Unmasking subclinical cardiac dysfunction in type 2 diabetes through genetic and epigenetic profiling

Abstract Background Diabetic Cardiomyopathy (DiabCM) develops in patients with Type-2-Diabetes Mellitus (T2D) and is characterized by cardiac dysfunction independent of ischemic heart disease or systemic hypertension. Its underlying mechanisms remain poorly defined with likely genetic and non-genetic mechanisms including epigenetic modifications. Combining T2D-derived polygenic risk scores (PRS) and methylation risk scores (MRS) with key clinical characteristics may aid risk stratification for myocardial dysfunction among patients with T2D. Methods We analyzed 173 deeply phenotyped participants from the CARDIATEAM discovery study, grouping them by the severity of myocardial dysfunction determined by echocardiography. Both PRS and MRS show significantly different distribution between severity groups ( p -value = 0.02 and 1.29e-05, respectively) with significant odds ratios (ORs) at ≥ 80th and ≥ 90th percentiles: PRS (2.23 [95%CI 1.03–4.92] and 2.82 [95%CI 1.02–8.34]), and MRS (4.52 [95%CI 2.01–10.83] and 3.49 [95%CI 1.22–11.02]) respectively. Combining individuals with PRS and MRS above the 80th percentile showed a higher OR (6.48). The combined PRS + MRS model demonstrated the best discriminative ability (AUC = 0.753), while the interaction model did not enhance performance (AUC = 0.752). Results Adding PRS and MRS to ten baseline covariates (age, sex and eight cardiometabolic variables) slightly increased bootstrap-validated sensitivity/specificity, from 0.819/0.878 to 0.827/0.885. MRS increased step-wise from non-diabetic low-risk to diabetic high-risk clusters, whereas PRS primarily distinguished diabetic from non-diabetic status. Exploratory pathway analysis of MRS-mapped genes identified enrichment for phosphatase signalling and oxidative-stress pathways implicated in diabetic cardiomyopathy. Conclusions This study provides proof-of-concept evidence that integrating T2D-derived polygenic and methylation risk scores with detailed clinical phenotyping captures distinct biological information related to subclinical myocardial dysfunction. MRS showed stronger association, including after adjustment for clinical covariates and in sensitivity analyses restricted to individuals with T2D, whereas the PRS added limited discriminatory value within the T2D population. These findings are exploratory and require validation in larger independent cohorts.

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Journal
Cardiovascular Diabetology
Published
2026-08-17
DOI
https://doi.org/10.1186/s12933-026-03329-3
Primary Topic
Genetic Associations and Epidemiology
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article
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article

Unmasking subclinical cardiac dysfunction in type 2 diabetes through genetic and epigenetic profiling

Bianca Riccardi, Étienne Audureau, Josefina Lascano-Maillard, Cyrille Bergerot et al.
Cardiovascular Diabetology
Genetic Associations and Epidemiology
article

Unmasking subclinical cardiac dysfunction in type 2 diabetes through genetic and epigenetic profiling

Bianca Riccardi, Étienne Audureau, Josefina Lascano-Maillard, Cyrille Bergerot, Khadija Sana Hafeez, Yvan Devaux, Elisabetta Casalone, Simonetta Guarrera, Flora Sam, Florian Sohler, Bénédicte Gaborit, Paul Balfanz, Robin Liechti, Alessandra Allione, Cecilia Di Primio, Alessia Russo, Genevieve Derumeaux, Miriam Rosselli, Rebecca Filomena, S. R. B. Heymans, Mark Ibberson, Rui Wang-Sattler, Chim C. Lang, Javier Bermejo, Olivier Martin, Bart Jacobs, Giuseppe Matullo
article en

Abstract

Abstract Background Diabetic Cardiomyopathy (DiabCM) develops in patients with Type-2-Diabetes Mellitus (T2D) and is characterized by cardiac dysfunction independent of ischemic heart disease or systemic hypertension. Its underlying mechanisms remain poorly defined with likely genetic and non-genetic mechanisms including epigenetic modifications. Combining T2D-derived polygenic risk scores (PRS) and methylation risk scores (MRS) with key clinical characteristics may aid risk stratification for myocardial dysfunction among patients with T2D. Methods We analyzed 173 deeply phenotyped participants from the CARDIATEAM discovery study, grouping them by the severity of myocardial dysfunction determined by echocardiography. Both PRS and MRS show significantly different distribution between severity groups ( p -value = 0.02 and 1.29e-05, respectively) with significant odds ratios (ORs) at ≥ 80th and ≥ 90th percentiles: PRS (2.23 [95%CI 1.03–4.92] and 2.82 [95%CI 1.02–8.34]), and MRS (4.52 [95%CI 2.01–10.83] and 3.49 [95%CI 1.22–11.02]) respectively. Combining individuals with PRS and MRS above the 80th percentile showed a higher OR (6.48). The combined PRS + MRS model demonstrated the best discriminative ability (AUC = 0.753), while the interaction model did not enhance performance (AUC = 0.752). Results Adding PRS and MRS to ten baseline covariates (age, sex and eight cardiometabolic variables) slightly increased bootstrap-validated sensitivity/specificity, from 0.819/0.878 to 0.827/0.885. MRS increased step-wise from non-diabetic low-risk to diabetic high-risk clusters, whereas PRS primarily distinguished diabetic from non-diabetic status. Exploratory pathway analysis of MRS-mapped genes identified enrichment for phosphatase signalling and oxidative-stress pathways implicated in diabetic cardiomyopathy. Conclusions This study provides proof-of-concept evidence that integrating T2D-derived polygenic and methylation risk scores with detailed clinical phenotyping captures distinct biological information related to subclinical myocardial dysfunction. MRS showed stronger association, including after adjustment for clinical covariates and in sensitivity analyses restricted to individuals with T2D, whereas the PRS added limited discriminatory value within the T2D population. These findings are exploratory and require validation in larger independent cohorts.

Cardiovascular Diabetology
Boston University (US), SIB Swiss Institute of Bioinformatics (CH), Inserm (FR), Eli Lilly (United States) (US), University of Dundee (GB), Université Paris-Est Créteil (FR), Aix-Marseille Université (FR), Hospital General Universitario Gregorio Marañón (ES), Helmholtz Zentrum München (DE), Maastricht University (NL), Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT), Assistance Publique Hôpitaux de Marseille (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), VIB-KU Leuven Center for Cancer Biology (BE), Assistance Publique – Hôpitaux de Paris (FR), Hospices Civils de Lyon (FR), Luxembourg Institute of Health (LU), Italian institute for Genomic Medicine (IT), Hôpitaux Universitaires Henri-Mondor (FR), ERN GUARD-Heart (NL), Institut Mondor de Recherche Biomédicale (FR), University of Turin (IT), Bayer (Germany) (DE), RWTH Aachen University (DE), KU Leuven (BE)
Reduced inequalities
Openalex Percentile: Top 9%
Genetic Associations and Epidemiology
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