Circulating unmethylated CHTOP and INS DNA fragments provide evidence of possible islet cell death in youth with obesity and diabetes

Background Identification of islet beta cell death prior to the onset of type 1 diabetes (T1D) or type 2 diabetes (T2D) might allow for interventions to protect beta cells and reduce diabetes risk. Circulating unmethylated DNA fragments arising from the humanINSgene have been proposed as biomarkers of beta cell death, but this gene alone may not be sufficiently specific to report beta cell death. Results To identify new candidate genes whose CpG sites may show greater specificity for beta cells, we performed unbiased DNA methylation analysis using the Infinium HumanMethylation 450 array on 64 human islet preparations and 27 non-islet human tissues. For verification of array results, bisulfite DNA sequencing of human beta cells and 11 non-beta cell tissues was performed on 5 of the top 10 CpG sites that were found to be differentially methylated. We identified theCHTOPgene as a candidate whose CpGs show a greater frequency of unmethylation in human islets. A digital PCR strategy was used to determine the methylation pattern ofCHTOPandINSCpG sites in primary human tissues. Although bothINSandCHTOPcontained unmethylated CpG sites in non-islet tissues, they occurred in a non-overlapping pattern. Based on Naive Bayes classifier analysis, the two genes together report 100% specificity for islet damage. Digital PCR was then performed on cell-free DNA from serum from human subjects. Compared to healthy controls (N= 10), differentially methylatedCHTOPandINSlevels were higher in youth with new onset T1D (N= 43) and, unexpectedly, in healthy autoantibody-negative youth who have first-degree relatives with T1D (N= 23). When tested in lean (N= 32) and obese (N= 118) youth, increased levels of unmethylatedINSandCHTOPwere observed in obese individuals. Conclusion Our data suggest that concurrent measurement of circulating unmethylatedINSandCHTOPhas the potential to detect islet death in youth at risk for both T1D and T2D. Our data also support the use of multiple parameters to increase the confidence of detecting islet damage in individuals at risk for developing diabetes.