ArticleGeroScience2024
Associations between epigenetic aging and diabetes mellitus in a Swedish longitudinal study.
Article in GeroScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- HIV associated epigenetic trends and chronic diseases: insights into the hidden burden of chronic infection.Clinical epigenetics · 2026Review
- Association of systemic immune-inflammation index (SII) with epigenetic age acceleration in adults: insights from NHANES.Epigenetics · 2025Article
- Novel approaches and applications in identifying DNA methylation markers of cardio-kidney-metabolic disease.Epigenomics · 2025Review
- EpInflammAge: Epigenetic-Inflammatory Clock for Disease-Associated Biological Aging Based on Deep Learning.International journal of molecular sciences · 2025Article
- Functional Foods in Modern Nutrition Science: Mechanisms, Evidence, and Public Health Implications.Nutrients · 2025Review
- Association of DNA methylation epigenetic markers with all-cause mortality and cardiovascular disease-related mortality in diabetic population: a machine learning-based retrospective cohort study.Diabetology & metabolic syndrome · 2025Article
- Association of Epigenetic Markers of Aging With Prevalent and Incident Type 2 Diabetes.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- MicroRNAs in diabetes mellitus.Journal of diabetes and metabolic disorders · 2025Review
- Type-2 diabetes epigenetic biomarkers: present status and future directions for global and Indigenous health.Frontiers in molecular biosciences · 2025Review
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Authors and funding
7 authors.
Funding
Abstract
Diabetes mellitus type 2 (T2D) is associated with accelerated biological aging and the increased risk of onset of other age-related diseases. Epigenetic changes in DNA methylation levels have been found to serve as reliable biomarkers for biological aging. This study explores the relationship between various epigenetic biomarkers of aging and diabetes risk using longitudinal data. Data from the Swedish Adoption/Twin Study of Aging (SATSA) was collected from 1984 to 2014 and included 536 individuals with at least one epigenetic measurement. The following epigenetic biomarkers of aging were employed: DNAm PAI-1, DNAmTL, DunedinPACE, PCHorvath1, PCHorvath2, PCHannum, PCPhenoAge, and PCGrimAge. Firstly, longitudinal analysis of biomarker trajectories was done. Secondly, linear correlations between the biomarkers and time to diabetes were studied within individuals developing diabetes. Thirdly, Cox proportional hazards (PH) models were used to assess the associations between these biomarkers and time of diabetes diagnosis, with adjustments for chronological age, sex, education, smoking, blood glucose, and BMI. The longitudinal trajectories of the biomarkers revealed differences between individuals with and without diabetes. Smoothened average curves for DunedinPACE and DNAm PAI-1 were higher for individuals with diabetes around the age 60-70, compared to controls. Likewise, DunedinPACE and DNAm PAI-1 were higher closer to diabetes onset. However, no significant associations were found between the epigenetic biomarkers of aging and risk of diabetes in Cox PH models. Our findings suggest the potential value of developing epigenetic biomarkers specifically tailored to T2D, should we wish to model and explore the potential for predicting the disease.
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