Zejglicova K, Zeljkovic Vrkic T, Zeng Y, Zentai A, Zhang B, Zhang L, Zhang ZY, Zhao D, Zhao MH, Zhao W, Zhecheva YV, Zhen S, Zheng W, Zheng Y, Zholdin B, Zhou M, Zhu D, Zimmet P, Zins M, Zitt E, Zocalo Y, Zoghlami N, Zuñiga Cisneros J, Zuziak M, Ezzati M. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 2024; 403:1027-1050. [PMID: 38432237 PMCID: PMC7615769 DOI: 10.1016/s0140-6736(23)02750-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/22/2023] [Accepted: 12/05/2023] [Indexed: 03/05/2024]
Abstract
BACKGROUND Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. METHODS We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5-19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For school-aged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). FINDINGS From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%) with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and 42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents, the increases in double burden were driven by increases in obesity, and decreases in double burden by declining underweight or thinness. INTERPRETATION The combined burden of underweight and obesity has increased in most countries, driven by an increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of underweight while curbing and reversing the increase in obesity. FUNDING UK Medical Research Council, UK Research and Innovation (Research England), UK Research and Innovation (Innovate UK), and European Union.
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Lin JS, Petrera A, Hauck SM, Müller CL, Peters A, Thorand B. Associations of Proteomics With Hypertension and Systolic Blood Pressure: KORA S4/F4/FF4 and KORA-Age1/Age2 Cohort Studies. Hypertension 2024. [PMID: 38445514 DOI: 10.1161/hypertensionaha.123.22614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 02/19/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Hypertension, a complex condition, is primarily defined based on blood pressure readings without involving its pathophysiological mechanisms. We aimed to identify biomarkers through a proteomic approach, thereby enhancing the future definition of hypertension with insights into its molecular mechanisms. METHODS The discovery analysis included 1560 participants, aged 55 to 74 years at baseline, from the KORA (Cooperative Health Research in the Region of Augsburg) S4/F4/FF4 cohort study, with 3332 observations over a median of 13.4 years of follow-up. Generalized estimating equations were used to estimate the associations of 233 plasma proteins with hypertension and systolic blood pressure (SBP). For validation, proteins significantly associated with hypertension or SBP in discovery analysis were validated in the KORA-Age1/Age2 cohort study (1024 participants, 1810 observations). A 2-sample Mendelian randomization analysis was conducted to infer causalities of validated proteins with SBP. RESULTS Discovery analysis identified 49 proteins associated with hypertension and 99 associated with SBP. Validation in the KORA-Age1/Age2 study replicated 7 proteins associated with hypertension and 23 associated with SBP. Three proteins, NT-proBNP (N-terminal pro-B-type natriuretic peptide), KIM1 (kidney injury molecule 1), and OPG (osteoprotegerin), consistently showed positive associations with both outcomes. Five proteins demonstrated potential causal associations with SBP in Mendelian randomization analysis, including NT-proBNP and OPG. CONCLUSIONS We identified and validated 7 hypertension-associated and 23 SBP-associated proteins across 2 cohort studies. KIM1, NT-proBNP, and OPG demonstrated robust associations, and OPG was identified for the first time as associated with blood pressure. For NT-proBNP (protective) and OPG, causal associations with SBP were suggested.
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Affiliation(s)
- Jie-Sheng Lin
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (J.-s.L., A. Peters, B.T.)
- Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Pettenkofer School of Public Health, Germany (J.-s.L., B.T.)
| | - Agnese Petrera
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (J.-s.L., A. Peters, B.T.)
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (A. Petrera, S.M.H.)
| | - Stefanie M Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (A. Petrera, S.M.H.)
| | - Christian L Müller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (C.L.M.)
- Department of Statistics, Ludwig-Maximilians-Universität München, Munich, Germany. (C.L.M.)
- Center for Computational Mathematics, Flatiron Institute, New York, NY (C.L.M.)
| | - Annette Peters
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany.(A. Peters)
- German Center for Diabetes Research, Partner München-Neuherberg, Germany (A. Peters, B.T.)
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. (J.-s.L., A. Peters, B.T.)
- Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Pettenkofer School of Public Health, Germany (J.-s.L., B.T.)
- German Center for Diabetes Research, Partner München-Neuherberg, Germany (A. Peters, B.T.)
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Maushagen J, Addin NS, Schuppert C, Ward-Caviness CK, Nattenmüller J, Adamski J, Peters A, Bamberg F, Schlett CL, Wang-Sattler R, Rospleszcz S. Serum metabolite signatures of cardiac function and morphology in individuals from a population-based cohort. Biomark Res 2024; 12:31. [PMID: 38444025 PMCID: PMC10916302 DOI: 10.1186/s40364-024-00578-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/24/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Changes in serum metabolites in individuals with altered cardiac function and morphology may exhibit information about cardiovascular disease (CVD) pathway dysregulations and potential CVD risk factors. We aimed to explore associations of cardiac function and morphology, evaluated using magnetic resonance imaging (MRI) with a large panel of serum metabolites. METHODS Cross-sectional data from CVD-free individuals from the population-based KORA cohort were analyzed. Associations between 3T-MRI-derived left ventricular (LV) function and morphology parameters (e.g., volumes, filling rates, wall thickness) and markers of carotid plaque with metabolite profile clusters and single metabolites as outcomes were assessed by adjusted multinomial logistic regression and linear regression models. RESULTS In 360 individuals (mean age 56.3 years; 41.9% female), 146 serum metabolites clustered into three distinct profiles that reflected high-, intermediate- and low-CVD risk. Higher stroke volume (relative risk ratio (RRR): 0.53, 95%-CI [0.37; 0.76], p-value < 0.001) and early diastolic filling rate (RRR: 0.51, 95%-CI [0.37; 0.71], p-value < 0.001) were most strongly protectively associated against the high-risk profile compared to the low-risk profile after adjusting for traditional CVD risk factors. Moreover, imaging markers were associated with 10 metabolites in linear regression. Notably, negative associations of stroke volume and early diastolic filling rate with acylcarnitine C5, and positive association of function parameters with lysophosphatidylcholines, diacylphosphatidylcholines, and acylalkylphosphatidylcholines were observed. Furthermore, there was a negative association of LV wall thickness with alanine, creatinine, and symmetric dimethylarginine. We found no significant associations with carotid plaque. CONCLUSIONS Serum metabolite signatures are associated with cardiac function and morphology even in individuals without a clinical indication of CVD.
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Affiliation(s)
- Juliane Maushagen
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Nuha Shugaa Addin
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Christopher Schuppert
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, U.S. EPA, Chapel Hill, NC, USA
| | - Johanna Nattenmüller
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, 117597, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany
- German Center for Diabetes Research, DZD, Neuherberg, Germany
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Rui Wang-Sattler
- German Center for Diabetes Research, DZD, Neuherberg, Germany
- Institute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany.
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig- Maximilians-Universität (LMU), München, Germany.
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center - University of Freiburg, University of Freiburg, Freiburg, Germany.
- German Center for Cardiovascular Disease Research (DZHK), Munich Heart Alliance, Munich, Germany.
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Ratter-Rieck JM, Shi M, Suhre K, Prehn C, Adamski J, Rathmann W, Thorand B, Roden M, Peters A, Wang-Sattler R, Herder C. Omentin associates with serum metabolite profiles indicating lower diabetes risk: KORA F4 Study. BMJ Open Diabetes Res Care 2024; 12:e003865. [PMID: 38442989 DOI: 10.1136/bmjdrc-2023-003865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/01/2024] [Indexed: 03/07/2024] Open
Abstract
INTRODUCTION Circulating omentin levels have been positively associated with insulin sensitivity. Although a role for adiponectin in this relationship has been suggested, underlying mechanisms remain elusive. In order to reveal the relationship between omentin and systemic metabolism, this study aimed to investigate associations of serum concentrations of omentin and metabolites. RESEARCH DESIGN AND METHODS This study is based on 1124 participants aged 61-82 years from the population-based KORA (Cooperative Health Research in the Region of Augsburg) F4 Study, for whom both serum omentin levels and metabolite concentration profiles were available. Associations were assessed with five multivariable regression models, which were stepwise adjusted for multiple potential confounders, including age, sex, body mass index, waist-to-hip ratio, lifestyle markers (physical activity, smoking behavior and alcohol consumption), serum adiponectin levels, high-density lipoprotein cholesterol, use of lipid-lowering or anti-inflammatory medication, history of myocardial infarction and stroke, homeostasis model assessment 2 of insulin resistance, diabetes status, and use of oral glucose-lowering medication and insulin. RESULTS Omentin levels significantly associated with multiple metabolites including amino acids, acylcarnitines, and lipids (eg, sphingomyelins and phosphatidylcholines (PCs)). Positive associations for several PCs, such as diacyl (PC aa C32:1) and alkyl-alkyl (PC ae C32:2), were significant in models 1-4, whereas those with hydroxytetradecenoylcarnitine (C14:1-OH) were significant in all five models. Omentin concentrations were negatively associated with several metabolite ratios, such as the valine-to-PC ae C32:2 and the serine-to-PC ae C32:2 ratios in most models. CONCLUSIONS Our results suggest that omentin may influence insulin sensitivity and diabetes risk by changing systemic lipid metabolism, but further mechanistic studies investigating effects of omentin on metabolism of insulin-sensitive tissues are needed.
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Affiliation(s)
- Jacqueline M Ratter-Rieck
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
| | - Mengya Shi
- TUM School of Medicine and Health, Technical University of Munich (TUM), Munich, Germany
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Partner Neuherberg, Neuherberg, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Wolfgang Rathmann
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Barbara Thorand
- German Center for Diabetes Research, Partner Neuherberg, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Annette Peters
- German Center for Diabetes Research, Partner Neuherberg, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Partner Neuherberg, Neuherberg, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
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18
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Atasoy S, Henningsen P, Johar H, Middeke M, Sattel H, Linkohr B, Rückert-Eheberg IM, Heier M, Peters A, Ladwig KH. Hypertension in the first blood pressure reading and the risk of cardiovascular disease mortality in the general population: findings from the prospective KORA study. J Hypertens 2024; 42:521-529. [PMID: 38088424 DOI: 10.1097/hjh.0000000000003629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
BACKGROUND The risk of cardiovascular disease (CVD) mortality in individuals with an alerting reaction, assessed by hypertension in the first blood pressure (BP) reading but normal BP in further readings, remains unknown in the general population. METHODS AND RESULTS In a sample of 11 146 adults (51.5% men and 48.5% women) with a mean age of 47.1 years (SD ± 12.3) from a German population-based cohort, we analyzed risk factors and CVD mortality risk associated with an alerting reaction. An alerting reaction was prevalent in 10.2% of the population and associated with sociodemographic, lifestyle, and somatic CVD risk factors. Within a mean follow-up period of 22.7 years (SD ± 7.05 years; max: 32 years; 253 201 person years), 1420 (12.7%) CVD mortality cases were observed. The CVD mortality rate associated with an alerting reaction was significantly higher than in normotension (64 vs. 32 cases/10 000 person-years), but lower than hypertension (118 cases/10 000 person-years). Correspondingly, the alerting reaction was associated with a 23% higher hazard ratio of CVD mortality than normal blood pressure [hazard ratio 1.23 (95% confidence interval 1.02-1.49), P = 0.04]. However, adjustment for antihypertensive medication use attenuated this association [1.19 (0.99-1.44), P = 0.06]. CONCLUSION The results may warrant monitoring of an alerting reaction as a preventive measure of CVD mortality in untreated individuals with elevated first BP readings, as well as optimized treatment in treated individuals.
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Affiliation(s)
- Seryan Atasoy
- Department of Psychosomatic Medicine and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Psychosomatic Medicine and Psychotherapy, University of Giessen and Marburg, Germany
| | - Peter Henningsen
- Department of Psychosomatic Medicine and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Hamimatunnisa Johar
- Department of Psychosomatic Medicine and Psychotherapy, University of Giessen and Marburg, Germany
- Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, Selangor, Malaysia
| | - Martin Middeke
- Hypertension Center Munich, a European Society of Hypertension (ESH) Center of Excellence, Munich, Germany
| | - Heribert Sattel
- Department of Psychosomatic Medicine and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum Munich - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Partnersite Munich
| | - Ina-Maria Rückert-Eheberg
- Institute of Epidemiology, Helmholtz Zentrum Munich - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum Munich - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Kora Study Centre, University Hospital of Augsburg, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum Munich - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Partnersite Munich
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Karl-Heinz Ladwig
- Department of Psychosomatic Medicine and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK), Partnersite Munich
- Hypertension Center Munich, a European Society of Hypertension (ESH) Center of Excellence
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19
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Harrer P, Inderhees J, Zhao C, Schormair B, Tilch E, Gieger C, Peters A, Jöhren O, Fleming T, Nawroth PP, Berger K, Hermesdorf M, Winkelmann J, Schwaninger M, Oexle K. Phenotypic and genome-wide studies on dicarbonyls: major associations to glomerular filtration rate and gamma-glutamyltransferase activity. EBioMedicine 2024; 101:105007. [PMID: 38354534 PMCID: PMC10875252 DOI: 10.1016/j.ebiom.2024.105007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND The dicarbonyl compounds methylglyoxal (MG), glyoxal (GO) and 3-deoxyglucosone (3-DG) have been linked to various diseases. However, disease-independent phenotypic and genotypic association studies with phenome-wide and genome-wide reach, respectively, have not been provided. METHODS MG, GO and 3-DG were measured by LC-MS in 1304 serum samples of two populations (KORA, n = 482; BiDirect, n = 822) and assessed for associations with genome-wide SNPs (GWAS) and with phenome-wide traits. Redundancy analysis (RDA) was used to identify major independent trait associations. FINDINGS Mutual correlations of dicarbonyls were highly significant, being stronger between MG and GO (ρ = 0.6) than between 3-DG and MG or GO (ρ = 0.4). Significant phenotypic results included associations of all dicarbonyls with sex, waist-to-hip ratio, glomerular filtration rate (GFR), gamma-glutamyltransferase (GGT), and hypertension, of MG and GO with age and C-reactive protein, of GO and 3-DG with glucose and antidiabetics, of MG with contraceptives, of GO with ferritin, and of 3-DG with smoking. RDA revealed GFR, GGT and, in case of 3-DG, glucose as major contributors to dicarbonyl variance. GWAS did not identify genome-wide significant loci. SNPs previously associated with glyoxalase activity did not reach nominal significance. When multiple testing was restricted to the lead SNPs of GWASs on the traits selected by RDA, 3-DG was found to be associated (p = 2.3 × 10-5) with rs1741177, an eQTL of NF-κB inhibitor NFKBIA. INTERPRETATION This large-scale, population-based study has identified numerous associations, with GFR and GGT being of pivotal importance, providing unbiased perspectives on dicarbonyls beyond the current state. FUNDING Deutsche Forschungsgemeinschaft, Helmholtz Munich, German Centre for Cardiovascular Research (DZHK), German Federal Ministry of Research and Education (BMBF).
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Affiliation(s)
- Philip Harrer
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julica Inderhees
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; Bioanalytic Core Facility, Center for Brain, Behavior and Metabolism, University of Lübeck, Germany; German Centre for Cardiovascular Research (DZHK), Hamburg-Lübeck-Kiel, Germany
| | - Chen Zhao
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany
| | - Barbara Schormair
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Erik Tilch
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Munich, Neuherberg, Germany; Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, Neuherberg, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Olaf Jöhren
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; Bioanalytic Core Facility, Center for Brain, Behavior and Metabolism, University of Lübeck, Germany
| | - Thomas Fleming
- Department of Internal Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter P Nawroth
- Department of Internal Medicine, University of Heidelberg, Heidelberg, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Marco Hermesdorf
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Centre for Mental Health (DZPG), Munich-Augsburg, Germany
| | - Markus Schwaninger
- Institute for Experimental and Clinical Pharmacology and Toxicology, Center of Brain, Behavior and Metabolism, University of Lubeck, Lubeck, Germany; German Centre for Cardiovascular Research (DZHK), Hamburg-Lübeck-Kiel, Germany
| | - Konrad Oexle
- Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany; Neurogenetic Systems Analysis Group, Institute of Neurogenomics, Helmholtz Munich, Neuherberg, Germany.
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20
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Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Melloni GEM, Kanoni S, Rayner NW, Bocher O, Arruda AL, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Thangam M, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Franco OH, Frayling TM, Freedman BI, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Gordon-Larsen P, Gross M, Guare LA, Hackinger S, Hakaste L, Han S, Hattersley AT, Herder C, Horikoshi M, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen T, Kamanu FK, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee KM, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Ligthart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lynch JA, Lyssenko V, Maeda S, Mamakou V, Mansuri SR, Matsuda K, Meitinger T, Melander O, Metspalu A, Mo H, Morris AD, Moura FA, Nadler JL, Nalls MA, Nayak U, Ntalla I, Okada Y, Orozco L, Patel SR, Patil S, Pei P, Pereira MA, Peters A, Pirie FJ, Polikowsky HG, Porneala B, Prasad G, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sandow K, Sankareswaran A, Sattar N, Schönherr S, Shahriar M, Shen B, Shi J, Shin DM, Shojima N, Smith JA, So WY, Stančáková A, Steinthorsdottir V, Stilp AM, Strauch K, Taylor KD, Thorand B, Thorsteinsdottir U, Tomlinson B, Tran TC, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Wacher-Rodarte N, Wheeler E, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamamoto K, Yoon K, Yu C, Yuan JM, Yusuf S, Zawistowski M, Zhang L, Zheng W, Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Fornage M, Hanis CL, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Yokota M, Kardia SLR, Peyser PA, Pankow JS, Engert JC, Bonnefond A, Froguel P, Wilson JG, Sheu WHH, Wu JY, Hayes MG, Ma RCW, Wong TY, Mook-Kanamori DO, Tuomi T, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, Chen YDI, Rich SS, McKean-Cowdin R, Grallert H, Cheng CY, Ghanbari M, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Bowden DW, Palmer CNA, Kooner JS, Kooperberg C, Liu S, North KE, Saleheen D, Hansen T, Pedersen O, Wareham NJ, Lee J, Kim BJ, Millwood IY, Walters RG, Stefansson K, Ahlqvist E, Goodarzi MO, Mohlke KL, Langenberg C, Haiman CA, Loos RJF, Florez JC, Rader DJ, Ritchie MD, Zöllner S, Mägi R, Marston NA, Ruff CT, van Heel DA, Finer S, Denny JC, Yamauchi T, Kadowaki T, Chambers JC, Ng MCY, Sim X, Below JE, Tsao PS, Chang KM, McCarthy MI, Meigs JB, Mahajan A, Spracklen CN, Mercader JM, Boehnke M, Rotter JI, Vujkovic M, Voight BF, Morris AP, Zeggini E. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature 2024; 627:347-357. [PMID: 38374256 PMCID: PMC10937372 DOI: 10.1038/s41586-024-07019-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 01/03/2024] [Indexed: 02/21/2024]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
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Affiliation(s)
- Ken Suzuki
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Henry J Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Xianyong Yin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kim M Lorenz
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alicia Huerta-Chagoya
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Giorgio E M Melloni
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Nigel W Rayner
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ana Luiza Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Graduate School of Experimental Medicine, Technical University of Munich, Munich, Germany
- Munich School for Data Science, Helmholtz Munich, Neuherberg, Germany
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Simon S K Lee
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lauren E Petty
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip Schroeder
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brett Vanderwerff
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fiona Bragg
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sanghoon Moon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - James P Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Jung-Jin Lee
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian Pan
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, Ontario, Canada
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yang Hai
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamar Sofer
- Department of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard University, Boston, MA, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Darryl Nousome
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Soo-Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meng Sun
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lin Tong
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suraj S Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Victor J Y Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Yoonjung Yoonie Joo
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bram Peter Prins
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lisa R Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Edmond Kabagambe
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Academics, Ochsner Health, New Orleans, LA, USA
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Anny H Xiang
- Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, CA, USA
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jingyi Tan
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - K Alaine Broadaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jinrui Cui
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Manonanthini Thangam
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Linda S Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carlos A Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Thomas A Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Adam S Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Li-Ching Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ji Chen
- Exeter Centre of Excellence in Diabetes (ExCEeD), Exeter Medical School, University of Exeter, Exeter, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Shyh-Huei Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lee-Ming Chuang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Mary Cushman
- Department of Medicine, University of Vermont, Colchester, VT, USA
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus, University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Swapan K Das
- Section of Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shufa Du
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Barry I Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Pauline Genter
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Maria Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay A Guare
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sophie Hackinger
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Liisa Hakaste
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | | | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Annie-Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Willa Hsueh
- Department of Internal Medicine, Diabetes and Metabolism Research Center, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mengna Huang
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Farzana Jasmine
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Jost B Jonas
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Frederick K Kamanu
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fouad R Kandeel
- Department of Clinical Diabetes, Endocrinology and Metabolism, Department of Translational Research and Cellular Therapeutics, City of Hope, Duarte, CA, USA
| | | | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Jacob M Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Abel N Kho
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Muhammad G Kibriya
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Duk-Hwan Kim
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Myung-Shik Lee
- Soochunhyang Institute of Medi-bio Science and Division of Endocrinology, Department of Internal Medicine, Soochunhyang University College of Medicine, Cheonan, South Korea
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Symen Ligthart
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Adam E Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St Louis, MO, USA
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andrea O Luk
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Xi Luo
- Department of Biostatistics and Data Science, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
| | - Shiro Maeda
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara, Japan
| | - Vasiliki Mamakou
- Dromokaiteio Psychiatric Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Sohail Rafik Mansuri
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Koichi Matsuda
- Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Olle Melander
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Huan Mo
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew D Morris
- Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Filipe A Moura
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jerry L Nadler
- Department of Medicine and Pharmacology, New York Medical College, Valhalla, NY, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Sanjay R Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Snehal Patil
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Mark A Pereira
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Fraser J Pirie
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Hannah G Polikowsky
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Campus, Ghaziabad, India
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Roden
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katheryn Roll
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Kevin Sandow
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alagu Sankareswaran
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Mohammad Shahriar
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Dong Mun Shin
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wing Yee So
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | | | - Adrienne M Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Biostatistics, Epidemiology, and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Chair of Genetic Epidemiology, Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Tam C Tran
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Fuu-Jen Tsai
- Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
- National School of Public Health, Madrid, Spain
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxiología Ambiental, Instituto de Investigaciones Biomédicas, UNAM, Mexico City, Mexico
| | - Miriam S Udler
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jan B van Klinken
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Chemistry, Laboratory of Genetic Metabolic Disease, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Hospital, Los Angeles, CA, USA
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Ko Willems van Dijk
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Chittaranjan S Yajnik
- Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Leslie J Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, UCI Irvine School of Medicine, Irvine, CA, USA
| | - Michiya Igase
- Department of Anti-Aging Medicine, Ehime University Graduate School of Medicine, Touon, Japan
| | - Eli Ipp
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Michael A Province
- Division of Statistical Genomics, Washington University School of Medicine, St Louis, MO, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Ophthalmology and Visual Sciences Key Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Diane M Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James C Engert
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Amélie Bonnefond
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - James G Wilson
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Wayne H H Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Hong Kong, China
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tiinamaija Tuomi
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- Science and Engineering Research Board (SERB), Department of Science and Technology, Ministry of Science and Technology, Government of India, New Delhi, India
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Michèle M Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Habibul Ahsan
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, University of Chicago, Chicago, IL, USA
| | - Ayesha A Motala
- Department of Diabetes and Endocrinology, Nelson R. Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyong-Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Woon-Puay Koh
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Dundee, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
- Department of Medicine, Brown University Alpert School of Medicine, Providence, RI, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Juyoung Lee
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen, Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Emma Ahlqvist
- Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Mark O Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité-Universitätsmedizin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Jose C Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel J Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Translational Medicine and Therapeutics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Precision Medicine, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Nicholas A Marston
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Christian T Ruff
- TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Sarah Finer
- Institute for Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Joshua C Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Toranomon Hospital, Tokyo, Japan
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jennifer E Below
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - James B Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Genentech, South San Francisco, CA, USA
| | - Cassandra N Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Josep M Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK.
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany.
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Prapiadou S, Živković L, Thorand B, George MJ, van der Laan SW, Malik R, Herder C, Koenig W, Ueland T, Kleveland O, Aukrust P, Gullestad L, Bernhagen J, Pasterkamp G, Peters A, Hingorani AD, Rosand J, Dichgans M, Anderson CD, Georgakis MK. Proteogenomic Data Integration Reveals CXCL10 as a Potentially Downstream Causal Mediator for IL-6 Signaling on Atherosclerosis. Circulation 2024; 149:669-683. [PMID: 38152968 PMCID: PMC10922752 DOI: 10.1161/circulationaha.123.064974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 11/17/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Genetic and experimental studies support a causal involvement of IL-6 (interleukin-6) signaling in atheroprogression. Although trials targeting IL-6 signaling are underway, any benefits must be balanced against an impaired host immune response. Dissecting the mechanisms that mediate the effects of IL-6 signaling on atherosclerosis could offer insights about novel drug targets with more specific effects. METHODS Leveraging data from 522 681 individuals, we constructed a genetic instrument of 26 variants in the gene encoding the IL-6R (IL-6 receptor) that proxied for pharmacological IL-6R inhibition. Using Mendelian randomization, we assessed its effects on 3281 plasma proteins quantified with an aptamer-based assay in the INTERVAL cohort (n=3301). Using mediation Mendelian randomization, we explored proteomic mediators of the effects of genetically proxied IL-6 signaling on coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease. For significant mediators, we tested associations of their circulating levels with incident cardiovascular events in a population-based study (n=1704) and explored the histological, transcriptomic, and cellular phenotypes correlated with their expression levels in samples from human atherosclerotic lesions. RESULTS We found significant effects of genetically proxied IL-6 signaling on 70 circulating proteins involved in cytokine production/regulation and immune cell recruitment/differentiation, which correlated with the proteomic effects of pharmacological IL-6R inhibition in a clinical trial. Among the 70 significant proteins, genetically proxied circulating levels of CXCL10 (C-X-C motif chemokine ligand 10) were associated with risk of coronary artery disease, large artery atherosclerotic stroke, and peripheral artery disease, with up to 67% of the effects of genetically downregulated IL-6 signaling on these end points mediated by decreases in CXCL10. Higher midlife circulating CXCL10 levels were associated with a larger number of cardiovascular events over 20 years, whereas higher CXCL10 expression in human atherosclerotic lesions correlated with a larger lipid core and a transcriptomic profile reflecting immune cell infiltration, adaptive immune system activation, and cytokine signaling. CONCLUSIONS Integrating multiomics data, we found a proteomic signature of IL-6 signaling activation and mediators of its effects on cardiovascular disease. Our analyses suggest the interferon-γ-inducible chemokine CXCL10 to be a potentially causal mediator for atherosclerosis in 3 vascular compartments and, as such, could serve as a promising drug target for atheroprotection.
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Affiliation(s)
- Savvina Prapiadou
- University of Patras School of Medicine, Patras, Greece
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luka Živković
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Marc J. George
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rainer Malik
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, Partner Düsseldorf, Neuherberg, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
- German Heart Center Munich, Technical University of Munich, Munich, Germany
| | - Thor Ueland
- Thrombosis Research Center (TREC), Division of internal medicine, University hospital of North Norway, Tromsø, Norway
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ola Kleveland
- Clinic of Cardiology, St Olavs Hospital, Trondheim, Norway
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Pål Aukrust
- Research Institute of Internal Medicine, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Lars Gullestad
- Department of Cardiology Oslo University Hospital Rikshospitalet, Oslo, Norway
| | - Jürgen Bernhagen
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gerard Pasterkamp
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany
- Munich Heart Alliance, German Center for Cardiovascular Health (DZHK e.V., partner-site Munich), Munich, Germany
| | - Aroon D. Hingorani
- Department of Clinical Pharmacology, Division of Medicine, University College London, London, United Kingdom
- Centre for Translational Genomics, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Section of Clinical Immunology and Infectious Diseases, Oslo University Hospital Rikshospitalet, Oslo, Norway
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
| | - Christopher D. Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Marios K. Georgakis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Stroke and Dementia Research, Ludwig-Maximilians-University of Munich, Munich, Germany
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22
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Vogli M, Peters A, Wolf K, Thorand B, Herder C, Koenig W, Cyrys J, Maestri E, Marmiroli N, Karrasch S, Zhang S, Pickford R. Long-term exposure to ambient air pollution and inflammatory response in the KORA study. Sci Total Environ 2024; 912:169416. [PMID: 38123091 DOI: 10.1016/j.scitotenv.2023.169416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/27/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023]
Abstract
Previous studies consistently showed an association between fine atmospheric particulate matter (PM2.5) and cardiovascular diseases. Concerns about adverse health effects of ultrafine particles (UFP) are growing but long-term studies are still scarce. In this study, we examined the association between long-term exposure to ambient air pollutants and blood biomarkers of inflammation and coagulation, including fibrinogen, high-sensitivity C-reactive protein (hs-CRP), serum amyloid A (SAA) adiponectin and interleukin-6 (IL-6), measured in the German KORA-S4 cohort study (1999-2001). IL-6 was available for older participants only, who were therefore considered as a subsample. Annual mean concentrations of UFP (as particle number concentration), particulate matter in different particles sizes (PM10, PMcoarse, PM2.5, PM2.5 absorbance), ozone (O3), and nitrogen oxides (NO2, NOX) were estimated by land-use regression models and assigned to participants' home addresses. We performed a multiple linear regression between each pollutant and each biomarker with adjustment for confounders. Per 1 interquartile range (IQR, 1945 particles/cm3) increase of UFP, fibrinogen increased by 0.70 % (0.04; 1.37) and hs-CRP increased by 3.16 % (-0.52; 6.98). Adiponectin decreased by -2.53 % (-4.78; -0.24) per 1 IQR (1.4 μg/m3) increase of PM2.5. Besides, PM2.5 was associated with increased IL-6 in the subsample. In conclusion, we observed that long-term exposure to air pollutants, including both fine and ultrafine particles, was associated with higher concentrations of pro-inflammatory and lower concentrations of an anti-inflammatory blood biomarkers, which is consistent with an increased risk for cardiovascular disease observed for long-term exposure to air pollutants.
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Affiliation(s)
- Megi Vogli
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, 81377 Munich, Germany; Munich Heart Alliance, German Center for Cardiovascular Health (DZHK e.V., partner-site Munich), Munich, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, 81377 Munich, Germany; German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany; Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Wolfgang Koenig
- German Research Center for Cardiovascular Disease, Partner Site of Munich Heart Alliance, Munich, Germany; Deutsches Herzzentrum München, Technische Universität München, Munich, Germany; Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Josef Cyrys
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Elena Maestri
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; National Interuniversity Consortium for Environmental Sciences (CINSA), Parco Area delle Scienze, 43124 Parma, Italy
| | - Nelson Marmiroli
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; National Interuniversity Consortium for Environmental Sciences (CINSA), Parco Area delle Scienze, 43124 Parma, Italy
| | - Stefan Karrasch
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital LMU Munich, Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Siqi Zhang
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Regina Pickford
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany.
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23
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Lange de Luna J, Nounu A, Neumeyer S, Sinke L, Wilson R, Hellbach F, Matías-García PR, Delerue T, Winkelmann J, Peters A, Thorand B, Beekman M, Heijmans BT, Slagboom E, Gieger C, Linseisen J, Waldenberger M. Epigenome-wide association study of dietary fatty acid intake. Clin Epigenetics 2024; 16:29. [PMID: 38365790 PMCID: PMC10874013 DOI: 10.1186/s13148-024-01643-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 02/09/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS). RESULTS DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed. Below the Bonferroni correction threshold (p < 7.17 × 10-8), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 × 10-5, 95%CI: 1.28 × 10-5-2.73 × 10-5, P value: 6.98 × 10-8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10-5, 95%CI: 6.25 × 10-5-1.33 × 10-4, P value: 6.75 × 10-8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10-7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10-5, 95% CI: 1.27 × 10-5-2.73 × 10-5, P value = 5.99 × 10-8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10-5, 95% CI: 1.31 × 10-5-2.83 × 10-5, P value = 1.00 × 10-7 and beta: 2.19 × 10-5, 95% CI: 1.41 × 10-5-2.97 × 10-5, P value = 5.91 × 10-8 respectively). CONCLUSIONS Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes.
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Affiliation(s)
- Julia Lange de Luna
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Aayah Nounu
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Sonja Neumeyer
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Lucy Sinke
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Fabian Hellbach
- Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital of Augsburg, 86156, Augsburg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Pamela R Matías-García
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Klinikum Rechts Der Isar, Chair Neurogenetics, Technical University of Munich, Munich, Germany
- Klinikum Rechts Der Isar, Institute of Human Genetics, Technical University of Munich, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC, Leiden, The Netherlands
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany
| | - Jakob Linseisen
- Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital of Augsburg, 86156, Augsburg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU Munich, 80539, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum Munich, German Research Center for Environmental Health, 85764, Neuherberg, Germany.
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24
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Taj T, Chen J, Rodopoulou S, Strak M, de Hoogh K, Poulsen AH, Andersen ZJ, Bellander T, Brandt J, Zitt E, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann B, Hvidtfeldt UA, Jørgensen JT, Katsouyanni K, Ketzel M, Lager A, Leander K, Liu S, Ljungman P, Severi G, Besson C, Magnusson PKE, Nagel G, Pershagen G, Peters A, Rizzuto D, Samoli E, Sørensen M, Stafoggia M, Tjønneland A, Weinmayr G, Wolf K, Brunekreef B, Hoek G, Raaschou-Nielsen O. Long-term exposure to ambient air pollution and risk of leukemia and lymphoma in a pooled European cohort. Environ Pollut 2024; 343:123097. [PMID: 38065336 DOI: 10.1016/j.envpol.2023.123097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/08/2023] [Accepted: 12/02/2023] [Indexed: 12/19/2023]
Abstract
Leukemia and lymphoma are the two most common forms of hematologic malignancy, and their etiology is largely unknown. Pathophysiological mechanisms suggest a possible association with air pollution, but little empirical evidence is available. We aimed to investigate the association between long-term residential exposure to outdoor air pollution and risk of leukemia and lymphoma. We pooled data from four cohorts from three European countries as part of the "Effects of Low-level Air Pollution: a Study in Europe" (ELAPSE) collaboration. We used Europe-wide land use regression models to assess annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) at residences. We also estimated concentrations of PM2.5 elemental components: copper (Cu), iron (Fe), zinc (Zn); sulfur (S); nickel (Ni), vanadium (V), silicon (Si) and potassium (K). We applied Cox proportional hazards models to investigate the associations. Among the study population of 247,436 individuals, 760 leukemia and 1122 lymphoma cases were diagnosed during 4,656,140 person-years of follow-up. The results showed a leukemia hazard ratio (HR) of 1.13 (95% confidence intervals [CI]: 1.01-1.26) per 10 μg/m3 NO2, which was robust in two-pollutant models and consistent across the four cohorts and according to smoking status. Sex-specific analyses suggested that this association was confined to the male population. Further, the results showed increased lymphoma HRs for PM2.5 (HR = 1.16; 95% CI: 1.02-1.34) and potassium content of PM2.5, which were consistent in two-pollutant models and according to sex. Our results suggest that air pollution at the residence may be associated with adult leukemia and lymphoma.
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Affiliation(s)
- Tahir Taj
- Danish Cancer Institute, Strandboulevarden 49, 2100, Copenhagen, Denmark.
| | - Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.
| | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
| | - Maciej Strak
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.
| | | | - Zorana J Andersen
- Section of Environment and Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | - Tom Bellander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden.
| | - Jørgen Brandt
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark.
| | - Emanuel Zitt
- Agency for Preventive and Social Medicine (aks), Bregenz, Austria; Department of Internal Medicine 3, LKH Feldkirch, Feldkirch, Austria.
| | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
| | - Francesco Forastiere
- Department of Epidemiology, Lazio Region Health Service, ASL Roma 1, Rome, Italy; Environmental Research Group, School of Public Health, Faculty of Medicine, Imperial College, London, United Kingdom.
| | - John Gulliver
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, United Kingdom.
| | - Ole Hertel
- Department of Ecoscience, Aarhus University, Roskilde, Denmark.
| | - Barbara Hoffmann
- Institute for Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty, Heinrich Heine University Düsseldorf, Germany.
| | | | - Jeanette T Jørgensen
- Section of Environment and Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.
| | - Matthias Ketzel
- Department of Environmental Science, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark; Global Centre for Clean Air Research (GCARE), University of Surrey, Guildford GU2 7XH, United Kingdom.
| | - Anton Lager
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
| | - Karin Leander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Shuo Liu
- Section of Environment and Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | - Petter Ljungman
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Cardiology, Danderyd University Hospital, Stockholm, Sweden.
| | - Gianluca Severi
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" Team, CESP UMR1018, 94805, Villejuif, France; Department of Statistics, Computer Science, Applications "G. Parenti" (DISIA), University of Florence, Italy.
| | - Caroline Besson
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" Team, CESP UMR1018, 94805, Villejuif, France.
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany; Chair of Epidemiology, Ludwig Maximilians Universität München, Munich, Germany.
| | - Debora Rizzuto
- Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden.
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
| | - Mette Sørensen
- Danish Cancer Institute, Strandboulevarden 49, 2100, Copenhagen, Denmark; Department of Natural Science and Environment, Roskilde University, Roskilde, Denmark.
| | - Massimo Stafoggia
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology, Lazio Region Health Service, ASL Roma 1, Rome, Italy.
| | - Anne Tjønneland
- Danish Cancer Institute, Strandboulevarden 49, 2100, Copenhagen, Denmark.
| | - Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands.
| | - Ole Raaschou-Nielsen
- Danish Cancer Institute, Strandboulevarden 49, 2100, Copenhagen, Denmark; Department of Environmental Science, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark.
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25
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Herbolsheimer F, Peters A, Wagner S, Willich SN, Krist L, Pischon T, Nimptsch K, Gastell S, Brandes M, Brandes B, Schikowski T, Schmidt B, Michels KB, Mikolajczyk R, Harth V, Obi N, Castell S, Heise JK, Lieb W, Franzpötter K, Karch A, Teismann H, Völzke H, Meinke-Franze C, Leitzmann M, Stein MJ, Brenner H, Holleczek B, Weber A, Bohn B, Kluttig A, Steindorf K. Changes in physical activity and sedentary behavior during the first COVID-19 pandemic- restrictions in Germany: a nationwide survey : Running head: physical activity during the COVID-19 restrictions. BMC Public Health 2024; 24:433. [PMID: 38347566 PMCID: PMC10860251 DOI: 10.1186/s12889-024-17675-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/04/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic restrictions posed challenges to maintaining healthy lifestyles and physical well-being. During the first mobility restrictions from March to mid-July 2020, the German population was advised to stay home, except for work, exercise, and essential shopping. Our objective was to comprehensively assess the impact of these restrictions on changes in physical activity and sedentary behavior to identify the most affected groups. METHODS Between April 30, 2020, and May 12, 2020, we distributed a COVID-19-specific questionnaire to participants of the German National Cohort (NAKO). This questionnaire gathered information about participants' physical activity and sedentary behavior currently compared to the time before the restrictions. We integrated this new data with existing information on anxiety, depressive symptoms, and physical activity. The analyses focused on sociodemographic factors, social relationships, physical health, and working conditions. RESULTS Out of 152,421 respondents, a significant proportion reported altered physical activity and sedentary behavioral patterns due to COVID-19 restrictions. Over a third of the participants initially meeting the WHO's physical activity recommendation could no longer meet the guidelines during the restrictions. Participants reported substantial declines in sports activities (mean change (M) = -0.38; 95% CI: -.390; -.378; range from -2 to + 2) and reduced active transportation (M = -0.12; 95% CI: -.126; -.117). However, they also increased recreational physical activities (M = 0.12; 95% CI: .117; .126) while engaging in more sedentary behavior (M = 0.24; 95% CI: .240; .247) compared to pre-restriction levels. Multivariable linear and log-binomial regression models indicated that younger adults were more affected by the restrictions than older adults. The shift to remote work, self-rated health, and depressive symptoms were the factors most strongly associated with changes in all physical activity domains, including sedentary behavior, and the likelihood to continue following the physical activity guidelines. CONCLUSIONS Mobility patterns shifted towards inactivity or low-intensity activities during the nationwide restrictions in the spring of 2020, potentially leading to considerable and lasting health risks.
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Affiliation(s)
- Florian Herbolsheimer
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Sarah Wagner
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Stefan N Willich
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Lilian Krist
- Institute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Sylvia Gastell
- German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, Germany
| | - Mirko Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Berit Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Tamara Schikowski
- IUF - Leibniz Research Institute for Environmental Medicine, Duesseldorf, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany
| | - Karin B Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics, and Informatics, Interdisciplinary Center for Health Sciences , Medical Faculty of the Martin-Luther University Halle-Wittenberg, Halle, Germany
| | - Volker Harth
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Centre Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Centre Hamburg-Eppendorf (UKE), Hamburg, Germany
| | | | - Jana K Heise
- Helmholtz Centre for Infection Research, Brunswick, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology, University of Kiel, Kiel, Germany
| | | | - André Karch
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Henning Teismann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Claudia Meinke-Franze
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | | | | | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | | | - Alexander Kluttig
- Institute for Medical Epidemiology, Biometrics, and Informatics, Interdisciplinary Center for Health Sciences , Medical Faculty of the Martin-Luther University Halle-Wittenberg, Halle, Germany
| | - Karen Steindorf
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Huber V, Breitner-Busch S, He C, Matthies-Wiesler F, Peters A, Schneider A. Heat-Related Mortality in the Extreme Summer of 2022. Dtsch Arztebl Int 2024; 121:79-85. [PMID: 38169332 PMCID: PMC11002439 DOI: 10.3238/arztebl.m2023.0254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/16/2023] [Accepted: 11/16/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Estimating the excess mortality attributable to heat is a central element of the documentation of the consequences of climate change for human health. Until now, estimates of heatrelated deaths in Germany by the Robert Koch Institute (RKI) have been based on weekly mortality records. METHODS Our study is the first to use higher resolution data-i.e. daily all-cause mortality linked to daily mean temperatures-from each of the German federal states to assess the heat-related mortality from 2000 to 2023 in Germany, employing quasi-Poisson models and multivariate meta-regression analyses. We focus our analysis on the extreme summer of 2022. RESULTS Our analysis yielded an estimate of 9100 (95% CI: [7300; 10 700]) heat-related deaths in Germany for the summer of 2022, whereas previous studies of the RKI estimated the number of heatrelated deaths at 4500 [2100; 7000]. When we set a higher temperature threshold in the definition of the heat risk, we arrived at a figure of 6900 [5500; 8100] heat-related deaths in 2022. In other summers that-similarly to 2022-were characterized by large fluctuations in daily mean temperatures, we also robustly estimated higher numbers of heat-related deaths than the RKI did. The exclusion of reported deaths due to COVID-19 had only a minor effect on our estimates. CONCLUSION Our findings suggest that previous studies based on weekly mortality data have underestimated the full extent of heat-related mortality in Germany, particularly in the extreme summer of 2022. The monitoring of heat-related mortality should be systematic and as comprehensive as possible if it is to enable the development of effective heat-health action plans.
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Affiliation(s)
- Veronika Huber
- Institute of Epidemiology, The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig-Maximilians-Universität (LMU), München, Germany
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Breitner-Busch
- Institute of Epidemiology, The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Medical Faculty, Ludwig-Maximilians-Universität (LMU), München, Germany
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
| | - Cheng He
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
| | - Franziska Matthies-Wiesler
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
- German Alliance on Climate Change and Health (KLUG e.V.), Berlin, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
- Munich Heart Alliance, German Center for Cardiovascular Health (DZHK e.V., partner-site Munich), München, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Center Munich – German Research Center for Environmental Health, Neuherberg, Germany
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27
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Luo H, Huemer MT, Petrera A, Hauck SM, Rathmann W, Herder C, Koenig W, Hoyer A, Peters A, Thorand B. Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study. Cardiovasc Diabetol 2024; 23:53. [PMID: 38310303 PMCID: PMC10838466 DOI: 10.1186/s12933-024-02143-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/22/2024] [Indexed: 02/05/2024] Open
Abstract
BACKGROUND Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. METHODS The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). RESULTS We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). CONCLUSIONS This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.
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Affiliation(s)
- Hong Luo
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstraße 1, D-85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Marie-Theres Huemer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstraße 1, D-85764, Neuherberg, Germany
| | - Agnese Petrera
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Stefanie M Hauck
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Universität, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Universität, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine Universität, Düsseldorf, Germany
| | - Wolfgang Koenig
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Annika Hoyer
- Biostatistics and Medical Biometry, Medical School OWL, Bielefeld University, Bielefeld, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstraße 1, D-85764, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstraße 1, D-85764, Neuherberg, Germany.
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany.
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, Neuherberg, Germany.
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Stoecklein VM, Grosu S, Nikolova T, Tonn JC, Zausinger S, Ricke J, Schlett CL, Maurer E, Walter SS, Peters A, Bamberg F, Rospleszcz S, Stoecklein S. Strong Association of Depression and Anxiety With the Presence of Back Pain While Impact of Spinal Imaging Findings is Limited: Analysis of an MRI Cohort Study. J Pain 2024; 25:497-507. [PMID: 37742905 DOI: 10.1016/j.jpain.2023.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 09/10/2023] [Accepted: 09/18/2023] [Indexed: 09/26/2023]
Abstract
Development of back pain is multifactorial, and it is not well understood which factors are the main drivers of the disease. We therefore applied a machine-learning approach to an existing large cohort study data set and sought to identify and rank the most important contributors to the presence of back pain amongst the documented parameters of the cohort. Data from 399 participants in the KORA-MRI (Cooperative health research in the region Augsburg-magnetic resonance imaging) (Cooperative Health Research in the Region Augsburg) study was analyzed. The data set included MRI images of the whole body, including the spine, metabolic, sociodemographic, anthropometric, and cardiovascular data. The presence of back pain was one of the documented items in this data set. Applying a machine-learning approach to this preexisting data set, we sought to identify the variables that were most strongly associated with back pain. Mediation analysis was performed to evaluate the underlying mechanisms of the identified associations. We found that depression and anxiety were the 2 most selected predictors for back pain in our model. Additionally, body mass index, spinal canal width and disc generation, medium and heavy physical work as well as cardiovascular factors were among the top 10 most selected predictors. Using mediation analysis, we found that the effects of anxiety and depression on the presence of back pain were mainly direct effects that were not mediated by spinal imaging. In summary, we found that psychological factors were the most important predictors of back pain in our cohort. This supports the notion that back pain should be treated in a personalized multidimensional framework. PERSPECTIVE: This article presents a wholistic approach to the problem of back pain. We found that depression and anxiety were the top predictors of back pain in our cohort. This strengthens the case for a multidimensional treatment approach to back pain, possibly with a special emphasis on psychological factors.
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Affiliation(s)
- Veit M Stoecklein
- Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Sergio Grosu
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Trayana Nikolova
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | | | - Stefan Zausinger
- Department of Neurosurgery, University Hospital, LMU Munich, Munich, Germany
| | - Jens Ricke
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Elke Maurer
- Department of Trauma and Reconstructive Surgery, BG Unfallklinik Tuebingen, Eberhard Karls University of Tuebingen, Tuebingen, Germany
| | - Sven S Walter
- Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Eberhard Karls University of Tuebingen, Tuebingen, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, LMU Munich, Munich, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany; German Center for Diabetes Research (DZD), Partner Site Neuherberg, Neuherberg, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, LMU Munich, Munich, Germany; German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Sophia Stoecklein
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
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29
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Schepp M, Freuer D, Peters A, Heier M, Teupser D, Meisinger C, Linseisen J. Is the Habitual Dietary Intake of Foods of Plant or Animal Origin Associated with Circulating Hemostatic Factors?-Results of the Population-Based KORA-Fit Study. Nutrients 2024; 16:432. [PMID: 38337715 PMCID: PMC10857183 DOI: 10.3390/nu16030432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 01/26/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024] Open
Abstract
Blood coagulation is a complex physiological process critical for maintaining hemostasis, and disruptions in this system can lead to various health complications. Since the effects of specific food groups on a series of circulating coagulation parameters in the population are not well established, this study examines such associations in the population-based KORA-Fit study. A total of 595 subjects (263 men and 332 women) born between 1945 and 1964 and living in the study region of Augsburg were included in the study. Habitual food intake was estimated based on a combination of repeated 24-h food lists (24HFLs) and a food frequency questionnaire (FFQ). Antithrombin III, D-dimers, factor VIII, fibrinogen, protein C, protein S, aPTT, Quick value and INR were measured in citrate plasma. Multivariable linear regression models were applied to investigate associations between the consumption of specific foods of plant or animal origin and hemostatic factors. We found that the consumption of plant-based food groups, including green leafy vegetables (rich in vitamin K1), were hardly associated with coagulation parameters. Surprisingly, a high consumption of dairy products and especially butter were associated with higher D-dimer concentrations. These findings need further evaluation in prospective studies.
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Affiliation(s)
- Michael Schepp
- Epidemiology, University Hospital Augsburg, University of Augsburg, 86156 Augsburg, Germany; (D.F.); (C.M.); (J.L.)
| | - Dennis Freuer
- Epidemiology, University Hospital Augsburg, University of Augsburg, 86156 Augsburg, Germany; (D.F.); (C.M.); (J.L.)
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (A.P.); (M.H.)
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, 81377 Munich, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health (GmbH), 85764 Neuherberg, Germany; (A.P.); (M.H.)
- KORA Study Centre, University Hospital Augsburg, 86156 Augsburg, Germany
| | - Daniel Teupser
- Institute of Laboratory Medicine, Medical Faculty, Ludwig-Maximilians-Universität München, 81377 Munich, Germany;
| | - Christine Meisinger
- Epidemiology, University Hospital Augsburg, University of Augsburg, 86156 Augsburg, Germany; (D.F.); (C.M.); (J.L.)
| | - Jakob Linseisen
- Epidemiology, University Hospital Augsburg, University of Augsburg, 86156 Augsburg, Germany; (D.F.); (C.M.); (J.L.)
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30
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Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, Galesloot TE, Babajide O, Andreasen L, Astrup A, Åsvold BO, Bandinelli S, Beekman M, Beilby JP, Bork-Jensen J, Boutin T, Brody JA, Brown SJ, Brumpton B, Campbell PJ, Cappola AR, Ceresini G, Chaker L, Chasman DI, Concas MP, Coutinho de Almeida R, Cross SM, Cucca F, Deary IJ, Kjaergaard AD, Echouffo Tcheugui JB, Ellervik C, Eriksson JG, Ferrucci L, Freudenberg J, Fuchsberger C, Gieger C, Giulianini F, Gögele M, Graham SE, Grarup N, Gunjača I, Hansen T, Harding BN, Harris SE, Haunsø S, Hayward C, Hui J, Ittermann T, Jukema JW, Kajantie E, Kanters JK, Kårhus LL, Kiemeney LALM, Kloppenburg M, Kühnel B, Lahti J, Langenberg C, Lapauw B, Leese G, Li S, Liewald DCM, Linneberg A, Lominchar JVT, Luan J, Martin NG, Matana A, Meima ME, Meitinger T, Meulenbelt I, Mitchell BD, Møllehave LT, Mora S, Naitza S, Nauck M, Netea-Maier RT, Noordam R, Nursyifa C, Okada Y, Onano S, Papadopoulou A, Palmer CNA, Pattaro C, Pedersen O, Peters A, Pietzner M, Polašek O, Pramstaller PP, Psaty BM, Punda A, Ray D, Redmond P, Richards JB, Ridker PM, Russ TC, Ryan KA, Olesen MS, Schultheiss UT, Selvin E, Siddiqui MK, Sidore C, Slagboom PE, Sørensen TIA, Soto-Pedre E, Spector TD, Spedicati B, Srinivasan S, Starr JM, Stott DJ, Tanaka T, Torlak V, Trompet S, Tuhkanen J, Uitterlinden AG, van den Akker EB, van den Eynde T, van der Klauw MM, van Heemst D, Verroken C, Visser WE, Vojinovic D, Völzke H, Waldenberger M, Walsh JP, Wareham NJ, Weiss S, Willer CJ, Wilson SG, Wolffenbuttel BHR, Wouters HJCM, Wright MJ, Yang Q, Zemunik T, Zhou W, Zhu G, Zöllner S, Smit JWA, Peeters RP, Köttgen A, Teumer A, Medici M. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications. Nat Commun 2024; 15:888. [PMID: 38291025 PMCID: PMC10828500 DOI: 10.1038/s41467-024-44701-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024] Open
Abstract
To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases.
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Affiliation(s)
- Rosalie B T M Sterenborg
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Inga Steinbrenner
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Yong Li
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | | | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
- Digital Environment Research Institute, Queen Mary University of London, London, UK
| | - Tessel E Galesloot
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Oladapo Babajide
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Laura Andreasen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arne Astrup
- Department of Obesity and Nutritional Sciences, The Novo Nordisk Foundation, Hellerup, Denmark
| | - Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Marian Beekman
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - John P Beilby
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Suzanne J Brown
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, 7600, Norway
| | - Purdey J Campbell
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, University of Pennsylvania, Philadelphia, PA, USA
| | - Graziano Ceresini
- Oncological Endocrinology, University of Parma, Parma, Italy
- Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Layal Chaker
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
| | - Rodrigo Coutinho de Almeida
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Simone M Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
- Università di Sassari, Dipartimento di Scienze Biomediche, V.le San Pietro, 07100, Sassari (SS), Italy
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Alisa Devedzic Kjaergaard
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Palle Juul-Jensens Blvd. 11, Entrance A, 8200, Aarhus, Denmark
| | - Justin B Echouffo Tcheugui
- Division of Endocrinology, Diabetes, and Metabolism, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Christina Ellervik
- Harvard Medical School, Boston, USA
- Faculty of Medical Science, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Laboratory Medicine, Boston Children's Hospital, Boston, MA, USA
- Department of Clinical Biochemistry, Zealand University Hospital, Køge, Denmark
| | - Johan G Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland
- National University Singapore, Yong Loo Lin School of Medicine, Department of Obstetrics and Gynecology, Singapore, Singapore
| | - Luigi Ferrucci
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | | | - Christian Fuchsberger
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
| | - Martin Gögele
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Sarah E Graham
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivana Gunjača
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Barbara N Harding
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Barcelona Institute for Global Health, Barcelona, Spain
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Stig Haunsø
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, United Kingdom
| | - Jennie Hui
- Pathwest Laboratory Medicine WA, Nedlands, WA, 6009, Australia
- School of Population and Global Health, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Eero Kajantie
- Finnish Institute for Health and Welfare, Population Health Unit, Helsinki and Oulu, Oulu, Finland
- Clinical Medicine Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jørgen K Kanters
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
| | - Line L Kårhus
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Lambertus A L M Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Margreet Kloppenburg
- Departments of Rheumatology and Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brigitte Kühnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Bruno Lapauw
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | | | - Shuo Li
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - David C M Liewald
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - Allan Linneberg
- Center of Physiological Research, University of California San Francisco, San Francisco, USA
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jesus V T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | | | - Antonela Matana
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
| | - Marcel E Meima
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Thomas Meitinger
- Institute for Human Genetics, Technical University of Munich, Munich, Germany
| | - Ingrid Meulenbelt
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Braxton D Mitchell
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, 21201, USA
| | - Line T Møllehave
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
| | - Samia Mora
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Romana T Netea-Maier
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Casia Nursyifa
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan
| | - Stefano Onano
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - Areti Papadopoulou
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Colin N A Palmer
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Herlev-Gentofte University Hospital, Copenhagen, Denmark
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Maik Pietzner
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ozren Polašek
- Department of Public Health, University of Split, School of Medicine, Split, Croatia
- Algebra University College, Zagreb, Croatia
| | - Peter P Pramstaller
- Institute for Biomedicine (affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ante Punda
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Debashree Ray
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
| | - J Brent Richards
- Lady Davis Institute, Jewish General Hospital, Montreal, Quebec, H3T 1E2, Canada
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, USA
- Harvard Medical School, Boston, USA
| | - Tom C Russ
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathleen A Ryan
- University of Maryland School of Medicine, Division of Endocrinology, Diabetes and Nutrition, Baltimore, USA
| | - Morten Salling Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Moneeza K Siddiqui
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Carlo Sidore
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, 09042, Monserrato (CA), Italy
| | - P Eline Slagboom
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Enrique Soto-Pedre
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - Tim D Spector
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Beatrice Spedicati
- Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Sundararajan Srinivasan
- Division of Population Health Genomics, School of Medicine, University of Dundee, DD19SY, Dundee, UK
| | - John M Starr
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Toshiko Tanaka
- Longitudinal Study Section, National Institute on Aging, Baltimore, MD, USA
| | - Vesela Torlak
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Johanna Tuhkanen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Erik B van den Akker
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, The Netherlands
| | - Tibbert van den Eynde
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Melanie M van der Klauw
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Charlotte Verroken
- Department of Endocrinology, Ghent University Hospital, C. Heymanslaan 10, 9000, Ghent, Belgium
| | - W Edward Visser
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Dina Vojinovic
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- Medical School, The University of Western Australia, Crawley, WA, 6009, Australia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Stefan Weiss
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Cristen J Willer
- Department of Internal Medicine, Cardiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Scott G Wilson
- School of Biomedical Sciences, The University of Western Australia, Perth, WA, 6009, Australia
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia
- The Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Campus, Lambeth Palace Road, London, SE1 7EH, UK
| | - Bruce H R Wolffenbuttel
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hanneke J C M Wouters
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Tatijana Zemunik
- Department of Medical Biology, University of Split, School of Medicine, Split, Croatia
- Department of Nuclear Medicine, University Hospital Split, Split, Croatia
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Gu Zhu
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Johannes W A Smit
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Robin P Peeters
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
- CIBSS - Centre for Integrative Biological Signalling Studies, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany.
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
| | - Marco Medici
- Department of Internal Medicine, Division of Endocrinology, Radboud University Medical Center, Nijmegen, The Netherlands.
- Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
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Arnold M, Buyukozkan M, Doraiswamy PM, Nho K, Wu T, Gudnason V, Launer LJ, Wang-Sattler R, Adamski J, De Jager PL, Ertekin-Taner N, Bennett DA, Saykin AJ, Peters A, Suhre K, Kaddurah-Daouk R, Kastenmüller G, Krumsiek J. Individual bioenergetic capacity as a potential source of resilience to Alzheimer's disease. medRxiv 2024:2024.01.23.23297820. [PMID: 38313266 PMCID: PMC10836119 DOI: 10.1101/2024.01.23.23297820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Impaired glucose uptake in the brain is one of the earliest presymptomatic manifestations of Alzheimer's disease (AD). The absence of symptoms for extended periods of time suggests that compensatory metabolic mechanisms can provide resilience. Here, we introduce the concept of a systemic 'bioenergetic capacity' as the innate ability to maintain energy homeostasis under pathological conditions, potentially serving as such a compensatory mechanism. We argue that fasting blood acylcarnitine profiles provide an approximate peripheral measure for this capacity that mirrors bioenergetic dysregulation in the brain. Using unsupervised subgroup identification, we show that fasting serum acylcarnitine profiles of participants from the AD Neuroimaging Initiative yields bioenergetically distinct subgroups with significant differences in AD biomarker profiles and cognitive function. To assess the potential clinical relevance of this finding, we examined factors that may offer diagnostic and therapeutic opportunities. First, we identified a genotype affecting the bioenergetic capacity which was linked to succinylcarnitine metabolism and significantly modulated the rate of future cognitive decline. Second, a potentially modifiable influence of beta-oxidation efficiency seemed to decelerate bioenergetic aging and disease progression. Our findings, which are supported by data from more than 9,000 individuals, suggest that interventions tailored to enhance energetic health and to slow bioenergetic aging could mitigate the risk of symptomatic AD, especially in individuals with specific mitochondrial genotypes.
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Affiliation(s)
- Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Mustafa Buyukozkan
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - P. Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tong Wu
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | | | | | - Philip L. De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Taub Institute, Columbia University Irving Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | | | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; IBE, Medical Faculty, Ludwig-Maximilians-Universität, Munich, Germany; German Center for Diabetes Research (DZD e.V.), Munich, Germany; German Center for Cardiovascular Disease (DZHK e.V.), Munich Heart Alliance, Munich, Germany
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Education City, Doha, Qatar
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Duke University, Durham, NC, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jan Krumsiek
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
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Schmitz T, Harmel E, Raake P P, Freuer D, Kirchberger I, Heier M, Peters A, Linseisen J, Meisinger C. Association between acute myocardial infarction symptoms and short- and long-term mortality after the event. Can J Cardiol 2024:S0828-282X(24)00067-9. [PMID: 38278322 DOI: 10.1016/j.cjca.2024.01.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 01/03/2024] [Accepted: 01/15/2024] [Indexed: 01/28/2024] Open
Abstract
BACKGROUND In this study we investigated the associations between various acute myocardial infarction (AMI) symptoms and their associations with short-term (28 day) - and long-term mortality. METHODS The analysis was based on 5,900 patients aged 25 to 84 years with a first-time AMI recorded by the population-based Myocardial Infarction Registry Augsburg between 2010 and 2017. Median follow-up time was 3.8 years [IQR: 1.1-6.3]. As part of a face-to-face interview, the presence (yes/no) of 11 most commonly AMI symptoms at the acute event was assessed. Using multivariable-adjusted logistic regression and COX regression models the association between various symptoms and all-cause mortality was investigated. P values of the regression models were FDR-adjusted. RESULTS Pain in various body parts (chest pain, left and right shoulder/arm/hand, between shoulder blades), sweating, nausea/vomiting, dizziness and fear of death/feeling of annihilation were significantly associated with a decreased 28-day mortality after AMI. The pain symptoms and sweating were also significantly associated with a decreased long-term mortality. Shortness of breath was significantly associated with a higher long-term mortality. CONCLUSIONS The absence of several symptoms, including typical chest discomfort (chest pain or retrosternal pressure/tightness), is associated with unfavorable outcomes after AMI. This finding has implications for patient management and public health measures designed to encourage appropriate and prompt medical consultation of patients with atypical AMI symptoms.
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Affiliation(s)
- Timo Schmitz
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany.
| | - Eva Harmel
- University Hospital Augsburg, Department of Cardiology, Respiratory Medicine and Intensive Care, Augsburg, Germany
| | - Philip Raake P
- University Hospital Augsburg, Department of Cardiology, Respiratory Medicine and Intensive Care, Augsburg, Germany
| | - Dennis Freuer
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Inge Kirchberger
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Margit Heier
- University Hospital of Augsburg, KORA Study Centre, Augsburg, Germany; Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany
| | - Annette Peters
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany; Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich Germany; German Center for Diabetes Research (DZD) Neuherberg Germany
| | - Jakob Linseisen
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Christa Meisinger
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
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33
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Arnold N, Blaum C, Goßling A, Brunner FJ, Bay B, Ferrario MM, Brambilla P, Cesana G, Leoni V, Palmieri L, Donfrancesco C, Padró T, Andersson J, Jousilahti P, Ojeda F, Zeller T, Linneberg A, Söderberg S, Iacoviello L, Gianfagna F, Sans S, Veronesi G, Thorand B, Peters A, Tunstall-Pedoe H, Kee F, Salomaa V, Schnabel RB, Kuulasmaa K, Blankenberg S, Koenig W, Waldeyer C. C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project. Eur Heart J 2024:ehad867. [PMID: 38240386 DOI: 10.1093/eurheartj/ehad867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 11/20/2023] [Accepted: 12/06/2023] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND AND AIMS Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population. METHODS Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L). RESULTS Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024). CONCLUSIONS While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.
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Affiliation(s)
- Natalie Arnold
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christopher Blaum
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alina Goßling
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fabian J Brunner
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Benjamin Bay
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marco M Ferrario
- Research Center in Epidemiology and Preventive Medicine-EPIMED, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Paolo Brambilla
- Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
| | - Giancarlo Cesana
- Department of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy
| | - Valerio Leoni
- Laboratory of Clinical Pathology, Hospital Pio XI of Desio, ASST Brianza, School of Medicine and Surgery, University of Milano Bicocca, Milan, Italy
| | - Luigi Palmieri
- Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore di Sanità-ISS, Rome, Italy
| | - Chiara Donfrancesco
- Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore di Sanità-ISS, Rome, Italy
| | - Teresa Padró
- Cardiovascular-Program ICCC, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Centro de Investigación Biomédica en Red Cardiovascular (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Jonas Andersson
- Department of Public Health and Clinical Medicine, Skellefteå Research Unit, Umeå University, Skellefteå, Sweden
| | - Pekka Jousilahti
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Francisco Ojeda
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tanja Zeller
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- University Center of Cardiovascular Science, University Heart and Vascular Center Hamburg, Hamburg, Germany
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stefan Söderberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Licia Iacoviello
- Research Center in Epidemiology and Preventive Medicine-EPIMED, Department of Medicine and Surgery, University of Insubria, Varese, Italy
- Department of Epidemiology and Prevention, IRCCS Neuromed, Pozzilli, Italy
| | - Francesco Gianfagna
- Research Center in Epidemiology and Preventive Medicine-EPIMED, Department of Medicine and Surgery, University of Insubria, Varese, Italy
- Mediterranea Cardiocentro, Naples, Italy
| | - Susana Sans
- Catalan Department of Health, Barcelona, Spain
| | - Giovanni Veronesi
- Research Center in Epidemiology and Preventive Medicine-EPIMED, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology-IBE, Ludwig-Maximilians University of Munich, Munich, Germany
- German Center for Cardiovascular Disease Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Hugh Tunstall-Pedoe
- Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, Dundee, Scotland
| | - Frank Kee
- Centre for Public Health, Queens University of Belfast, Belfast, Northern Ireland, UK
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Renate B Schnabel
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kari Kuulasmaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Stefan Blankenberg
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Wolfgang Koenig
- German Center for Cardiovascular Disease Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
- German Heart Center, Munich, Technical University of Munich, Lazarettstr. 36, Munich 80636, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Christoph Waldeyer
- Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Hamburg/Kiel/Luebeck, Hamburg, Germany
- Center for Population Health Innovation (POINT), University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Schmitz T, Wein B, Raake P, Heier M, Peters A, Linseisen J, Meisinger C. Do patients with diabetes with new onset acute myocardial infarction present with different symptoms than non-diabetic patients? Front Cardiovasc Med 2024; 11:1324451. [PMID: 38287984 PMCID: PMC10822885 DOI: 10.3389/fcvm.2024.1324451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/03/2024] [Indexed: 01/31/2024] Open
Abstract
Background The objective of this study was to investigate the differences in presenting symptoms between patients with and without diabetes being diagnosed with an acute myocardial infarction (AMI). Methods A total of 5,900 patients with a first-time AMI were included into the analysis. All patients aged between 25 and 84 years were recorded by the population-based Myocardial Infarction Registry in Augsburg, Germany, between 2010 and 2017. The presence (yes/no) of 12 AMI typical symptoms during the acute event was assessed within the scope of a face-to-face interview. Multivariable adjusted logistic regression models were calculated to analyze the associations between presenting symptoms and diabetes mellitus in AMI patients. Results Patients with diabetes had significantly less frequent typical pain symptoms, including typical chest pain. Also, other symptoms like sweating, vomiting/nausea, dizziness/vertigo and fear of death/feeling of annihilation occurred significantly more likely in non-diabetic patients. The only exception was the symptom of shortness of breath, which was found significantly more often in patients with diabetes. In multivariable-adjusted regression models, however, the observed effects were attenuated. In patients younger than 55 years, the associations between diabetes and various symptoms were mainly missing. Conclusions Type 2 diabetes mellitus is a risk factor not only for the development of AMI, but is also associated with an adverse outcome after AMI. Atypical clinical presentation additionally complicates the diagnostic process. It is therefore essential for physicians to be aware of the more often atypical symptoms that diabetic AMI patients report.
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Affiliation(s)
- Timo Schmitz
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Bastian Wein
- Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany
| | - Philip Raake
- Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany
| | - Margit Heier
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Germany
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany
| | - Annette Peters
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research (DZD) Neuherberg, Neuherberg, Germany
| | - Jakob Linseisen
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Christa Meisinger
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
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Fokkens WJ, De Corso E, Backer V, Bernal-Sprekelsen M, Bjermer L, von Buchwald C, Chaker A, Diamant Z, Gevaert P, Han J, Hopkins C, Hox V, Klimek L, Lund VJ, Lee S, Luong A, Mullol J, Peters A, Pfaar O, Reitsma S, Toppila-Salmi S, Scadding GK, Sedaghat AR, Viskens AS, Wagenmann M, Hellings PW. EPOS2020/EUFOREA expert opinion on defining disease states and therapeutic goals in CRSwNP. Rhinology 2024; 0:3150. [PMID: 38217529 DOI: 10.4193/rhin23.415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Abstract
Severe chronic rhinosinusitis with nasal polyps (CRSwNP), a form of diffuse bilateral (usually type 2) CRS, is a debilitating disease with a significant impact on quality of life (QoL). With novel knowledge and treatment options becoming available, there is a growing need to update or revise key definitions to enable communication across different specialties dealing with CRS, and to agree on novel goals of care in CRSwNP. The European Forum for Research and Education in Allergy and Airway diseases (EUFOREA) and EPOS expert members discussed how to measure treatment responses and set new treatment goals for CRSwNP. In this paper a consensus on a list of definitions related to CRSwNP is provided: control, remission, cure, recurrence/exacerbation, treatable traits, remodeling, progression, and disease modification. By providing these definitions, the involved experts hope to improve communication between all stakeholders involved in CRSwNP treatment for use in routine care, basic and clinical research and international guidelines aimed to harmonize and optimize standard of care of patients with CRSwNP in the future.
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Affiliation(s)
- W J Fokkens
- Department of Otorhinolarynogology and head/neck surgery, Amsterdam University Medical Centres, location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - E De Corso
- Otolaryngology, Head and Neck Surgery, Rhinology, A. Gemelli Universitary Hospital Foundation, IRCSS, Rome, Italy
| | - V Backer
- Department of Otorhinolaryngology, Head and Neck surgery and Audiology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
| | - M Bernal-Sprekelsen
- Department of Otorhinolaryngology, University of Barcelona, Department of Otorhinolaryngology, Clinic Barcelona, Spain
| | - L Bjermer
- Department of Respiratory Medicine and Allergology, Lund University, Skåne University Hospital, Lund, Sweden
| | - C von Buchwald
- Department of Otorhinolaryngology, Head and Neck surgery and Audiology, Rigshospitalet, Copenhagen University, Copenhagen, Denmark
| | - A Chaker
- Department of Otorhinolaryngology and Center for Allergy and Environment (ZAUM), TUM School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany
| | - Z Diamant
- Department of Otorhinolaryngology and Center for Allergy and Environment (ZAUM), TUM School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany
- Department of Microbiology Immunology and Transplantation, KU Leuven, Catholic University of Leuven, Leuven, Belgium
- Department of Clinical Pharmacy and Pharmacology, UMCG, Groningen, The Netherlands
- Department of Respiratory Medicine and Allergology, Institute for Clinical Science, Skåne University Hospital Lund, Sweden
- D
| | - P Gevaert
- Laboratory of Upper Airways Research, Department of Otorhinolaryngology, University Hospital Ghent, Ghent, Belgium
| | - J Han
- Department of Otolaryngology and Head and Neck Surgery at Eastern Virginia Medical School, Norfolk, VI, USA
| | - C Hopkins
- Ear, Nose and Throat Department, Guys and St. Thomas Hospital, London, United Kingdom
| | - V Hox
- Department of Otorhinolaryngology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - L Klimek
- Center for Rhinology and Allergology, Wiesbaden, Germany
| | - V J Lund
- Professorial Unit, Ear Institute, University College London, United Kingdom
| | - S Lee
- Division of Rhinology and Skull Base Surgery, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - A Luong
- Department of Otorhinolaryngology, Head and Neck Surgery, McGovern Medical School at the University of Texas Health Science Center, Houston, TX, USA
| | - J Mullol
- Rhinology Unit and Smell Clinic, ENT Department, Hospital Clínic, FRCB-IDIBAPS, Universitat de Barcelona, CIBERES. Barcelona, Catalonia, Spain
| | - A Peters
- Department of Otolaryngology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - O Pfaar
- Department of Otorhinolaryngology, Head and Neck Surgery, Section of Rhinology and Allergy, University Hospital Marburg, Philipps-Universität Marburg, Marburg, Germany
| | - S Reitsma
- Department of Otorhinolarynogology and head/neck surgery, Amsterdam University Medical Centres, location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - S Toppila-Salmi
- Department of Otorhinolaryngology - Head and Neck Surgery, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland
- Department of Allergy, Inflammation Center, Helsinki University Hospital and University of Helsinki , Finland
| | - G K Scadding
- Division of infection and Immunity, University College London, United Kingdom
| | - A R Sedaghat
- Department of Otolaryngology - Head and Neck Surgery, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - A-S Viskens
- Laboratory of Allergy and Clinical Immunology Research Unit, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium
| | - M Wagenmann
- Department of Otorhinolaryngology, Universitätsklinikum Düsseldorf, Dusseldorf, Germany
| | - P W Hellings
- Department of Otorhinolaryngology, Head and Neck Surgery, UZ Leuven, Leuven, Belgium
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Bauke F, Schmitz T, Harmel E, Raake P, Heier M, Linseisen J, Peters A, Meisinger C. Anterior-wall and non-anterior-wall STEMIs do not differ in long-term mortality: results from the augsburg myocardial infarction registry. Front Cardiovasc Med 2024; 10:1306272. [PMID: 38259315 PMCID: PMC10800510 DOI: 10.3389/fcvm.2023.1306272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Background Different ST-segment elevation myocardial infarction (STEMI) localizations go along with dissimilarities in the size of the affected myocardium, the causing coronary vessel occlusion, and the right ventricular participation. Therefore, this study aims to clarify if there is any difference in long-term survival between anterior- and non-anterior-wall STEMI. Methods This study included 2,195 incident STEMI cases that occurred between 2009 and 2017, recorded by the population-based Augsburg Myocardial Infarction Registry, Germany. The study population comprised 1.570 men and 625 women aged 25-84 years at acute myocardial infarction. The patients were observed from the day of their first acute event with an average follow-up period of 4.3 years, (standard deviation: 3.0). Survival analyses and multivariable Cox regression analyses were performed to examine the association between infarction localizations and long-term all-cause mortality. Results Of the 2,195 patients, 1,118 had an anterior (AWS)- and 1,077 a non-anterior-wall-STEMI (NAWS). No significant associations of the STEMI localization with long-term mortality were found. When comparing AWS with NAWS, a hazard ratio of 0.91 [95% confidence interval: 0.75-1.10] could be calculated after multivariable adjustment. In contrast to NAWS, AWS was associated with a greater <28 day mortality, less current or former smoking and higher creatine kinase-myocardial band levels (CK-MB) and went along with a higher frequency of impaired left ventricular ejection fraction (<30%). Conclusions Despite pathophysiological differences between AWS and NAWS, and identified differences in multiple clinical characteristics, no significant differences in long-term mortality between both groups were observed.
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Affiliation(s)
- F. Bauke
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
- Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany
| | - T. Schmitz
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - E. Harmel
- Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany
| | - P. Raake
- Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany
| | - M. Heier
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Germany
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany
| | - J. Linseisen
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - A. Peters
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute for Epidemiology, Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
- German Research Center for Cardiovascular Research (DZHK e.V.), Partner Site Munich Heart Alliance, Munich, Germany
| | - C. Meisinger
- Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany
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Hellbach F, Freuer D, Meisinger C, Peters A, Winkelmann J, Costeira R, Hauner H, Baumeister SE, Bell JT, Waldenberger M, Linseisen J. Usual dietary intake and change in DNA methylation over years: EWAS in KORA FF4 and KORA fit. Front Nutr 2024; 10:1295078. [PMID: 38249614 PMCID: PMC10799384 DOI: 10.3389/fnut.2023.1295078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/11/2023] [Indexed: 01/23/2024] Open
Abstract
Introduction Changes in DNA methylation can increase or suppress the expression of health-relevant genes. We investigated for the first time the relationship between habitual food consumption and changes in DNA methylation. Methods The German KORA FF4 and KORA Fit studies were used to study the change in methylation over a median follow-up of 4 years. Only subjects participating in both surveys and with available dietary and methylation data were included in the analysis (n = 465). DNA methylation was measured using the Infinium MethylationEPIC BeadChip (Illumina), resulting in 735,527 shared CpGs across both studies. Generalized estimating equation models with an interaction term of exposure and time point were used to analyze the association of 34 food groups, folic acid, and two dietary patterns with changes in DNA methylation over time. Results The results were corrected for genomic inflation. Significant interaction terms indicate different effects between both time points. We observed only a few significant associations between food intake and change in DNA methylation, except for cream and spirit consumption. The annotated genes include CLN3, PROM1, DLEU7, TLL2, and UGT1A10. Discussion We identified weak associations between food consumption and DNA methylation change. The differential results for cream and spirits, both consumed in low quantities, require replication in independent studies.
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Affiliation(s)
- Fabian Hellbach
- Department of Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
- Medical Faculty, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilian University Munich, Munich, Germany
| | - Dennis Freuer
- Department of Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
| | - Christa Meisinger
- Department of Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
| | - Annette Peters
- Medical Faculty, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilian University Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Technical University of Munich, Institute of Human Genetics, Klinikum Rechts der Isar, Munich, Germany
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Hans Hauner
- Else Kröner-Fresenius-Center for Nutritional Medicine, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
- School of Medicine, Institute of Nutritional Medicine, Technical University of Munich, Munich, Germany
| | - Sebastian-Edgar Baumeister
- Medical Faculty, Institute of Health Services Research in Dentistry, University of Münster, Münster, Germany
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Jakob Linseisen
- Department of Epidemiology, Faculty of Medicine, University of Augsburg, University Hospital Augsburg, Augsburg, Germany
- Medical Faculty, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilian University Munich, Munich, Germany
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Michel LJ, Rospleszcz S, Reisert M, Rau A, Nattenmueller J, Rathmann W, Schlett CL, Peters A, Bamberg F, Weiss J. Deep learning to estimate impaired glucose metabolism from Magnetic Resonance Imaging of the liver: An opportunistic population screening approach. PLOS Digit Health 2024; 3:e0000429. [PMID: 38227569 PMCID: PMC10791001 DOI: 10.1371/journal.pdig.0000429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 12/07/2023] [Indexed: 01/18/2024]
Abstract
AIM Diabetes is a global health challenge, and many individuals are undiagnosed and not aware of their increased risk of morbidity/mortality although dedicated tests are available, which indicates the need for novel population-wide screening approaches. Here, we developed a deep learning pipeline for opportunistic screening of impaired glucose metabolism using routine magnetic resonance imaging (MRI) of the liver and tested its prognostic value in a general population setting. METHODS In this retrospective study a fully automatic deep learning pipeline was developed to quantify liver shape features on routine MR imaging using data from a prospective population study. Subsequently, the association between liver shape features and impaired glucose metabolism was investigated in individuals with prediabetes, type 2 diabetes and healthy controls without prior cardiovascular diseases. K-medoids clustering (3 clusters) with a dissimilarity matrix based on Euclidean distance and ordinal regression was used to assess the association between liver shape features and glycaemic status. RESULTS The deep learning pipeline showed a high performance for liver shape analysis with a mean Dice score of 97.0±0.01. Out of 339 included individuals (mean age 56.3±9.1 years; males 58.1%), 79 (23.3%) and 46 (13.6%) were classified as having prediabetes and type 2 diabetes, respectively. Individuals in the high risk cluster using all liver shape features (n = 14) had a 2.4 fold increased risk of impaired glucose metabolism after adjustment for cardiometabolic risk factors (age, sex, BMI, total cholesterol, alcohol consumption, hypertension, smoking and hepatic steatosis; OR 2.44 [95% CI 1.12-5.38]; p = 0.03). Based on individual shape features, the strongest association was found between liver volume and impaired glucose metabolism after adjustment for the same risk factors (OR 1.97 [1.38-2.85]; p<0.001). CONCLUSIONS Deep learning can estimate impaired glucose metabolism on routine liver MRI independent of cardiometabolic risk factors and hepatic steatosis.
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Affiliation(s)
- Lea J. Michel
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
| | - Susanne Rospleszcz
- Department of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Germany
| | - Marco Reisert
- Medical Physics, Department of Radiology, Medical Center—University of Freiburg, Freiburg, Germany
| | - Alexander Rau
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
| | - Johanna Nattenmueller
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; German Center for Diabetes Research, München-Neuherberg, Germany
| | - Christopher. L. Schlett
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
| | - Annette Peters
- Department of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Germany
- German Center for Diabetes Research (DZD), partner site Neuherberg, Neuherberg, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
| | - Jakob Weiss
- Department of Diagnostic and Interventional Radiology, University Hospital Freiburg, Freiburg, Germany
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Kunz S, Wang X, Ferrari U, Drey M, Theodoropoulou M, Schilbach K, Reincke M, Heier M, Peters A, Koenig W, Zeller T, Thorand B, Bidlingmaier M. Age- and sex-adjusted reference intervals for steroid hormones measured by liquid chromatography-tandem mass spectrometry using a widely available kit. Endocr Connect 2024; 13:e230225. [PMID: 37938144 PMCID: PMC10762560 DOI: 10.1530/ec-23-0225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 11/08/2023] [Indexed: 11/09/2023]
Abstract
Objective Measurements utilizing commercially available sets of reagents for determination of steroid hormone profiles by liquid chromatography-tandem mass spectrometry (LC-MS/MS) have become increasingly important for routine laboratories. However, method-specific publications of reference intervals obtained from sufficiently large studies are often missing. Methods After validation of performance characteristics, a widely available kit for steroid analysis by LC-MS/MS was used to measure concentrations of 15 endogenous steroids (aldosterone, cortisol, cortisone, corticosterone, 11-deoxycortisol, 21-deoxycortisol, dehydroepiandrosterone sulfate, estradiol, testosterone, androstenedione, dihydrotestosterone, dehydroepiandrosterone, 17-hydroxyprogesterone, 11-deoxycorticosterone, progesterone) in more than 500 blood samples from a population-based study. While randomly selected from a larger cohort, the samples equally represented both sexes and covered a wide range of adult age groups. Age- and sex-specific reference intervals were calculated, and correlation with BMI was assessed. Results Performance characteristics of the assay matched expectations for 9 of 15 steroids. For most of them, reference intervals obtained from our study population were comparable to those reported by others, with age and sex being the major determinants. A sex-specific correlation with BMI was found for seven steroids. We identified limitations regarding sensitivity of the method for quantification of progesterone in males and postmenopausal females. Concentrations of aldosterone, 21-deoxycortisol, estradiol, 11-deoxycorticosterone, and dihydrotestosterone could not be quantified in a large percentage of samples. Conclusions The reference intervals for nine steroids will support meaningful interpretation for steroid profiles as measured by a widely used kit for LC-MS/MS-based quantification. Laboratories using such kits must be aware of potential limitations in sensitivity for some steroids included in the profile. Significance Statement Quantification of steroid hormones is a cornerstone for diagnosis of several diseases. Commonly used immunoassays have limitations in specificity. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a promising alternative, particularly if methods are harmonized across laboratories. The use of kits from commercial suppliers might support this. Clinical interpretation of steroid concentrations requires availability of appropriate reference intervals (RIs), but studies on RIs reported in the literature differ in preanalytical and analytical procedures. Here, we provide RIs for steroids measured by a widely available kit under preanalytical conditions mirroring common clinical practice. Such RIs might facilitate interpretation for those using the same method and comparable conditions in clinical routine.
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Affiliation(s)
- Sonja Kunz
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Xiao Wang
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Uta Ferrari
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Michael Drey
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Marily Theodoropoulou
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Katharina Schilbach
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Martin Reincke
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Augsburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), Partner site Munich Heart Alliance, Munich, Germany
- German Heart Centre Munich, Technical University of Munich, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Tanja Zeller
- Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Martin Bidlingmaier
- Department of Medicine IV, University Hospital, Ludwig Maximilian University Munich, Munich, Germany
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Wang M, Flexeder C, Harris CP, Thiering E, Koletzko S, Bauer CP, Schulte-Körne G, von Berg A, Berdel D, Heinrich J, Schulz H, Schikowski T, Peters A, Standl M. Accelerometry-assessed sleep clusters and cardiometabolic risk factors in adolescents. Obesity (Silver Spring) 2024; 32:200-213. [PMID: 37873587 DOI: 10.1002/oby.23918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/07/2023] [Accepted: 08/18/2023] [Indexed: 10/25/2023]
Abstract
OBJECTIVE This study aimed to identify sleep clusters based on objective multidimensional sleep characteristics and test their associations with adolescent cardiometabolic health. METHODS The authors included 1090 participants aged 14.3 to 16.4 years (mean = 15.2 years) who wore 7-day accelerometers during the 15-year follow-up of the German Infant Study on the influence of Nutrition Intervention PLUS environmental and genetic influences on allergy development (GINIplus) and the Influence of Lifestyle factors on the development of the Immune System and Allergies in East and West Germany (LISA) birth cohorts. K-means cluster analysis was performed across 12 sleep characteristics reflecting sleep quantity, quality, schedule, variability, and regularity. Cardiometabolic risk factors included fat mass index (FMI), blood pressure, triglycerides, high-density lipoprotein cholesterol, high-sensitivity C-reactive protein, and insulin resistance (n = 505). Linear and logistic regression models were examined. RESULTS Five sleep clusters were identified: good sleep (n = 337); delayed sleep phase (n = 244); sleep irregularity and variability (n = 108); fragmented sleep (n = 313); and prolonged sleep latency (n = 88). The "prolonged sleep latency" cluster was associated with increased sex-scaled FMI (β = 0.39, 95% CI: 0.15-0.62) compared with the "good sleep" cluster. The "sleep irregularity and variability" cluster was associated with increased odds of high triglycerides only in male individuals (odds ratio: 9.50, 95% CI: 3.22-28.07), but this finding was not confirmed in linear models. CONCLUSIONS The prolonged sleep latency cluster was associated with higher FMI in adolescents, whereas the sleep irregularity and variability cluster was specifically linked to elevated triglycerides (≥1.7 mmol/L) in male individuals.
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Affiliation(s)
- Mingming Wang
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany
| | - Claudia Flexeder
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Carla P Harris
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Pediatrics, Dr. von Hauner Children's Hospital, LMU University Hospitals, Munich, Germany
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Pediatrics, Dr. von Hauner Children's Hospital, LMU University Hospitals, Munich, Germany
| | - Sibylle Koletzko
- Department of Pediatrics, Dr. von Hauner Children's Hospital, LMU University Hospitals, Munich, Germany
- Department of Pediatrics, Gastroenterology and Nutrition, School of Medicine Collegium Medicum, University of Warmia and Mazury, Olsztyn, Poland
| | | | - Gerd Schulte-Körne
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Andrea von Berg
- Research Institute, Department of Pediatrics, Marien-Hospital Wesel, Wesel, Germany
| | - Dietrich Berdel
- Research Institute, Department of Pediatrics, Marien-Hospital Wesel, Wesel, Germany
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, Germany
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Holger Schulz
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Tamara Schikowski
- IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
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41
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Nogal A, Alkis T, Lee Y, Kifer D, Hu J, Murphy RA, Huang Z, Wang-Sattler R, Kastenmüler G, Linkohr B, Barrios C, Crespo M, Gieger C, Peters A, Price J, Rexrode KM, Yu B, Menni C. Predictive metabolites for incident myocardial infarction: a two-step meta-analysis of individual patient data from six cohorts comprising 7897 individuals from the COnsortium of METabolomics Studies. Cardiovasc Res 2023; 119:2743-2754. [PMID: 37706562 PMCID: PMC10757581 DOI: 10.1093/cvr/cvad147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/28/2023] [Accepted: 07/18/2023] [Indexed: 09/15/2023] Open
Abstract
AIMS Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. METHODS AND RESULTS We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26-1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67-0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. CONCLUSIONS In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings.
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Affiliation(s)
- Ana Nogal
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
| | - Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Yura Lee
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Jie Hu
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rachel A Murphy
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Zhe Huang
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gabi Kastenmüler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Clara Barrios
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Marta Crespo
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jackie Price
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Kathryn M Rexrode
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Cristina Menni
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
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42
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Yao Y, Schneider A, Wolf K, Zhang S, Wang-Sattler R, Prehn C, Adamski J, Peters A, Breitner S. Corrigendum to "Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study" [Sci. Total Environ. 900 (2023) 165780]. Sci Total Environ 2023; 905:167050. [PMID: 37734230 DOI: 10.1016/j.scitotenv.2023.167050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Affiliation(s)
- Yueli Yao
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Siqi Zhang
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Rui Wang-Sattler
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany; German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich, Munich, Germany
| | - Susanne Breitner
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
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43
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Schwedhelm C, Nimptsch K, Ahrens W, Hasselhorn HM, Jöckel KH, Katzke V, Kluttig A, Linkohr B, Mikolajczyk R, Nöthlings U, Perrar I, Peters A, Schmidt CO, Schmidt B, Schulze MB, Stang A, Zeeb H, Pischon T. Chronic disease outcome metadata from German observational studies - public availability and FAIR principles. Sci Data 2023; 10:868. [PMID: 38052810 PMCID: PMC10698176 DOI: 10.1038/s41597-023-02726-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 11/07/2023] [Indexed: 12/07/2023] Open
Abstract
Metadata from epidemiological studies, including chronic disease outcome metadata (CDOM), are important to be findable to allow interpretability and reusability. We propose a comprehensive metadata schema and used it to assess public availability and findability of CDOM from German population-based observational studies participating in the consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health). Additionally, principal investigators from the included studies completed a checklist evaluating consistency with FAIR principles (Findability, Accessibility, Interoperability, Reusability) within their studies. Overall, six of sixteen studies had complete publicly available CDOM. The most frequent CDOM source was scientific publications and the most frequently missing metadata were availability of codes of the International Classification of Diseases, Tenth Revision (ICD-10). Principal investigators' main perceived barriers for consistency with FAIR principles were limited human and financial resources. Our results reveal that CDOM from German population-based studies have incomplete availability and limited findability. There is a need to make CDOM publicly available in searchable platforms or metadata catalogues to improve their FAIRness, which requires human and financial resources.
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Affiliation(s)
- Carolina Schwedhelm
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, 13125, Germany.
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, 13125, Germany
| | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, 28359, Germany
- Institute of Statistics, Faculty of Mathematics and Computer Science, University of Bremen, Bremen, 28334, Germany
| | - Hans Martin Hasselhorn
- Department of Occupational Health Science, University of Wuppertal, Wuppertal, 42119, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, 45122, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Alexander Kluttig
- Institute of Medical Epidemiology, Biometrics, and Informatics, Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), 06112, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
| | - Rafael Mikolajczyk
- Institute of Medical Epidemiology, Biometrics, and Informatics, Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), 06112, Germany
- DZPG (German Center for Mental Health), partner site Halle-Jena-Magdeburg, 07743, Jena, Germany
| | - Ute Nöthlings
- Institute of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, 53115, Germany
| | - Ines Perrar
- Institute of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, 53115, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Department of Epidemiology, Medical Faculty of the Ludwig-Maximilians-Universität München, Munich, 81377, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, 17489, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, 45122, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam Rehbruecke, Nuthetal, 14558, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, 14558, Germany
| | - Andreas Stang
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, 45122, Germany
- Department of Epidemiology, School of Public Health, Boston University, Boston, MA, 02118, USA
| | - Hajo Zeeb
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, 28359, Germany
- Faculty 11 - Human and Health Sciences, University of Bremen, Bremen, 28359, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, 13125, Germany
- Biobank Technology Platform, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, 13125, Germany
- Core Facility Biobank, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, 13125, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, 10117, Germany
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Keshawarz A, Joehanes R, Ma J, Lee GY, Costeira R, Tsai PC, Masachs OM, Bell JT, Wilson R, Thorand B, Winkelmann J, Peters A, Linseisen J, Waldenberger M, Lehtimäki T, Mishra PP, Kähönen M, Raitakari O, Helminen M, Wang CA, Melton PE, Huang RC, Pennell CE, O’Sullivan TA, Ochoa-Rosales C, Voortman T, van Meurs JB, Young KL, Graff M, Wang Y, Kiel DP, Smith CE, Jacques PF, Levy D. Dietary and supplemental intake of vitamins C and E is associated with altered DNA methylation in an epigenome-wide association study meta-analysis. Epigenetics 2023; 18:2211361. [PMID: 37233989 PMCID: PMC10228397 DOI: 10.1080/15592294.2023.2211361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 04/28/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Dietary intake of antioxidants such as vitamins C and E protect against oxidative stress, and may also be associated with altered DNA methylation patterns. METHODS We meta-analysed epigenome-wide association study (EWAS) results from 11,866 participants across eight population-based cohorts to evaluate the association between self-reported dietary and supplemental intake of vitamins C and E with DNA methylation. EWAS were adjusted for age, sex, BMI, caloric intake, blood cell type proportion, smoking status, alcohol consumption, and technical covariates. Significant results of the meta-analysis were subsequently evaluated in gene set enrichment analysis (GSEA) and expression quantitative trait methylation (eQTM) analysis. RESULTS In meta-analysis, methylation at 4,656 CpG sites was significantly associated with vitamin C intake at FDR ≤ 0.05. The most significant CpG sites associated with vitamin C (at FDR ≤ 0.01) were enriched for pathways associated with systems development and cell signalling in GSEA, and were associated with downstream expression of genes enriched in the immune response in eQTM analysis. Furthermore, methylation at 160 CpG sites was significantly associated with vitamin E intake at FDR ≤ 0.05, but GSEA and eQTM analysis of the top most significant CpG sites associated with vitamin E did not identify significant enrichment of any biological pathways investigated. CONCLUSIONS We identified significant associations of many CpG sites with vitamin C and E intake, and our results suggest that vitamin C intake may be associated with systems development and the immune response.
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Affiliation(s)
| | - Roby Joehanes
- Framingham Heart Study, Framingham, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jiantao Ma
- Framingham Heart Study, Framingham, Framingham, MA, USA
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Gha Young Lee
- Framingham Heart Study, Framingham, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Olatz M. Masachs
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jordana T. Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, München, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Chair of Neurogenetics, School of Medicine, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, München, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Chair of Epidemiology, Medical Faculty, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), München Heart Alliance, Munich, Germany
| | - Jakob Linseisen
- Chair of Epidemiology, University Augsburg at University Hospital Augsburg, Augsburg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), München Heart Alliance, Munich, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Pashupati P. Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Helminen
- Tays Research Services, Tampere University Hospital, Tampere, Finland
- Faculty of Social Sciences, Health Sciences, Tampere University, Tampere, Finland
| | - Carol A. Wang
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, The University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Phillip E. Melton
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- School of Population and Global Health, University of Western Australia, Perth, Australia
| | - Rae-Chi Huang
- Nutrition & Health Innovation Research Institute, Edith Cowan University, Perth, Australia
| | - Craig E. Pennell
- Faculty of Social Sciences, Health Sciences, Tampere University, Tampere, Finland
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | | | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
- Centro de Vida Saludable, Universidad de Concepción, Concepción, Chile
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Joyce B.J. van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Kristin L. Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Hebrew Senior Life, Chapel Hill, North Carolina, USA
| | - Misa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Hebrew Senior Life, Chapel Hill, North Carolina, USA
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Hebrew Senior Life, Chapel Hill, North Carolina, USA
| | - Douglas P. Kiel
- Department of Medicine, Beth Israel Deaconess Medical Center, Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Caren E. Smith
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Paul F. Jacques
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, Framingham, MA, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
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Nikolaou N, Bouwer LM, Dallavalle M, Valizadeh M, Stafoggia M, Peters A, Wolf K, Schneider A. Improved daily estimates of relative humidity at high resolution across Germany: A random forest approach. Environ Res 2023; 238:117173. [PMID: 37734577 DOI: 10.1016/j.envres.2023.117173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 09/01/2023] [Accepted: 09/17/2023] [Indexed: 09/23/2023]
Abstract
The lack of readily available methods for estimating high-resolution near-surface relative humidity (RH) and the incapability of weather stations to fully capture the spatiotemporal variability can lead to exposure misclassification in studies of environmental epidemiology. We therefore aimed to predict German-wide 1 × 1 km daily mean RH during 2000-2021. RH observations, longitude and latitude, modelled air temperature, precipitation and wind speed as well as remote sensing information on topographic elevation, vegetation, and the true color band composite were incorporated in a Random Forest (RF) model, in addition to date for capturing the temporal variations of the response-explanatory variables relationship. The model achieved high accuracy (R2 = 0.83) and low errors (Root Mean Square Error (RMSE) of 5.07%, Mean Absolute Percentage Error (MAPE) of 5.19% and Mean Percentage Error (MPE) of - 0.53%), calculated via ten-fold cross-validation. A comparison of our RH predictions with measurements from a dense monitoring network in the city of Augsburg, South Germany confirmed the good performance (R2 ≥ 0.86, RMSE ≤ 5.45%, MAPE ≤ 5.59%, MPE ≤ 3.11%). The model displayed high German-wide RH (22y-average of 79.00%) and high spatial variability across the country, exceeding 12% on yearly averages. Our findings indicate that the proposed RF model is suitable for estimating RH for a whole country in high-resolution and provide a reliable RH dataset for epidemiological analyses and other environmental research purposes.
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Affiliation(s)
- Nikolaos Nikolaou
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany.
| | - Laurens M Bouwer
- Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Hamburg, Germany.
| | - Marco Dallavalle
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany.
| | - Mahyar Valizadeh
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service - ASL Roma 1, Rome, Italy.
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Pettenkofer School of Public Health, Munich, Germany.
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
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Nogal A, Tettamanzi F, Dong Q, Louca P, Visconti A, Christiansen C, Breuninger T, Linseisen J, Grallert H, Wawro N, Asnicar F, Wong K, Baleanu AF, Michelotti GA, Segata N, Falchi M, Peters A, Franks PW, Bagnardi V, Spector TD, Bell JT, Gieger C, Valdes AM, Menni C. A Fecal Metabolite Signature of Impaired Fasting Glucose: Results From Two Independent Population-Based Cohorts. Diabetes 2023; 72:1870-1880. [PMID: 37699401 PMCID: PMC10658071 DOI: 10.2337/db23-0170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 08/30/2023] [Indexed: 09/14/2023]
Abstract
Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We searched for fecal metabolites, a readout of gut microbiome function, associated with impaired fasting glucose (IFG) in 142 individuals with IFG and 1,105 healthy individuals from the UK Adult Twin Registry (TwinsUK). We used the Cooperative Health Research in the Region of Augsburg (KORA) cohort (318 IFG individuals, 689 healthy individuals) to replicate our findings. We linearly combined eight IFG-positively associated metabolites (1-methylxantine, nicotinate, glucuronate, uridine, cholesterol, serine, caffeine, and protoporphyrin IX) into an IFG-metabolite score, which was significantly associated with higher odds ratios (ORs) for IFG (TwinsUK: OR 3.9 [95% CI 3.02-5.02], P < 0.0001, KORA: OR 1.3 [95% CI 1.16-1.52], P < 0.0001) and incident type 2 diabetes (T2D; TwinsUK: hazard ratio 4 [95% CI 1.97-8], P = 0.0002). Although these are host-produced metabolites, we found that the gut microbiome is strongly associated with their fecal levels (area under the curve >70%). Abundances of Faecalibacillus intestinalis, Dorea formicigenerans, Ruminococcus torques, and Dorea sp. AF24-7LB were positively associated with IFG, and such associations were partially mediated by 1-methylxanthine and nicotinate (variance accounted for mean 14.4% [SD 5.1], P < 0.05). Our results suggest that the gut microbiome is linked to prediabetes not only via the production of microbial metabolites but also by affecting intestinal absorption/excretion of host-produced metabolites and xenobiotics, which are correlated with the risk of IFG. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes and T2D onset. ARTICLE HIGHLIGHTS Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We investigated whether there is a fecal metabolite signature of impaired fasting glucose (IFG) and the possible underlying mechanisms of action. We identified a fecal metabolite signature of IFG associated with prevalent IFG in two independent cohorts and incident type 2 diabetes in a subanalysis. Although the signature consists of metabolites of nonmicrobial origin, it is strongly correlated with gut microbiome composition. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes by affecting intestinal absorption or excretion of host compounds and xenobiotics.
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Affiliation(s)
- Ana Nogal
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Francesca Tettamanzi
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
- Humanitas Clinical and Research Centre, IRCCS, Rozzano (Milan), Italy
| | - Qiuling Dong
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Panayiotis Louca
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Alessia Visconti
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Colette Christiansen
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
- School of Mathematics and Statistics, The Open University, Milton Keynes, U.K
| | - Taylor Breuninger
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
| | - Jakob Linseisen
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
- ZIEL-Institute for Food & Health, Technische Universität München, Freising, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Medical Faculty, Ludwig-Maximilian University Munich, Munich, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Nina Wawro
- Epidemiology, University Hospital Augsburg, University of Augsburg, Augsburg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Francesco Asnicar
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | | | - Andrei-Florin Baleanu
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | | | - Nicola Segata
- Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy
| | - Mario Falchi
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Annette Peters
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Munich Heart Alliance, German Center for Cardiovascular Research (DZHK e.V., Partner-Site Munich), Munich, Germany
| | - Paul W. Franks
- Lund University Diabetes Center, Lund University, Malmö, Sweden
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Vincenzo Bagnardi
- Department of Statistics and Quantitative Methods, University of Milan-Bicocca, Milan, Italy
| | - Tim D. Spector
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Jordana T. Bell
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, Research Unit of Molecular Epidemiology, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Ana M. Valdes
- Academic Rheumatology Clinical Sciences Building, Nottingham City Hospital, University of Nottingham, U.K
| | - Cristina Menni
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, London, U.K
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Kheirkhah A, Schachtl-Riess JF, Lamina C, Di Maio S, Koller A, Schönherr S, Coassin S, Forer L, Sekula P, Gieger C, Peters A, Köttgen A, Eckardt KU, Kronenberg F. Meta-GWAS on PCSK9 concentrations reveals associations of novel loci outside the PCSK9 locus in White populations. Atherosclerosis 2023; 386:117384. [PMID: 37989062 DOI: 10.1016/j.atherosclerosis.2023.117384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/23/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023]
Abstract
BACKGROUND AND AIMS Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations. METHODS We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis. RESULTS Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD. CONCLUSIONS We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected.
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Affiliation(s)
- Azin Kheirkhah
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Claudia Lamina
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Silvia Di Maio
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Adriana Koller
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Stefan Coassin
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Peggy Sekula
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Christian Gieger
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Kai-Uwe Eckardt
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; German Chronic Kidney Disease Study, Germany; Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
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Hecker K, Banszerus L, Schäpers A, Möller S, Peters A, Icking E, Watanabe K, Taniguchi T, Volk C, Stampfer C. Coherent charge oscillations in a bilayer graphene double quantum dot. Nat Commun 2023; 14:7911. [PMID: 38036517 PMCID: PMC10689829 DOI: 10.1038/s41467-023-43541-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 11/13/2023] [Indexed: 12/02/2023] Open
Abstract
The coherent dynamics of a quantum mechanical two-level system passing through an anti-crossing of two energy levels can give rise to Landau-Zener-Stückelberg-Majorana (LZSM) interference. LZSM interference spectroscopy has proven to be a fruitful tool to investigate charge noise and charge decoherence in semiconductor quantum dots (QDs). Recently, bilayer graphene has developed as a promising platform to host highly tunable QDs potentially useful for hosting spin and valley qubits. So far, in this system no coherent oscillations have been observed and little is known about charge noise in this material. Here, we report coherent charge oscillations and [Formula: see text] charge decoherence times in a bilayer graphene double QD. The charge decoherence times are measured independently using LZSM interference and photon assisted tunneling. Both techniques yield [Formula: see text] average values in the range of 400-500 ps. The observation of charge coherence allows to study the origin and spectral distribution of charge noise in future experiments.
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Affiliation(s)
- K Hecker
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany.
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany.
| | - L Banszerus
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - A Schäpers
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
| | - S Möller
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - A Peters
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
| | - E Icking
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - K Watanabe
- Research Center for Functional Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba, 305-0044, Japan
| | - T Taniguchi
- International Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba, 305-0044, Japan
| | - C Volk
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - C Stampfer
- JARA-FIT and 2nd Institute of Physics, RWTH Aachen University, 52074, Aachen, Germany
- Peter Grünberg Institute (PGI-9), Forschungszentrum Jülich, 52425, Jülich, Germany
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49
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Hassenstein MJ, Pischon T, Karch A, Peters A, Kerrinnes T, Teismann H, Schneider A, Thierry S, Moreno Velásquez I, Janke J, Kemmling Y, Castell S. Seropositivity of Borrelia burgdorferi s.l. in Germany-an analysis across four German National Cohort (NAKO) study sites. Sci Rep 2023; 13:21087. [PMID: 38036551 PMCID: PMC10689756 DOI: 10.1038/s41598-023-47766-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 11/17/2023] [Indexed: 12/02/2023] Open
Abstract
Lyme borreliosis (LB) is caused by the transmission of Borrelia burgdorferi s.l. from ticks to humans. Climate affects tick abundance, and climate change is projected to promote shifts in abundance in Europe, potentially increasing human exposure. We analyzed serum samples collected between the years 2014-2019 from German National Cohort (NAKO) participants at four study sites (Augsburg, Berlin, Hanover, Münster) for immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies using an enzyme-linked immunosorbent assay (ELISA) and line blot immunoassay as confirmatory test for positive and equivocal ELISA samples. We reported crude and weighted seropositivity proportions for local estimates. We used mixed model analysis to investigate associated factors, such as age, sex, migration background, or animal contacts. We determined the serostatus of 14,207 participants. The weighted seropositivity proportions were 3.4% (IgG) and 0.4% (IgM) in Augsburg, 4.1% (IgG) and 0.6% (IgM) in northern Berlin, 3.0% (IgG) and 0.9% (IgM) in Hanover, and 2.7% (IgG) and 0.6% (IgM) in Münster. We found higher odds for IgG seropositivity with advancing age (p < 0.001), among males compared to females (p < 0.001) and reduced odds among participants with migration background compared to those without (p = 0.001). We did not find evidence for an association between serostatus and depression, children within the household, or animal contact, respectively. We found low seropositivity proportions and indications of differences across the study locations, although between-group comparisons did not yield significant results. Comparisons to earlier research are subject to important limitations; however, our results indicate no major increases in seropositivity over time. Nevertheless, monitoring of seropositivity remains critical in light of potential climate-related Borrelia exposure.
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Affiliation(s)
- Max J Hassenstein
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany
- PhD Programme "Epidemiology", Braunschweig-Hannover, Germany
| | - Tobias Pischon
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Core Facility Biobank, Berlin, Germany
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Berlin, Germany
| | - André Karch
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Tobias Kerrinnes
- Department of RNA-Biology of Bacterial Infections, Helmholtz Institute for RNA-Based Infection Research, Würzburg, Germany
| | - Henning Teismann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Sigrid Thierry
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- NAKO Studienzentrum, Klinik für Diagnostische und Interventionelle Radiologie und Neuroradiologie, Universitätsklinikum Augsburg, Augsburg, Germany
| | - Ilais Moreno Velásquez
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
| | - Jürgen Janke
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
| | - Yvonne Kemmling
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany
| | - Stefanie Castell
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany.
- TWINCORE, Centre for Experimental and Clinical Infection Research, a Joint Venture of the Hannover Medical School and Helmholtz Centre for Infection Research, 30625, Hannover, Germany.
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50
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Gadd DA, Hillary RF, McCartney DL, Zaghlool SB, Stevenson AJ, Cheng Y, Fawns-Ritchie C, Nangle C, Campbell A, Flaig R, Harris SE, Walker RM, Shi L, Tucker-Drob EM, Gieger C, Peters A, Waldenberger M, Graumann J, McRae AF, Deary IJ, Porteous DJ, Hayward C, Visscher PM, Cox SR, Evans KL, McIntosh AM, Suhre K, Marioni RE. Correction: Epigenetic scores for the circulating proteome as tools for disease prediction. eLife 2023; 12:e94481. [PMID: 37982710 PMCID: PMC10659577 DOI: 10.7554/elife.94481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023] Open
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