Venkatesh L Murthy1, Matthew Nayor2, Mercedes Carnethon3, Jared P Reis4, Donald Lloyd-Jones3, Norrina B Allen3, Robert Kitchen5, Paolo Piaggi6, Lyn M Steffen7, Ramachandran S Vasan8,9, Jane E Freedman10, Clary B Clish11, Ravi V Shah12. 1. Department of Medicine and Radiology, University of Michigan, Ann Arbor, MI, USA. vlmurthy@med.umich.edu. 2. Section of Cardiovascular Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA. 3. Northwestern University, Chicago, IL, USA. 4. National Heart, Lung, and Blood Institute, Bethesda, MD, USA. 5. Simches Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA. 6. Department of Information Engineering, University of Pisa, Pisa, Italy. 7. University of Minnesota School of Public Health, Minneapolis, MN, USA. 8. Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, USA. 9. Framingham Heart Study, Framingham, MA, USA. 10. Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA. 11. Broad Institute of Harvard and MIT, Cambridge, MA, USA. 12. Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA. ravi.shah@vumc.org.
Abstract
AIMS/HYPOTHESIS: The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development. METHODS: We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts. RESULTS: We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07). CONCLUSIONS/ INTERPRETATION: Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course.
AIMS/HYPOTHESIS: The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development. METHODS: We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts. RESULTS: We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07). CONCLUSIONS/ INTERPRETATION: Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course.
Authors: A C Panveloski-Costa; S Silva Teixeira; I M R Ribeiro; C Serrano-Nascimento; R X das Neves; R R Favaro; M Seelaender; V R Antunes; M T Nunes Journal: Acta Physiol (Oxf) Date: 2016-01-30 Impact factor: 6.311
Authors: Paul Petrus; Simon Lecoutre; Lucile Dollet; Clotilde Wiel; André Sulen; Hui Gao; Beatriz Tavira; Jurga Laurencikiene; Olav Rooyackers; Antonio Checa; Iyadh Douagi; Craig E Wheelock; Peter Arner; Mark McCarthy; Martin O Bergo; Laurienne Edgar; Robin P Choudhury; Myriam Aouadi; Anna Krook; Mikael Rydén Journal: Cell Metab Date: 2019-12-19 Impact factor: 27.287
Authors: Filip Ottosson; Ulrika Ericson; Peter Almgren; Einar Smith; Louise Brunkwall; Sophie Hellstrand; Peter M Nilsson; Marju Orho-Melander; Céline Fernandez; Olle Melander Journal: J Am Heart Assoc Date: 2019-09-19 Impact factor: 5.501