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Human DNA methylation biomarkers in diabetic complications: from association to clinical translation
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DOI：10.1080/17501911.2026.2678921.png)
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Abstract
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Diabetic complications are a major contributor to morbidity and mortality, yet accurately identifying individuals at highest risk remains a persistent clinical challenge. Although established clinical risk factors underpin current prediction models, their ability to forecast complication onset and progression remains limited. Long-term follow-up of landmark clinical trials revealed the phenomenon of metabolic memory, whereby early glycemic exposure leaves a lasting imprint on future complication risk, even after glycemic differences have converged. Epigenetic mechanisms are compelling mediators of this effect, as they encode stable changes in gene regulation without altering the underlying DNA sequence.
Over the past decade, human studies have linked epigenetic modifications, particularly DNA methylation, to diabetic complications, yet translation into clinically useful biomarkers has been slow. This Perspective examines the current landscape of human epigenetic biomarker research, highlighting both biological insights and methodological constraints. We discuss key technological platforms, including Infiniummethylation arrays and sequencing-based approaches such as bisulfites sequencing and enzymatic methyl-sequencing (EM-seq). While earlyarray-based studies provided proof of concept, next-generation sequencing approaches offer substantially greater discovery potential.
We conclude by outlining priorities for the next decade, emphasizing longitudinal cohorts, multi-omics integration, and predictive frameworks capable oftransforming epigenetic signals into meaningful clinical tools.
Keywords:
Diabetic complications
DNA methylation
metabolic memory
diabetic kidney disease
cardiovascular disease
gestational diabetes
cell-free DNA
precision medicine
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