Background Acute hyperinsulinemia may directly affect blood cells. In this study a hyperinsulinemic-euglycemic clamp (HEC) and multiomics methods were used to explore the epigenetic regulation by hyperinsulinemia in blood cells.
Methods To assess short-term changes in DNA methylation (within 2 hours), blood samples were collected from five non-diabetic adults before and after HEC. mRNA sequencing (mRNA-seq) and targeted bisulfite sequencing (methyl-seq) were performed. Using mRNA-seq, 697 differentially expressed genes (DEGs) were identified, and methyl-seq was used to select those with changes in promoter or gene body methylation. In vitro validation study was also performed in THP1 and 3T3–L1 cells after acute insulin treatment.
Results Among the 697 DEGs, 119 (henceforth, ‘methyl-DEGs’) showed methylation changes. Of these 697 DEGs, 45 (‘publictrait- DEGs’) were associated with pathways such as oxidative stress, insulin signaling, inflammation, and carbohydrate metabolism. Interaction networks between methyl-DEGs and public-trait-DEGs revealed that six genes (B3GALNT1, ESR1, FGF4, PER1, PRKAR1B, and TNFSF4) were affected by DNA methylation and linked to insulin response or diabetes. In response to acute insulin treatment, ESR1, PRKAR1B, PER1, and B3GALNT1 expression decreased in THP1 cells. Similar trends were seen in 3T3–L1 cells, except B3GALNT1. PER1 displayed consistent and significant downregulation across the clamp study and the two cell lines, indicating it as a key circadian-responsive gene under acute hyperinsulinemia.
Conclusion These results provide epigenetic evidence for the role of DNA methylation in CpG regions and gene bodies in hyperinsulinemia- mediated regulation of gene expression in blood cells, which warrants further studies in relation to diabetes-related pathophysiology.
Background Although the prevalence of diabetic kidney disease (DKD) is increasing, reliable biomarkers for its early detection are scarce. This study aimed to evaluate the association of adenosine and succinate levels and their related pathways, including hyaluronic acid (HA) synthesis, with DKD.
Methods We examined 235 participants and categorized them into three groups: healthy controls; those with diabetes but without DKD; and those with DKD, which was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. We compared the concentrations of urinary adenosine, succinate, and HA and the serum levels of cluster of differentiation 39 (CD39) and CD73, which are involved in adenosine generation, among the groups with DKD or albuminuria. In addition, we performed multiple logistic regression analysis to evaluate the independent association of DKD or albuminuria with the metabolites after adjusting for risk factors. We also showed the association of these metabolites with eGFR measured several years before enrollment. This study was registered with the Clinical Research Information Service (https://cris.nih.go.kr; Registration number: KCT0003573).
Results Urinary succinate and serum CD39 levels were higher in the DKD group than in the control and non-DKD groups. Correlation analysis consistently linked urinary succinate and serum CD39 concentrations with eGFR, albuminuria, and ΔeGFR, which was calculated retrospectively. However, among the various metabolites studied, only urinary succinate was identified as an independent indicator of DKD and albuminuria.
Conclusion Among several potential metabolites, only urinary succinate was independently associated with DKD. These findings hold promise for clinical application in the management of DKD.
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