Plasma extrachromosomal circular DNA is a pathophysiological hallmark of short‐term intensive insulin therapy for type 2 diabetes

Abstract

BackgroundExtrachromosomal circular DNA (eccDNA) has emerged as a promising biomarker for disease diagnosis and prognosis prediction. However, its role in type 2 diabetes remains unexplored.ObjectiveTo investigate the characteristics and dynamics of circulating eccDNAs in newly diagnosed type 2 diabetes mellitus (T2DM) patients undergoing short‐term intensive insulin therapy (SIIT), a highly effective treatment for inducing long‐term glycemic remission.MethodsWe conducted Circle‐Seq analysis on plasma samples from 35 T2DM patients at three time points: pre‐SIIT, post‐SIIT, and 1‐year post‐SIIT. Our analysis encompassed the characterization of eccDNA features, including GC content, eccDNA length distribution, genomic distribution, and the genes in eccDNAs.ResultsFollowing SIIT, we observed an increase in plasma eccDNA load, suggesting metabolic alterations during therapy. Notably, a correlation was identified between eccDNA profiles and glycemia in T2DM, both quantitatively and genetically. Our analysis also revealed the frequent presence of metabolism‐related genes within T2DM plasma eccDNAs, some of which spanned gene exons and/or fractions.ConclusionThis study represents the first report of cell‐free eccDNA in T2DM and underscores a compelling association between cell‐free eccDNA and profound glycemic changes. These findings highlight the potential of eccDNAs as crucial players in the context of T2DM and glycemic control.

Cell-Free Genic Extrachromosomal Circular DNA Profiles of DNase Knockouts Associated with Systemic Lupus Erythematosus and Relation with Common Fragile Sites

“…For example, Yu et al [32] provided a direct relationship between the loss of double minutes (DMs) and a decrease in ovarian cancer malignancy, showing that the drug gemcitabine decreases the number of DMs. Xu et al [3] investigated the characteristics and dynamics of circulating eccDNAs in type 2 diabetes mellitus (T2DM) patients undergoing short-term intensive insulin therapy (SIIT) for inducing long-term glycemic remission. Genic cf-eccDNA profiles before and after treatment offer the possibility to follow the effect of drugs not only at the level of number of eccDNAs but also at the more precise level of actual genes and CFSs that are affected by the drug.…”

“…Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker in cancer [2] and other diseases such as diabetes [3], inflammatory bowel disease [4], and amyotrophic lateral sclerosis [5], among others. EccDNA features such as changes in the number of the eccDNAs, changes in the length frequency distributions of the eccDNA or differential abundance of eccDNA from certain genes [3,6,7] have been considered as biomarkers.…”

“…Cell-free (cf) extrachromosomal circular DNA (eccDNA) has a potential clinical application as a biomarker in cancer [2] and other diseases such as diabetes [3], inflammatory bowel disease [4], and amyotrophic lateral sclerosis [5], among others. EccDNA features such as changes in the number of the eccDNAs, changes in the length frequency distributions of the eccDNA or differential abundance of eccDNA from certain genes [3,6,7] have been considered as biomarkers. Previous work studying the relationship of nucleases and eccDNA characteristics in plasma using knockout (KO) mouse models with a deficiency in Dnase1 or Dnase1l3 found that cf-eccDNA Dnase1l3 −/− exhibited larger size distributions than in wild type mice [8].…”

Extrachromosomal circular DNA landscape of breast cancer with lymph node metastasis

“…Seven major classes of genomic elements, namely, 3 0 -UTR, 5 0 -UTR, CpG island, exon, Gene2KbD, Gene2KbU, and intron, were utilized to align eccDNAs based on their junction sites. 27 2.8 | Differential eccDNA-associated genes Differential eccDNA-associated genes (eccGenes) analysis was performed to identify circles that were significantly altered between primary tumors and matched LNM. The DESeq2 package was used to perform differential eccGenes analysis and p < .05 was applied to define the set of differential eccGenes.…”