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DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Authors :
Drawshy, Zeina
Neiman, Daniel
Fridlich, Ori
Peretz, Ayelet
Magenheim, Judith
Rozo, Andrea V.
Doliba, Nicolai M.
Stoffers, Doris A.
Kaestner, Klaus H.
Schatz, Desmond A.
Wasserfall, Clive
Campbell-Thompson, Martha
Shapiro, James
Kaplan, Tommy
Shemer, Ruth
Glaser, Benjamin
Klochendler, Agnes
Dor, Yuval
Source :
Diabetes; Apr2024, Vol. 73 Issue 4, p554-564, 11p
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00121797
Volume :
73
Issue :
4
Database :
Complementary Index
Journal :
Diabetes
Publication Type :
Academic Journal
Accession number :
176240068
Full Text :
https://doi.org/10.2337/db23-0704