Cornelia Huth1,2, Alina Bauer3, Astrid Zierer3, Julie Sudduth-Klinger4, Christa Meisinger5,6, Michael Roden7,8,9, Annette Peters3,7,10, Wolfgang Koenig10,11,12, Christian Herder7,8,9, Barbara Thorand3,7. 1. Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany. huth@helmholtz-muenchen.de. 2. German Center for Diabetes Research (DZD), München-Neuherberg, Germany. huth@helmholtz-muenchen.de. 3. Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany. 4. Tethys Bioscience Inc., Emeryville, CA, USA. 5. Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany. 6. Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neuherberg, Germany. 7. German Center for Diabetes Research (DZD), München-Neuherberg, Germany. 8. Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 9. Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany. 10. German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany. 11. Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany. 12. Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.
Abstract
BACKGROUND: Biomarkers may contribute to our understanding of the pathophysiology of various diseases. Type 2 diabetes (T2D) and coronary heart disease (CHD) share many clinical and lifestyle risk factors and several biomarkers are associated with both diseases. The current analysis aims to assess the relevance of biomarkers combined to pathway groups for the development of T2D and CHD in the same cohort. METHODS: Forty-seven serum biomarkers were measured in the MONICA/KORA case-cohort study using clinical chemistry assays and ultrasensitive molecular counting technology. The T2D (CHD) analyses included 689 (568) incident cases and 1850 (2004) non-cases from three population-based surveys. At baseline, the study participants were 35-74 years old. The median follow-up was 14 years. We computed Cox regression models for each biomarker, adjusted for age, sex, and survey. Additionally, we assigned the biomarkers to 19 etiological pathways based on information from literature. One age-, sex-, and survey-controlled average variable was built for each pathway. We used the R2PM coefficient of determination to assess the explained disease risk. RESULTS: The associations of many biomarkers, such as several cytokines or the iron marker soluble transferrin receptor (sTfR), were similar in strength for T2D and CHD, but we also observed important differences. Lipoprotein (a) (Lp(a)) and N-terminal pro B-type natriuretic peptide (NT-proBNP) even demonstrated opposite effect directions. All pathway variables together explained 49% of the T2D risk and 21% of the CHD risk. The insulin-like growth factor binding protein 2 (IGFBP-2, IGF/IGFBP system pathway) best explained the T2D risk (about 9% explained risk, independent of all other pathway variables). For CHD, the myocardial-injury- and lipid-related-pathways were most important and both explained about 4% of the CHD risk. CONCLUSIONS: The biomarker-derived pathway variables explained a higher proportion of the T2D risk compared to CHD. The ranking of the pathways differed between the two diseases, with the IGF/IGFBP-system-pathway being most strongly associated with T2D and the myocardial-injury- and lipid-related-pathways with CHD. Our results help to better understand the pathophysiology of the two diseases, with the ultimate goal of pointing out targets for lifestyle intervention and drug development to ideally prevent both T2D and CHD development.
BACKGROUND: Biomarkers may contribute to our understanding of the pathophysiology of various diseases. Type 2 diabetes (T2D) and coronary heart disease (CHD) share many clinical and lifestyle risk factors and several biomarkers are associated with both diseases. The current analysis aims to assess the relevance of biomarkers combined to pathway groups for the development of T2D and CHD in the same cohort. METHODS: Forty-seven serum biomarkers were measured in the MONICA/KORA case-cohort study using clinical chemistry assays and ultrasensitive molecular counting technology. The T2D (CHD) analyses included 689 (568) incident cases and 1850 (2004) non-cases from three population-based surveys. At baseline, the study participants were 35-74 years old. The median follow-up was 14 years. We computed Cox regression models for each biomarker, adjusted for age, sex, and survey. Additionally, we assigned the biomarkers to 19 etiological pathways based on information from literature. One age-, sex-, and survey-controlled average variable was built for each pathway. We used the R2PM coefficient of determination to assess the explained disease risk. RESULTS: The associations of many biomarkers, such as several cytokines or the iron marker soluble transferrin receptor (sTfR), were similar in strength for T2D and CHD, but we also observed important differences. Lipoprotein (a) (Lp(a)) and N-terminal pro B-type natriuretic peptide (NT-proBNP) even demonstrated opposite effect directions. All pathway variables together explained 49% of the T2D risk and 21% of the CHD risk. The insulin-like growth factor binding protein 2 (IGFBP-2, IGF/IGFBP system pathway) best explained the T2D risk (about 9% explained risk, independent of all other pathway variables). For CHD, the myocardial-injury- and lipid-related-pathways were most important and both explained about 4% of the CHD risk. CONCLUSIONS: The biomarker-derived pathway variables explained a higher proportion of the T2D risk compared to CHD. The ranking of the pathways differed between the two diseases, with the IGF/IGFBP-system-pathway being most strongly associated with T2D and the myocardial-injury- and lipid-related-pathways with CHD. Our results help to better understand the pathophysiology of the two diseases, with the ultimate goal of pointing out targets for lifestyle intervention and drug development to ideally prevent both T2D and CHD development.
Authors: Raphael S Peter; Andrea Jaensch; Ute Mons; Ben Schöttker; Roman Schmucker; Wolfgang Koenig; Hermann Brenner; Dietrich Rothenbacher Journal: Cardiovasc Diabetol Date: 2021-05-13 Impact factor: 9.951
Authors: Suriya Prausmüller; Michael Resl; Henrike Arfsten; Georg Spinka; Raphael Wurm; Stephanie Neuhold; Philipp E Bartko; Georg Goliasch; Guido Strunk; Noemi Pavo; Martin Clodi; Martin Hülsmann Journal: Cardiovasc Diabetol Date: 2021-02-02 Impact factor: 9.951
Authors: Margarita Ortiz-Martínez; Mirna González-González; Alexandro J Martagón; Victoria Hlavinka; Richard C Willson; Marco Rito-Palomares Journal: Curr Diab Rep Date: 2022-03-10 Impact factor: 5.430
Authors: Marie-Theres Huemer; Cornelia Huth; Florian Schederecker; Stefanie J Klug; Christa Meisinger; Wolfgang Koenig; Wolfgang Rathmann; Annette Peters; Barbara Thorand Journal: BMJ Open Diabetes Res Care Date: 2020-07
Authors: Barbara Thorand; Astrid Zierer; Mustafa Büyüközkan; Jan Krumsiek; Alina Bauer; Florian Schederecker; Julie Sudduth-Klinger; Christa Meisinger; Harald Grallert; Wolfgang Rathmann; Michael Roden; Annette Peters; Wolfgang Koenig; Christian Herder; Cornelia Huth Journal: J Clin Endocrinol Metab Date: 2021-03-25 Impact factor: 5.958