Update: the role of epigenetics in the metabolic memory of diabetic complications - Chen, Zhuo; Malek, Vajir; Natarajan, Rama (American journal of physiology. Renal physiology, 2024)
Diabetes, a chronic disease characterized by hyperglycemia, is associated with significantly accelerated complications, including diabetic kidney disease (DKD), which increases morbidity and mortality. Hyperglycemia and other diabetes-related environmental factors such as overnutrition, sedentary lifestyles, and hyperlipidemia can induce epigenetic changes. Working alone or with genetic factors, these epigenetic changes that occur without alterations in the underlying DNA sequence, can alter the expression of pathophysiological genes and impair functions of associated target cells/organs, leading to diabetic complications like DKD. Notably, some hyperglycemia-induced epigenetic changes persist in target cells/tissues even after glucose normalization, leading to sustained complications despite glycemic control, so-called metabolic memory. Emerging evidence from in vitro and in vivo animal models and clinical trials with subjects with diabetes identified clear associations between metabolic memory and epigenetic changes including DNA methylation, histone modifications, chromatin structure, and noncoding RNAs at key loci. Targeting such persistent epigenetic changes and/or molecules regulated by them can serve as valuable opportunities to attenuate, or erase metabolic memory, which is crucial to prevent complication progression. Here, we review these cell/tissue-specific epigenetic changes identified to-date as related to diabetic complications, especially DKD, and the current status on targeting epigenetics to tackle metabolic memory. We also discuss limitations in current studies, including the need for more (epi)genome-wide studies, integrative analysis using multiple epigenetic marks and Omics datasets, and mechanistic evaluation of metabolic memory. Considering the tremendous technological advances in epigenomics, genetics, sequencing, and availability of genomic datasets from clinical cohorts, this field is likely to see considerable progress in the upcoming years.