Dna methylation-based assessment of cell composition in human pancreas and islets

Zeina Drawshy, Daniel Neiman, Ori Fridlich, Ayelet Peretz, Judith Magenheim, Andrea V. Rozo, Nicolai M. Doliba, Doris A. Stoffers, Klaus H. Kaestner, Desmond A. Schatz, Clive Wasserfall, Martha Campbell-Thompson, James Shapiro, Tommy Kaplan, Ruth Shemer, Benjamin Glaser, Agnes Klochendler, Yuval Dor

Research output: Contribution to journalArticlepeer-review


Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of b-cells. A major limitation of thesemethods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNAmethylationmarkers for determining the fraction of specific cell types in human islet and pancreas specimens.We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to b-cell DNA revealed similar b-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed b-cell fraction within the normal range, suggesting a significant contribution of b-cell dysfunction. In T2D pancreata, we observed increased a-cell fraction and normal b-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

Original languageAmerican English
Pages (from-to)554-564
Number of pages11
Issue number4
StatePublished - Apr 2024

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism


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