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Lv Y, Luo WJ. Dapagliflozin and sacubitril on myocardial microperfusion in patients with post-acute myocardial infarction heart failure and type 2 diabetes. World J Clin Cases 2024; 12:5008-5015. [DOI: 10.12998/wjcc.v12.i22.5008] [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: 05/07/2024] [Revised: 06/09/2024] [Accepted: 06/18/2024] [Indexed: 06/30/2024] Open
Abstract
BACKGROUND Coronary heart disease and type 2 diabetes mellitus (T2DM) frequently coexist, creating a complex and challenging clinical scenario, particularly when complicated with acute myocardial infarction (AMI).
AIM To examine the effects of dapagliflozin combined with sakubactrovalsartan sodium tablets on myocardial microperfusion.
METHODS In total, 98 patients were categorized into control (n = 47) and observation (n = 51) groups. The control group received noxital, while the observation group was treated with dapagliflozin combined with noxital for 6 months. Changes in myocardial microperfusion, blood glucose level, cardiac function, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) level, growth differentiation factor-15 (GDF-15) level, and other related factors were compared between the two groups. Additionally, the incidence of major adverse cardiovascular events (MACE) and adverse reactions were calculated.
RESULTS After treatment, in the observation and control groups, the corrected thrombolysis in myocardial infarction frame counts were 37.12 ± 5.02 and 48.23 ± 4.66, respectively. The NT-proBNP levels were 1502.65 ± 255.87 and 2015.23 ± 286.31 pg/mL, the N-terminal pro-atrial natriuretic peptide (NT-proANP) levels were 1415.69 ± 213.05 and 1875.52 ± 241.02 ng/mL, the GDF-15 levels were 0.87 ± 0.43 and 1.21 ± 0.56 g/L, and the high-sensitivity C-reactive protein (hs-CRP) levels were 6.54 ± 1.56 and 8.77 ± 1.94 mg/L, respectively, with statistically significant differences (P < 0.05). The cumulative incidence of MACEs in the observation group was significantly lower than that in the control group (P < 0.05). The incidence of adverse reactions was 13.73% (7/51) in the observation group and 10.64% (5/47) in the control group, with no statistically significant difference (P > 0.05).
CONCLUSION Dapagliflozin combined with nocinto can improve myocardial microperfusion and left ventricular remodeling and reduce MACE incidence in patients with post-AMI heart failure and T2DM. The underlying mechanism may be related to the reduction in the expression levels of NT-proANP, GDF-15, and hs-CRP.
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Affiliation(s)
- Yuan Lv
- Department of Cardiology, Lishui People's Hospital, Lishui 323000, Zhejiang Province, China
| | - Wei-Jun Luo
- Department of Cardiology, Lishui People's Hospital, Lishui 323000, Zhejiang Province, China
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Elhadad MA, Del C Gómez-Alonso M, Chen CW, Neumeyer S, Delerue T, Rathmann W, Näbauer M, Meisinger C, Kääb S, Seissler J, Graumann J, Koenig W, Suhre K, Gieger C, Völker U, Peters A, Hammer E, Waldenberger M. Plasma proteome association with coronary heart disease and carotid intima media thickness: results from the KORA F4 study. Cardiovasc Diabetol 2024; 23:181. [PMID: 38811951 PMCID: PMC11138055 DOI: 10.1186/s12933-024-02274-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 05/08/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND AND AIMS Atherosclerosis is the main cause of stroke and coronary heart disease (CHD), both leading mortality causes worldwide. Proteomics, as a high-throughput method, could provide helpful insights into the pathological mechanisms underlying atherosclerosis. In this study, we characterized the associations of plasma protein levels with CHD and with carotid intima-media thickness (CIMT), as a surrogate measure of atherosclerosis. METHODS The discovery phase included 1000 participants from the KORA F4 study, whose plasma protein levels were quantified using the aptamer-based SOMAscan proteomics platform. We evaluated the associations of plasma protein levels with CHD using logistic regression, and with CIMT using linear regression. For both outcomes we applied two models: an age-sex adjusted model, and a model additionally adjusted for body mass index, smoking status, physical activity, diabetes status, hypertension status, low density lipoprotein, high density lipoprotein, and triglyceride levels (fully-adjusted model). The replication phase included a matched case-control sample from the independent KORA F3 study, using ELISA-based measurements of galectin-4. Pathway analysis was performed with nominally associated proteins (p-value < 0.05) from the fully-adjusted model. RESULTS In the KORA F4 sample, after Bonferroni correction, we found CHD to be associated with five proteins using the age-sex adjusted model: galectin-4 (LGALS4), renin (REN), cathepsin H (CTSH), and coagulation factors X and Xa (F10). The fully-adjusted model yielded only the positive association of galectin-4 (OR = 1.58, 95% CI = 1.30-1.93), which was successfully replicated in the KORA F3 sample (OR = 1.40, 95% CI = 1.09-1.88). For CIMT, we found four proteins to be associated using the age-sex adjusted model namely: cytoplasmic protein NCK1 (NCK1), insulin-like growth factor-binding protein 2 (IGFBP2), growth hormone receptor (GHR), and GDNF family receptor alpha-1 (GFRA1). After assessing the fully-adjusted model, only NCK1 remained significant (β = 0.017, p-value = 1.39e-06). Upstream regulators of galectin-4 and NCK1 identified from pathway analysis were predicted to be involved in inflammation pathways. CONCLUSIONS Our proteome-wide association study identified galectin-4 to be associated with CHD and NCK1 to be associated with CIMT. Inflammatory pathways underlying the identified associations highlight the importance of inflammation in the development and progression of CHD.
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Affiliation(s)
- Mohamed A Elhadad
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- Department of Internal Medicine B, University Medicine Greifswald, Ferdinand-Sauerbruch-Str., 17475, Greifswald, Germany.
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany.
| | - Mónica Del C Gómez-Alonso
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Chien-Wei Chen
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Information Sciences, Biometry and Epidemiology Medical Faculty, Ludwig-Maximilians-University, Munich, Germany
| | - Sonja Neumeyer
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Partner Site Düsseldorf, Düsseldorf, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Näbauer
- Medizinische Klinik und Poliklinik I, Klinikum der Universität München, Munich, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Munich, Germany
| | - Christa Meisinger
- Chair of Epidemiology, University of Augsburg, 86156, Augsburg, Germany
| | - Stefan Kääb
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Munich, Germany
- Department of Cardiology, Medical Policlinic and University Clinic I, Munich, Germany
| | - Jochen Seissler
- Department of Internal Medicine IV, University Hospital of Ludwig-Maximilians-University, Munich, Germany
| | - Johannes Graumann
- Department of Medicine, Institute of Translational Proteomics, Philipps-Universität Marburg, Marburg, Germany
| | - Wolfgang Koenig
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Munich, Germany
- Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, 24144, Doha, Qatar
- Department of Biophysics and Physiology, Weill Cornell Medicine, 10065, New York, NY , USA
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Munich, Germany
| | - Uwe Völker
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Annette Peters
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Information Sciences, Biometry and Epidemiology Medical Faculty, Ludwig-Maximilians-University, Munich, Germany
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, Munich, Germany
| | - Elke Hammer
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, 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] [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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4
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He J, Yang M, Song C, Zhang R, Yuan S, Li J, Dou K. Lipoprotein(a) is associated with recurrent cardiovascular events in patients with coronary artery disease and prediabetes or diabetes. J Endocrinol Invest 2024; 47:883-894. [PMID: 37777699 DOI: 10.1007/s40618-023-02203-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 09/17/2023] [Indexed: 10/02/2023]
Abstract
PURPOSE Elevated lipoprotein(a) [Lp(a)] and diabetes mellitus (DM) are both associated with adverse events in high-risk patients with established coronary artery disease (CAD). Currently, the association between Lp(a) levels and recurrent cardiovascular (CV) events (CVEs) remained undetermined in patients with different glucose status. Therefore, this study aimed to investigate the prognostic significance of Lp(a) levels for recurrent CVEs in high-risk CAD patients who suffered from first CVEs according to different glycemic metabolism. METHODS We recruited 5257 consecutive patients with prior CVEs and followed up for recurrent CVEs, including CV death, non-fatal myocardial infarction (MI), and non-fatal stroke. Patients were assigned to low, medium, and high groups according to Lp(a) levels and further stratified by glucose status. RESULTS During a median 37-month follow-up, 225 (4.28%) recurrent CVEs occurred. High Lp(a) was independently associated with recurrent CVEs [adjusted Hazard Ratio (HR), 1.57; 95% confidence interval (CI) 1.12-2.19; P = 0.008]. When participants were classified according to Lp(a) levels and glycemic status, high Lp(a) levels were associated with an increased risk of recurrent CVEs in pre-DM (adjusted HR, 2.96; 95% CI 1.24-7.05; P = 0.014). Meanwhile, medium and high Lp(a) levels were both associated with an increased risk for recurrent CVEs in DM (adjusted HR, 3.09; 95% CI 1.30-7.34; P = 0.010 and adjusted HR, 3.13, 95% CI 1.30-7.53; P = 0.011, respectively). CONCLUSIONS This study demonstrated that elevated Lp(a) levels were associated with an increased recurrent CVE risk in patients with CAD, particularly among those with pre-DM and DM, indicating that Lp(a) may provide incremental value in risk stratification in this population.
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Affiliation(s)
- J He
- State Key Laboratory of Cardiovascular Disease, Beijing, China
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - M Yang
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - C Song
- State Key Laboratory of Cardiovascular Disease, Beijing, China
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - R Zhang
- State Key Laboratory of Cardiovascular Disease, Beijing, China
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- National Clinical Research Center for Cardiovascular Diseases, Beijing, China
| | - S Yuan
- State Key Laboratory of Cardiovascular Disease, Beijing, China
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Li
- State Key Laboratory of Cardiovascular Disease, Beijing, China.
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China.
| | - K Dou
- State Key Laboratory of Cardiovascular Disease, Beijing, China.
- Cardiometabolic Medicine Center, State Key Laboratory of Cardiovascular Disease, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 167A Beilishi Road, Xi Cheng District, Beijing, 100037, China.
- Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- National Clinical Research Center for Cardiovascular Diseases, Beijing, China.
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Rauzier C, Chartrand DJ, Alméras N, Lemieux I, Larose E, Mathieu P, Pibarot P, Lamarche B, Rhéaume C, Poirier P, Després JP, Picard F. Plasma IGFBP-2 levels reveal heterogeneity in hepatic fat content in adults with excess visceral adiposity. Front Endocrinol (Lausanne) 2023; 14:1222101. [PMID: 37854178 PMCID: PMC10579942 DOI: 10.3389/fendo.2023.1222101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 09/05/2023] [Indexed: 10/20/2023] Open
Abstract
Lay summary Obesity is frequently accompanied by a fatty liver. However, some individuals with high abdominal fat levels nevertheless have low levels of liver fat. Reasons for such discordant phenotypes are unclear. In this paper, we report that among asymptomatic individuals with high levels of visceral fat, low concentrations of IGFBP-2 in the circulation were associated with significantly higher hepatic fat content compared to those with high IGFBP-2 levels. We conclude that quantification of plasma IGFBP-2 concentrations may be useful to identify the early risk for liver fat accumulation in apparently healthy individuals without cardiovascular symptoms. Aim/hypothesis Although excess visceral adiposity (VAT) is generally associated with increased liver fat (LF), recent evidence has revealed heterogeneity in LF content among adults with visceral obesity, potentially contributing to specific differences in cardiometabolic outcomes. Reasons for such discordant VAT-LF phenotypes are largely unknown. The present study aimed at assessing whether circulating levels of insulin growth-factor binding protein-2 (IGFBP-2) could be a useful biomarker in the identification of heterogenous and discordant VAT-LF phenotypes. Methods A sample of 308 middle-aged Caucasian apparently healthy men and women without cardiovascular symptoms were studied for the present cross-sectional analyses. Fasting plasma glucose and lipid levels were assessed and an oral glucose tolerance test was performed. Hepatic fat fraction (HFF) was measured using magnetic resonance spectroscopy whereas VAT was assessed by magnetic resonance imaging. Plasma IGFBP-2 levels were quantified by ELISA. Participants were then classified on the basis of median VAT (81 mL) and IGFBP-2 levels (233 ng/mL). Results Individuals with high levels of VAT were characterized by higher waist circumference, lower insulin sensitivity, as well as by higher plasma triglyceride and lower HDL-cholesterol levels. Plasma IGFBP-2 levels were inversely correlated with HFF (r = -0.39, p < 0.0001). Among men and women with high levels of VAT, those with low levels of IGFBP-2 had significantly higher HFF (7.5 ± 0.7%), compared to participants with high IGFBP-2 concentrations (3.2 ± 0.5%, p < 0.0001). Conclusion In the presence of excess VAT, high IGFBP-2 concentrations are associated with low levels of LF. Although additional studies will be necessary to establish causality and further clarify the clinical implications of these observations, these findings are concordant with a novel function of IGFBP-2 in modulating susceptibility to non-alcoholic fatty liver disease (NAFLD) in the presence of visceral obesity.
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Affiliation(s)
- Chloé Rauzier
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Faculté de pharmacie, Université Laval, Québec, QC, Canada
| | - Dominic J. Chartrand
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de kinésiologie, Faculté de médecine, Université Laval, Québec, QC, Canada
| | - Natalie Alméras
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de kinésiologie, Faculté de médecine, Université Laval, Québec, QC, Canada
| | - Isabelle Lemieux
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
| | - Eric Larose
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de médecine, Faculté de médecine, Université Laval, Québec, QC, Canada
| | - Patrick Mathieu
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de chirurgie, Faculté de médecine, Université Laval, Québec, QC, Canada
| | - Philippe Pibarot
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de médecine, Faculté de médecine, Université Laval, Québec, QC, Canada
| | - Benoît Lamarche
- Centre Nutrition, santé et société (NUTRISS), Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC, Canada
- École de nutrition, Faculté des sciences de l’agriculture et de l’alimentation, Université Laval, Québec, QC, Canada
| | - Caroline Rhéaume
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de médecine familiale et de médecine d’urgence, Faculté de médecine, Université Laval, Québec, QC, Canada
- VITAM – Centre de recherche en santé durable, Québec, QC, Canada
| | - Paul Poirier
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Faculté de pharmacie, Université Laval, Québec, QC, Canada
| | - Jean-Pierre Després
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Département de kinésiologie, Faculté de médecine, Université Laval, Québec, QC, Canada
- VITAM – Centre de recherche en santé durable, Québec, QC, Canada
| | - Frédéric Picard
- Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec (IUCPQ) – Université Laval, Québec, QC, Canada
- Faculté de pharmacie, Université Laval, Québec, QC, Canada
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Ortiz-Martínez M, González-González M, Martagón AJ, Hlavinka V, Willson RC, Rito-Palomares M. Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus. Curr Diab Rep 2022; 22:95-115. [PMID: 35267140 PMCID: PMC8907395 DOI: 10.1007/s11892-022-01453-4] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/27/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE OF REVIEW Diabetes mellitus is a complex, chronic illness characterized by elevated blood glucose levels that occurs when there is cellular resistance to insulin action, pancreatic β-cells do not produce sufficient insulin, or both. Diabetes prevalence has greatly increased in recent decades; consequently, it is considered one of the fastest-growing public health emergencies globally. Poor blood glucose control can result in long-term micro- and macrovascular complications such as nephropathy, retinopathy, neuropathy, and cardiovascular disease. Individuals with diabetes require continuous medical care, including pharmacological intervention as well as lifestyle and dietary changes. RECENT FINDINGS The most common form of diabetes mellitus, type 2 diabetes (T2DM), represents approximately 90% of all cases worldwide. T2DM occurs more often in middle-aged and elderly adults, and its cause is multifactorial. However, its incidence has increased in children and young adults due to obesity, sedentary lifestyle, and inadequate nutrition. This high incidence is also accompanied by an estimated underdiagnosis prevalence of more than 50% worldwide. Implementing successful and cost-effective strategies for systematic screening of diabetes mellitus is imperative to ensure early detection, lowering patients' risk of developing life-threatening disease complications. Therefore, identifying new biomarkers and assay methods for diabetes mellitus to develop robust, non-invasive, painless, highly-sensitive, and precise screening techniques is essential. This review focuses on the recent development of new clinically validated and novel biomarkers as well as the methods for their determination that represent cost-effective alternatives for screening and early diagnosis of T2DM.
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Affiliation(s)
- Margarita Ortiz-Martínez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
| | - Mirna González-González
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México.
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México.
| | - Alexandro J Martagón
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México City, México
| | - Victoria Hlavinka
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA
| | - Richard C Willson
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA
| | - Marco Rito-Palomares
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México
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Osawa Y, Tanaka T, Semba RD, Fantoni G, Moaddel R, Candia J, Simonsick EM, Bandinelli S, Ferrucci L. Proteins in the pathway from high red blood cell width distribution to all-cause mortality. EBioMedicine 2022; 76:103816. [PMID: 35065420 PMCID: PMC8784626 DOI: 10.1016/j.ebiom.2022.103816] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 12/21/2021] [Accepted: 01/06/2022] [Indexed: 01/01/2023] Open
Abstract
Background The pathophysiological mechanisms underlying the association between red blood cell distribution width (RDW) and all-cause mortality are unknown. We conducted a data-driven discovery investigation to identify plasma proteins that mediate the association between RDW and time to death in community-dwelling adults. Methods At baseline, 962 adults (women, 54·4%; age range, 21–98 years) participated in the InCHIANTI, “Aging in the Chianti Area” study, and proteomics data were generated from their plasma specimens. Of these, 623 participants had proteomics data available at the 9-year follow-up. For each visit, a total of 1301 plasma proteins were measured using SOMAscan technology. Complete data on vital status were available up to the 15-year follow-up period. Protein-specific exponential distribution accelerated failure time, and linear regression analyses adjusted for possible covariates were used for mortality and mediation analyses, respectively (survival data analysis). Findings Baseline values of EGFR, GHR, NTRK3, SOD2, KLRF1, THBS2, TIMP1, IGFBP2, C9, APOB, and LRP1B mediated the association between baseline RDW and all-cause mortality. Changes in IGFBP2 and C7 over 9 years mediated the association between changes in RDW and 6-year all-cause mortality. Interpretation Cellular senescence may contribute to the association between RDW and mortality. Funding This study was funded by grants from the National Institutes of Health (NIH) and the National Institute on Aging (NIA) contract and was supported by the Intramural Research Program of the NIA, NIH. The InCHIANTI study was supported as a ‘targeted project’ by the Italian Ministry of Health and in part by the U.S. NIA.
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Affiliation(s)
- Yusuke Osawa
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA; Graduate School of Health Management, Keio University, Kanagawa, Japan; Sports Medicine Research Center, Keio University, Kanagawa, Japan.
| | - Toshiko Tanaka
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA
| | - Richard D Semba
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Giovanna Fantoni
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA
| | - Ruin Moaddel
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA
| | - Julián Candia
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Eleanor M Simonsick
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA
| | | | - Luigi Ferrucci
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital 5th floor, 3001 S. Hanover Street, Baltimore, MD 21225 USA.
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8
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Birukov A, Polemiti E, Jäger S, Stefan N, Schulze MB. Fetuin-A and risk of diabetes-related vascular complications: a prospective study. Cardiovasc Diabetol 2022; 21:6. [PMID: 34998417 PMCID: PMC8742328 DOI: 10.1186/s12933-021-01439-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/13/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Fetuin-A is a hepatokine which has the capacity to prevent vascular calcification. Moreover, it is linked to the induction of metabolic dysfunction, insulin resistance and associated with increased risk of diabetes. It has not been clarified whether fetuin-A associates with risk of vascular, specifically microvascular, complications in patients with diabetes. We aimed to investigate whether pre-diagnostic plasma fetuin-A is associated with risk of complications once diabetes develops. METHODS Participants with incident type 2 diabetes and free of micro- and macrovascular disease from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 587) were followed for microvascular and macrovascular complications (n = 203 and n = 60, respectively, median follow-up: 13 years). Plasma fetuin-A was measured approximately 4 years prior to diabetes diagnosis. Prospective associations between baseline fetuin-A and risk of complications were assessed with Cox regression. RESULTS In multivariable models, fetuin-A was linearly inversely associated with incident total and microvascular complications, hazard ratio (HR, 95% CI) per standard deviation (SD) increase: 0.86 (0.74; 0.99) for total, 0.84 (0.71; 0.98) for microvascular and 0.92 (0.68; 1.24) for macrovascular complications. After additional adjustment for cardiometabolic plasma biomarkers, including triglycerides and high-density lipoprotein, the associations were slightly attenuated: 0.88 (0.75; 1.02) for total, 0.85 (0.72; 1.01) for microvascular and 0.95 (0.67; 1.34) for macrovascular complications. No interaction by sex could be observed (p > 0.10 for all endpoints). CONCLUSIONS Our data show that lower plasma fetuin-A levels measured prior to the diagnosis of diabetes may be etiologically implicated in the development of diabetes-associated microvascular disease.
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Affiliation(s)
- Anna Birukov
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany.
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
| | - Elli Polemiti
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Susanne Jäger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Norbert Stefan
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Department of Internal Medicine IV, University Hospital of Tübingen, Tübingen, Germany
- Institute of Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich, Tübingen, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany.
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany.
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9
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Wu L, Zhang Y, Zhao H, Rong G, Huang P, Wang F, Xu T. Dissecting the Association of Apolipoprotein E Gene Polymorphisms With Type 2 Diabetes Mellitus and Coronary Artery Disease. Front Endocrinol (Lausanne) 2022; 13:838547. [PMID: 35211094 PMCID: PMC8861372 DOI: 10.3389/fendo.2022.838547] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/10/2022] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Apolipoprotein E (APOE) gene mediates lipoprotein clearance and is one of the most studied candidate genes for type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD). This study was performed to determine the association between APOE polymorphisms and T2DM with and without CAD, and its effect on plasma lipid levels in a Chinese population. METHODS A total of 1,414 subjects involving 869 patients and 545 health individuals were recruited. These patients were categorized into three distinct groups: 264 in T2DM group, 401 in CAD group, and 204 in T2DM+CAD group. Logistic regression analysis was used to obtain odds ratio (OR) and 95% confidence interval (CI) in predicting the risk probability of APOE. Besides, a meta-analysis was preformed to integrate an evaluation index to evaluate their associations. RESULTS Genotype frequency ratio of genotype ϵ3/4 and allele ϵ4 among the CAD patients with or without T2DM was obviously increased. Compared with ϵ3/3 genotype, the ϵ3/4 genotype had a significant increased risk of CAD (adjusted OR = 1.90, 95% CI = 1.30-2.77) and T2DM+CAD (adjusted OR = 1.95, 95% CI = 1.24-3.08). In the meta-analysis, four studies were included and provided a strong evidence for the APOE ϵ4 mutation elevating the risk of CAD in patients with T2DM (ϵ3/ϵ4+ϵ4/ϵ4 vs. ϵ3/ϵ3, OR = 1.51, 95% CI = 1.13-2.02). In the T2DM group, the plasma levels of low-density lipoprotein cholesterol (LDL-C) showed significant difference among the three APOE isoforms. The high-density lipoprotein cholesterol (HDL-C) levels of CAD patients with ϵ4-bearing genotypes were lower than those with ϵ3/3 genotype. CONCLUSIONS Our results indicate that APOE gene polymorphisms are related to CAD with or without T2DM and have influence on lipid profiles in both T2DM and CAD patients.
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Affiliation(s)
- Lei Wu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Yan Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Hong Zhao
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Guodong Rong
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Peijun Huang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Fang Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
| | - Ting Xu
- Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- National Key Clinical Department of Laboratory Medicine, Nanjing, China
- *Correspondence: Ting Xu,
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10
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Zheng J, Huang M, Huang Q, Chen Q, Chen Z. The relationship between fetuin-A and coronary atherosclerotic heart disease (CHD) and CHD-related risk factors: A retrospective study. Medicine (Baltimore) 2021; 100:e27481. [PMID: 34713826 PMCID: PMC8556024 DOI: 10.1097/md.0000000000027481] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 09/14/2021] [Indexed: 01/05/2023] Open
Abstract
Fetuin-A plays an important role in antivascular calcification and inflammatory response, it is necessary to explore the relationship between fetuin-A and coronary atherosclerotic heart disease (CHD) and CHD-related risk factors.A total of 92 patients with CHD as the research group, and 60 healthy persons as the control group were enrolled from May 2019 to May 2020. Fetuin-A levels were determined by enzyme-linked immunosorbent assay, and the characteristics and clinical data were collected and compared. Logistic regression was used to analyze the factors influencing CHD.The age, proportion of males, patients with hypertension and diabetes, as well as fetuin-A level in the research group were significantly higher than those in the control group, but the high-density lipoprotein cholesterol level was significantly lower than that in the control group (P < .05). Logistic regression analysis and correction showed that gender, age, blood pressure, and diabetes were related to the onset of CHD, and there was a significant correlation between the level of fetuin-A and age (P < .05).Serum fetuin-A was related to the onset risk of CHD, and showed a significant correlation with age.
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11
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Bauer A, Zierer A, Gieger C, Büyüközkan M, Müller-Nurasyid M, Grallert H, Meisinger C, Strauch K, Prokisch H, Roden M, Peters A, Krumsiek J, Herder C, Koenig W, Thorand B, Huth C. Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study. Genet Epidemiol 2021; 45:633-650. [PMID: 34082474 DOI: 10.1002/gepi.22389] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 04/20/2021] [Accepted: 05/04/2021] [Indexed: 12/19/2022]
Abstract
It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PLMetabo ); validation of two comprehensive polygenic risk scores: GRSGola based on Metabochip data, and GRSKhera (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDIrel ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRSMetabo and PLMetabo , GRSGola significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDIrel : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRSKhera yielded slightly worse prediction results than GRSGola .
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Affiliation(s)
- Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Astrid Zierer
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Mustafa Büyüközkan
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, USA
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Chair of Epidemiology, LMU Munich, UNIKA-T Augsburg, Augsburg, Germany.,Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technische Universität München, München, Germany.,Institute of Neurogenomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Michael Roden
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, USA
| | - Christian Herder
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, 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
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany
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12
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Frantsiyants E, Bandovkina V, Kaplieva I, Surikova E, Cheryarina N, Shikhlyarova A, Neskubina I, Pogorelova Y, Trepitaki L, Goroshinskaya I, Kotieva I, Morozova M. Insulin-like growth factors and their binding proteins in the heart in rats in experimental diabetes mellitus, growing Guerin’s carcinoma and under their combination. CARDIOMETRY 2021. [DOI: 10.18137/cardiometry.2021.18.138144] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Diabetes mellitus is an additional risk factor for the development of heart diseases, cardiovascular dysfunction and malignant tumors. The aim of the study was to analyze levels of IGF and IGFBP in heart samples of animals with diabetes mellitus and/ or growing Guerin’s carcinoma. The study included white outbred rats of both genders weighing 180-220 g. The rats of each gender were divided into groups of 8 animals: the intact group; test groups 1 (with diabetes) and 2 (with transplanted Guerin’s carcinoma); the main group (transplanted Guerin’s carcinoma growing in the presence of diabetes mellitus). Levels of IGF-I, IGF-II, IGFBP-1, and IGFBP-2 were measured by ELISA (Mediagnost, Germany) in heart homogenates in animals of all groups
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13
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Peter RS, Jaensch A, Mons U, Schöttker B, Schmucker R, Koenig W, Brenner H, Rothenbacher D. Prognostic value of long-term trajectories of depression for incident diabetes mellitus in patients with stable coronary heart disease. Cardiovasc Diabetol 2021; 20:108. [PMID: 33985516 PMCID: PMC8120929 DOI: 10.1186/s12933-021-01298-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/05/2021] [Indexed: 11/15/2022] Open
Abstract
Background Diabetes mellitus (DM) and depression are bidirectionally interrelated. We recently identified long-term trajectories of depression symptom severity in individuals with coronary heart disease (CHD), which were associated with the risk for subsequent cardiovascular events (CVE). We now investigated the prognostic value of these trajectories of symptoms of depression with the risk of incident DM in patients with stable coronary heart disease. Methods The KAROLA cohort included CHD patients participating in an in-patient rehabilitation program (years 1999/2000) and followed for up to 15 years. We included 1048 patients (mean age 59.4 years, 15% female) with information on prevalent DM at baseline and follow-up data. Cox proportional hazards models were used to model the risk for incident DM during follow-up by depression trajectory class adjusted for age, sex, education, smoking status, body mass index, and physical activity. In addition, we modeled the excess risk for subsequent CVE due to incident DM during follow-up for each of the depression trajectories. Results DM was prevalent in 20.7% of patients at baseline. Over follow-up, 296 (28.2%) of patients had a subsequent CVE. During follow-up, 157 (15.0%) patients developed incident DM before experiencing a subsequent CVE. Patients following a high-stable depression symptom trajectory were at substantially higher risk of developing incident DM than patients following a low-stable depression symptom trajectory (hazard ratio (HR) = 2.50; 95% confidence interval (CI) (1.35, 4.65)). A moderate-stable and an increasing depression trajectory were associated with HRs of 1.48 (95%-CI (1.10, 1.98)) and 1.77 (95%-CI (1.00, 3.15)) for incident DM. In addition, patients in the high-stable depression trajectory class who developed incident DM during follow-up were at 6.5-fold risk (HR = 6.51; 95%-CI (2.77, 15.3)) of experiencing a subsequent cardiovascular event. Conclusions In patients with CHD, following a trajectory of high
stable symptoms of depression was associated with an increased risk of incident
DM. Furthermore, incident DM in these patients was associated with a
substantially increased risk of subsequent CVE. Identifying depressive symptoms
and pertinent treatment offers might be an important and promising approach to
enhance outcomes in patients with CHD, which should be followed up in further
research and practice.
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Affiliation(s)
- Raphael S Peter
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
| | - Andrea Jaensch
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Ute Mons
- Division of Clinical Epidemiology and Ageing Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Medicine and University Hospital Cologne, Heart Center, University of Cologne, Cologne, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Ageing Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Network Ageing Research, University of Heidelberg, Heidelberg, Germany
| | | | - Wolfgang Koenig
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.,Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.,German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Ageing Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Network Ageing Research, University of Heidelberg, Heidelberg, Germany
| | - Dietrich Rothenbacher
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.,Division of Clinical Epidemiology and Ageing Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
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14
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Thorand B, Zierer A, Büyüközkan M, Krumsiek J, Bauer A, Schederecker F, Sudduth-Klinger J, Meisinger C, Grallert H, Rathmann W, Roden M, Peters A, Koenig W, Herder C, Huth C. A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population. J Clin Endocrinol Metab 2021; 106:e1647-e1659. [PMID: 33382400 PMCID: PMC7993565 DOI: 10.1210/clinem/dgaa953] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Indexed: 12/29/2022]
Abstract
CONTEXT Improved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most. OBJECTIVE This work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c). METHODS We used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c). RESULTS Interleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies. CONCLUSION The addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.
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Affiliation(s)
- Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Correspondence: Barbara Thorand, PhD, MPH, Helmholtz Zentrum München GmbH, Institute of Epidemiology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany.
| | - Astrid Zierer
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Mustafa Büyüközkan
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Florian Schederecker
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Christa Meisinger
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-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
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
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15
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Prausmüller S, Resl M, Arfsten H, Spinka G, Wurm R, Neuhold S, Bartko PE, Goliasch G, Strunk G, Pavo N, Clodi M, Hülsmann M. Performance of the recommended ESC/EASD cardiovascular risk stratification model in comparison to SCORE and NT-proBNP as a single biomarker for risk prediction in type 2 diabetes mellitus. Cardiovasc Diabetol 2021; 20:34. [PMID: 33530999 PMCID: PMC7856811 DOI: 10.1186/s12933-021-01221-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 01/20/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Recently, the European Society of Cardiology (ESC) and European Association for the Society of Diabetes (EASD) introduced a new cardiovascular disease (CVD) risk stratification model to aid further treatment decisions in individuals with diabetes. Our study aimed to investigate the prognostic performance of the ESC/EASD risk model in comparison to the Systematic COronary Risk Evaluation (SCORE) risk model and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in an unselected cohort of type 2 diabetes mellitus (T2DM). METHODS AND RESULTS A total of 1690 T2DM patients with a 10-year follow up for fatal CVD and all-cause death and a 5-year follow up for CVD and all-cause hospitalizations were analyzed. According to ESC/EASD risk criteria 25 (1.5%) patients were classified as moderate, 252 (14.9%) high, 1125 (66.6%) very high risk and 288 (17.0%) were not classifiable. Both NT-proBNP and SCORE risk model were associated with 10-year CVD and all-cause death and 5-year CVD and all-cause hospitalizations while the ESC/EASD model was only associated with 10-year all-cause death and 5-year all-cause hospitalizations. NT-proBNP and SCORE showed significantly higher C-indices than the ESC/EASD risk model for CVD death [0.80 vs. 0.53, p < 0.001; 0.64 vs. 0.53, p = 0.001] and all-cause death [0.73, 0.66 vs. 0.52, p < 0.001 for both]. The performance of SCORE improved in a subgroup without CVD aged 40-64 years compared to the unselected cohort, while NT-proBNP performance was robust across all groups. CONCLUSION The new introduced ESC/EASD risk stratification model performed limited compared to SCORE and single NT-proBNP assessment for predicting 10-year CVD and all-cause fatal events in individuals with T2DM.
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Affiliation(s)
- Suriya Prausmüller
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Michael Resl
- Department of Internal Medicine, Saint John of God Hospital Linz, Seilerstaette 2, 4021, Linz, Austria
| | - Henrike Arfsten
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Georg Spinka
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Raphael Wurm
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Stephanie Neuhold
- Department of Medicine IV, Clinic Favoriten, Kundratstraße 3, 1100, Vienna, Austria
| | - Philipp E Bartko
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Georg Goliasch
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Guido Strunk
- Complexity Research, Schönbrunner Straße 32, 1050, Vienna, Austria
| | - Noemi Pavo
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - Martin Clodi
- Department of Internal Medicine, Saint John of God Hospital Linz, Seilerstaette 2, 4021, Linz, Austria
| | - Martin Hülsmann
- Department of Internal Medicine II, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
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16
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Magalhães P, Zürbig P, Mischak H, Schleicher E. Urinary fetuin-A peptides as a new marker for impaired kidney function in patients with type 2 diabetes. Clin Kidney J 2020; 14:269-276. [PMID: 33564428 PMCID: PMC7857838 DOI: 10.1093/ckj/sfaa176] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 07/09/2020] [Indexed: 02/06/2023] Open
Abstract
Background The hepatokine fetuin-A, released by the human liver, promotes pro-inflammatory effects of perivascular fat. The involvement of inflammation in type 2 diabetes mellitus (T2DM) can affect the kidney and contribute to the development of diabetic kidney disease. Therefore we examined the association of urinary fetuin-A protein fragments with renal damage in T2DM patients. Methods Urinary peptides of 1491 individuals using proteome data available from the human urine proteome database were analysed. Prediction of proteases involved in urinary peptide generation was performed using the Proteasix tool. Results We identified 14 different urinary protein fragments that belong to the region of the connecting peptide (amino acid 301–339) of the total fetuin-A protein. Calpains (CAPN1 and CAPN2), matrix metalloproteinase and pepsin A-3 were identified as potential proteases that were partially confirmed by previous in vitro studies. Combined fetuin-A peptides (mean of amplitudes) were significantly increased in T2DM patients with kidney disease and to a lesser extent with cardiovascular risk. Furthermore, fetuin-A peptide levels displayed a significant negative correlation with baseline estimated glomerular filtration rate (eGFR) values (r = −0.316, P < 0.0001) and with the slope (%) of eGFR per year (r = −0.096, P = 0.023). A multiple regression model including fetuin-A peptide and albuminuria resulted in a significantly improved correlation with eGFR (r = −0.354, P < 0.0001) compared with albuminuria, indicating an added value of this novel biomarker. Conclusions The urinary proteome analysis demonstrated the association of fetuin-A peptides with impaired kidney function in T2DM patients. Furthermore, fetuin-A peptides displayed early signs of kidney damage before albuminuria appeared and therefore can be used as markers for kidney disease detection.
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Affiliation(s)
| | | | - Harald Mischak
- Mosaiques Diagnostics GmbH, Hannover, Germany.,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Erwin Schleicher
- Institute for Clinical Chemistry and Pathobiochemistry/Central Laboratory, University of Tübingen, Tübingen, Germany.,German Center for Diabetes Research, Tübingen; Germany.,Institute for Diabetes Research and Metabolic Diseases, Helmholtz Centre Munich, University of Tübingen, Tübingen, Germany
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17
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Abstract
PURPOSE OF THE REVIEW Proteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable profiling of the plasma proteome with the potential to improve prediction and mechanistic understanding of type 2 diabetes (T2D). RECENT FINDINGS Technological and analytical advancements have enabled identification of novel protein biomarkers and signatures that help to address challenges of existing approaches to predict and screen for T2D. Genetic studies have so far revealed putative causal roles for only few of the proteins that have been linked to T2D, but ongoing large-scale genetic studies of the plasma proteome will help to address this and increase our understanding of aetiological pathways and mechanisms leading to diabetes. Studies of the human plasma proteome have started to elucidate its potential for T2D prediction and biomarker discovery. Future studies integrating genomic and proteomic data will provide opportunities to prioritise drug targets and identify pathways linking genetic predisposition to T2D development.
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Affiliation(s)
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
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18
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Zhang Y, Jin JL, Cao YX, Zhang HW, Guo YL, Wu NQ, Zhu CG, Gao Y, Hua Q, Li YF, Xu RX, Li JJ. Lipoprotein (a) predicts recurrent worse outcomes in type 2 diabetes mellitus patients with prior cardiovascular events: a prospective, observational cohort study. Cardiovasc Diabetol 2020; 19:111. [PMID: 32646432 PMCID: PMC7350185 DOI: 10.1186/s12933-020-01083-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 07/02/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Merging studies have reported the association of lipoprotein(a) [Lp(a)] with poor outcomes of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM). However, the prognostic importance of Lp(a) for recurrent cardiovascular events (CVEs) is currently undetermined in patients with T2DM and prior CVEs. METHODS From April 2011 to March 2017, we consecutively recruited 2284 T2DM patients with prior CVEs. Patients were categorized into low, medium, and high groups by Lp(a) levels and followed up for recurrent CVEs, including nonfatal acute myocardial infarction, stroke, and cardiovascular mortality. Kaplan-Meier, Cox regression and C-statistic analyses were performed. RESULTS During 7613 patient-years' follow-up, 153 recurrent CVEs occurred. Lp(a) levels were significantly higher in patients with recurrent CVEs than counterparts (20.44 vs. 14.71 mg/dL, p = 0.002). Kaplan-Meier analysis revealed that the event-free survival rate was dramatically lower in high and medium Lp(a) groups than that in low group irrespective of HBA1c status (< 7.0%; ≥ 7.0%, both p < 0.05). Furthermore, multivariate Cox regression models indicated that Lp(a) was independently associated with high risk of recurrent CVEs [HR(95% CI): 2.049 (1.308-3.212)], such data remains in different HBA1c status (HR(95% CI): < 7.0%, 2.009 (1.051-3.840); ≥ 7.0%, 2.162 (1.148-4.073)). Moreover, the results of C-statistic were significantly improved by 0.029 when added Lp(a) to the Cox model. CONCLUSIONS Our data, for the first time, confirmed that Lp(a) was an independent predictor for recurrent CVEs in T2DM patients with prior CVEs, suggesting that Lp(a) measurement may help to further risk stratification for T2DM patients after they suffered a first CVE.
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Affiliation(s)
- Yan Zhang
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Jing-Lu Jin
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Ye-Xuan Cao
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Hui-Wen Zhang
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Yuan-Lin Guo
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Na-Qiong Wu
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Cheng-Gang Zhu
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Ying Gao
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Qi Hua
- Department of Cardiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yan-Fang Li
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Rui-Xia Xu
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China
| | - Jian-Jun Li
- State Key Laboratory of Cardiovascular Disease, FuWai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing, 100037, China.
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19
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Huemer MT, Huth C, Schederecker F, Klug SJ, Meisinger C, Koenig W, Rathmann W, Peters A, Thorand B. Association of endothelial dysfunction with incident prediabetes, type 2 diabetes and related traits: the KORA F4/FF4 study. BMJ Open Diabetes Res Care 2020; 8:8/1/e001321. [PMID: 32690629 PMCID: PMC7373312 DOI: 10.1136/bmjdrc-2020-001321] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 04/25/2020] [Accepted: 05/30/2020] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION Peripheral arterial tonometry (PAT) is an operator-independent and non-invasive measurement method to assess microvascular endothelial function in the fingertips. PAT-derived measures of endothelial function were associated with type 2 diabetes in cross-sectional studies. However, longitudinal studies are lacking. The study aims to investigate the association of two PAT-derived endothelial function parameters reactive hyperemia index (RHI) and mean baseline amplitude (MBA) with follow-up glucose and insulin parameters and the development of (pre)diabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS The study included 673 participants initially without diabetes (328 men and 345 women) aged 52-71 years from the prospective population-based Cooperative Health Research in the Region of Augsburg F4/FF4 cohort study conducted in Southern Germany (baseline examination F4: 2006-2008; follow-up FF4: 2013-2014). An oral glucose tolerance test was performed at baseline and follow-up to define type 2 diabetes, prediabetes, fasting glucose, fasting insulin, 2-hour glucose, homeostasis model assessment of insulin resistance (HOMA-IR), homeostasis model assessment of beta-cell function and hemoglobin A1c. RESULTS In multivariable adjusted logistic/linear regression models, a 1 SD increase in baseline RHI was inversely associated with incident type 2 diabetes (OR 0.69 (95% CI 0.48 to 0.97)) as well as with fasting insulin (β -0.069 (95% CI -0.131 to -0.007)) and HOMA-IR (β -0.072 (95% CI -0.133 to -0.010)) at follow-up in participants with initial normoglycemia. A 1 SD increase in baseline MBA was positively associated with incident (pre)diabetes (OR 1.62 (95% CI 1.25 to 2.11)) and fasting glucose (β 0.096 (95% CI 0.047 to 0.146)) at follow-up in participants with initial normoglycemia. CONCLUSIONS Microvascular endothelial dysfunction seems to be involved in the development of early derangements in glucose metabolism and insulin resistance and could thereby trigger the development of prediabetes and type 2 diabetes.
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Affiliation(s)
- Marie-Theres Huemer
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Department of Sport and Health Sciences, Chair of Epidemiology, Technical University Munich, Munich, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Florian Schederecker
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Stefanie J Klug
- Department of Sport and Health Sciences, Chair of Epidemiology, Technical University Munich, Munich, Germany
| | - Christa Meisinger
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Epidemiology at UNIKA-T Augsburg, Ludwig-Maximilians-Universität München, Augsburg, Germany
| | - Wolfgang Koenig
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Technische Universität München, Munich, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research, Neuherberg, Germany
- Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
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