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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] [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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Jokisch M, Schramm S, Weimar C, Moebus S, Gronewold J, Dragano N, Jöckel KH. Fluctuation of depressive symptoms in cognitively unimpaired participants and the risk of mild cognitive impairment 5 years later: Results of the Heinz Nixdorf Recall study. Front Behav Neurosci 2022; 16:988621. [PMID: 36386784 PMCID: PMC9640513 DOI: 10.3389/fnbeh.2022.988621] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 09/14/2022] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Depression might be an independent risk factor for cognitive decline, a prodromal dementia symptom or a reaction to cognitive/functional impairment. OBJECTIVE To investigate the association between (1) depressive symptoms and (2) depressive symptom patterns over 13 years with incident mild cognitive impairment (MCI) 5 years later. MATERIALS AND METHODS We included 724/823 cognitively unimpaired men/women who participated in the population-based Heinz Nixdorf Recall study (t1: 2005-2008, ø62.9 years; t2: 2010-2015, ø68.1 years). Depressive symptoms were assessed in the study center and during six postal follow-ups using the short form of the Center for Epidemiologic Studies Depression Scale (CES-D). Relative risks (RR; 95% confidence intervals) for MCI at t2 (men/women: 71/76) were estimated for CES-D at t1 (linear and dichotomized at ≥17, cut-off for clinically relevant depressive symptoms) and CES-D fluctuations over 13 years (stable low, large fluctuations, stable high/stable around cut-off) using log-linear regression models with Poisson working likelihood adjusted for age, sex, education, diabetes mellitus, coronary heart disease, and stroke. RESULTS Fully adjusted risk for MCI at t2 (per CES-D point increase at t1) was elevated for the total cohort (1.053, 1.031-1.076), men (1.046, 1.012-1.081), and women (1.059, 1.029-1.090). Applying the dichotomized CES-D, risk for MCI was substantially increased for the total cohort [2.22 (1.38-3.58)] and in women [2.59 (1.46-4.58)]. Large CES-D fluctuations and stable high/stable around cut-off were associated with increased RR for MCI in the total cohort and in women compared to stable low symptoms. CONCLUSION Depressive symptoms predicted MCI in cognitively unimpaired participants of our population-based study. Adequate treatment of depression may therefore contribute to the maintenance of normal cognition and delay dementia onset.
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Affiliation(s)
- Martha Jokisch
- Department of Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Sara Schramm
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Christian Weimar
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- BDH-Klinik Elzach gGmbH, Elzach, Germany
| | - Susanne Moebus
- Institute for Urban Public Health, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Janine Gronewold
- Department of Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Nico Dragano
- Centre for Health and Society, Medical Faculty, Institute of Medical Sociology, University of Düsseldorf, Düsseldorf, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
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Lee PN, Coombs KJ. Systematic review with meta-analysis of the epidemiological evidence relating smoking to type 2 diabetes. World J Meta-Anal 2020; 8:119-152. [DOI: 10.13105/wjma.v8.i2.119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 04/02/2020] [Accepted: 04/20/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Evidence relating tobacco smoking to type 2 diabetes has accumulated rapidly in the last few years, rendering earlier reviews considerably incomplete.
AIM To review and meta-analyse evidence from prospective studies of the relationship between smoking and the onset of type 2 diabetes.
METHODS Prospective studies were selected if the population was free of type 2 diabetes at baseline and evidence was available relating smoking to onset of the disease. Papers were identified from previous reviews, searches on Medline and Embase and reference lists. Data were extracted on a range of study characteristics and relative risks (RRs) were extracted comparing current, ever or former smokers with never smokers, and current smokers with non-current smokers, as well as by amount currently smoked and duration of quitting. Fixed- and random-effects estimates summarized RRs for each index of smoking overall and by various subdivisions of the data: Sex; continent; publication year; method of diagnosis; nature of the baseline population (inclusion/exclusion of pre-diabetes); number of adjustment factors; cohort size; number of type 2 diabetes cases; age; length of follow-up; definition of smoking; and whether or not various factors were adjusted for. Tests of heterogeneity and publication bias were also conducted.
RESULTS The literature searches identified 157 relevant publications providing results from 145 studies. Fifty-three studies were conducted in Asia and 53 in Europe, with 32 in North America, and seven elsewhere. Twenty-four were in males, 10 in females and the rest in both sexes. Fifteen diagnosed type 2 diabetes from self-report by the individuals, 79 on medical records, and 51 on both. Studies varied widely in size of the cohort, number of cases, length of follow-up, and age. Overall, random-effects estimates of the RR were 1.33 [95% confidence interval (CI): 1.28-1.38] for current vs never smoking, 1.28 (95%CI: 1.24-1.32) for current vs non-smoking, 1.13 (95%CI: 1.11-1.16) for former vs never smoking, and 1.25 (95%CI: 1.21-1.28) for ever vs never smoking based on, respectively, 99, 156, 100 and 100 individual risk estimates. Risk estimates were generally elevated in each subdivision of the data by the various factors considered (exceptions being where numbers of estimates in the subsets were very low), though there was significant (P < 0.05) evidence of variation by level for some factors. Dose-response analysis showed a clear trend of increasing risk with increasing amount smoked by current smokers and of decreasing risk with increasing time quit. There was limited evidence of publication bias.
CONCLUSION The analyses confirmed earlier reports of a modest dose-related association of current smoking and a weaker dose-related association of former smoking with type 2 diabetes risk.
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Affiliation(s)
- Peter N Lee
- Department of Statistics, P.N. Lee Statistics and Computing Ltd., Sutton SM2 5DA, Surrey, United Kingdom
| | - Katharine J Coombs
- Department of Statistics, P.N. Lee Statistics and Computing Ltd., Sutton SM2 5DA, Surrey, United Kingdom
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Indoor and outdoor road traffic noise and incident diabetes mellitus: Results from a longitudinal German cohort study. Environ Epidemiol 2019; 3:e037. [PMID: 33778334 PMCID: PMC7952109 DOI: 10.1097/ee9.0000000000000037] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 12/10/2018] [Indexed: 12/24/2022] Open
Abstract
Supplemental Digital Content is available in the text. Road traffic noise affects a large number of people in urbanized areas. Recent epidemiological evidence indicates that environmental noise exposure may not only be associated with cardiovascular but also with cardio-metabolic outcomes. This prospective cohort study investigated the effect of outdoor and indoor residential road traffic noise on incident type 2 diabetes mellitus (T2DM).
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Dong MX, Feng X, Xu XM, Hu L, Liu Y, Jia SY, Li B, Chen W, Wei YD. Integrated Analysis Reveals Altered Lipid and Glucose Metabolism and Identifies NOTCH2 as a Biomarker for Parkinson's Disease Related Depression. Front Mol Neurosci 2018; 11:257. [PMID: 30233306 PMCID: PMC6127515 DOI: 10.3389/fnmol.2018.00257] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 07/06/2018] [Indexed: 12/21/2022] Open
Abstract
Depression is a common comorbidity in Parkinson's disease (PD) but is underdiagnosed. We aim to investigate the altered metabolic pathways of Parkinson's disease-related depression (PDD) in plasma and to identify potential biomarkers for clinical diagnosis. Consecutive patients with PD were recruited, clinically assessed, and patients with PDD identified. Fasting plasma samples were collected from 99 patients and differentially expressed metabolites and proteins between patients with PDD and PD were identified using non-targeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and tandem mass tag (TMT)-based proteomics analysis, followed by an integrated analysis. Based on the above results, enzyme-linked immune sorbent assay (ELISA) tests were then performed to identify potential biomarkers for PDD. In clinics, patients with PDD suffered less hypertension and had lower serum low-density lipoprotein cholesterol and apolipoprotein B levels when compared to the other patients with PD. A total of 85 differentially expressed metabolites were identified in metabolomics analysis. These metabolites were mainly lipids and lipid-like molecules, involved in lipid and glucose metabolic pathways. According to proteomics analysis, 17 differentially expressed proteins were identified, and 12 metabolic pathways were enriched, which were predominantly related to glucose metabolism. Integrated analysis indicated that altered lipid and glucose metabolism in PDD may induce cellular injury through oxidative stress. Additionally, plasma levels of several proteins were confirmed to be significantly altered and correlated with depressive severity. NOTCH2 may be a potential blood biomarker for PDD, with an optimal cut-off point of 0.91 ng/ml, a sensitivity value of 95.65%, and a specificity value of 81.58%. Depressive symptoms are associated with lipid and glucose metabolism in patients with PD and NOTCH2 may be a potential blood biomarker for the clinical diagnosis of PDD.
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Affiliation(s)
- Mei-Xue Dong
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Neurology, Renmin Hospital of Wuhan University, Hubei General Hospital, Hubei, China
| | - Xia Feng
- Department of Neurology, The People's Hospital of Tongliang District, Chongqing, China
| | - Xiao-Min Xu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ling Hu
- Department of Neurology, The Fifth People's Hospital of Chongqing, Chongqing, China
| | - Yang Liu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Si-Yu Jia
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Bo Li
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wei Chen
- Shanghai Applied Protein Technology Co. Ltd., Shanghai, China
| | - You-Dong Wei
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Weimar C, Winkler A, Dlugaj M, Lehmann N, Hennig F, Bauer M, Kröger K, Kälsch H, Mahabadi AA, Dragano N, Moebus S, Hoffmann B, Jöckel KH, Erbel R. Ankle-Brachial Index but Neither Intima Media Thickness Nor Coronary Artery Calcification is Associated With Mild Cognitive Impairment. J Alzheimers Dis 2016; 47:433-42. [PMID: 26401565 DOI: 10.3233/jad-150218] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Several studies have reported an association of atherosclerosis with mild cognitive impairment (MCI) and dementia independent of cardiovascular risk factors. OBJECTIVE To compare the cross-sectional association of the ankle-brachial index (ABI), intima media thickness (IMT), and coronary artery calcification (CAC) with MCI and its subtypes, amnestic MCI (aMCI) and non-amnestic MCI (naMCI) in the population-based Heinz Nixdorf Recall cohort study. METHODS 4,086 participants performed a validated brief cognitive assessment at the first follow-up examination (2006-2008). MCI was diagnosed according to previously published criteria. Prevalence ratio (PR) regression models adjusted for age, gender, education, cardiovascular risk factors, and APOE genotype were used to compare the association of the ABI, the CAC-Agatston score and the IMT with MCI and its subtypes. RESULTS We identified 490 participants with MCI (mean age 66.1 ± 7.8, 46.9 % male, aMCI n = 249, naMCI n = 241) and 1,242 cognitively normal participants. A decreasing ABI (per 0.1) was significantly associated with a higher MCI prevalence in fully adjusted models (PR 1.06; 95% confidence interval (CI) 1.01-1.11), whereas an increasing CAC (log(CAC+1)) or IMT (per 0.1 mm) were not associated after adjustment. A decreasing ABI was also significantly associated with naMCI in fully adjusted models (PR 1.12; CI 1.03-1.21) but not with aMCI. CONCLUSIONS Our data show that the degree of generalized atherosclerosis as measured by the ABI is associated with MCI and with naMCI in a population-based cohort.
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Affiliation(s)
- Christian Weimar
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Germany
| | - Angela Winkler
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Germany
| | - Martha Dlugaj
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Germany
| | - Nils Lehmann
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Frauke Hennig
- IUF-Leibniz Research Institute for Environmental Medicine
| | - Marcus Bauer
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Knut Kröger
- Department of Angiology, Helios Kliniken Krefeld, Germany
| | - Hagen Kälsch
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Amir-Abass Mahabadi
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Nico Dragano
- Institute for Medical Sociology, Centre for Healthy and Society, Medical Faculty, University of Düsseldorf, Germany
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Barbara Hoffmann
- IUF-Leibniz Research Institute for Environmental Medicine.,Medical Faculty, Deanery of Medicine, Heinrich-Heine-University of Düsseldorf, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Germany
| | - Raimund Erbel
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Germany
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Dlugaj M, Winkler A, Weimar C, Dürig J, Broecker-Preuss M, Dragano N, Moebus S, Jöckel KH, Erbel R, Eisele L. Anemia and Mild Cognitive Impairment in the German General Population. J Alzheimers Dis 2015; 49:1031-42. [PMID: 26599053 DOI: 10.3233/jad-150434] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- Martha Dlugaj
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Angela Winkler
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Christian Weimar
- Department of Neurology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Jan Dürig
- Department of Hematology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Martina Broecker-Preuss
- Department of Endocrinology, Division of Laboratory Research, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Nico Dragano
- Institute for Medical Sociology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Susanne Moebus
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Raimund Erbel
- Clinic of Cardiology, West German Heart Centre, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
| | - Lewin Eisele
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany
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