Gene expression profiles of beta-cell enriched tissue obtained by Laser Capture Microdissection from subjects with type 2 diabetes

Changes in gene expression in pancreatic beta-cells from type 2 diabetes could provide insights into their abnormal insulin secretion and beta-cell turnover. The laser capture microdissection technique was used to acquire beta-cells from pancreatic tissue sections obtained from type 2 diabetic (T2D) and non-diabetic controls. We found that 4% of analyzed transcripts were differentially expressed between the two groups at the lower confidence bound cutoff of 1.2, and, among the differentially expressed transcripts, 62% were up-regulated and 38% down-regulated in samples of T2D subjects compared to non-diabetic controls. We observed: 1) changes in expression of genes linked to glucotoxicity, in particular, up-regulation of LDHA and PCK1, and down-regulation of GPD2, ME1 and ACLY; 2) evidence of oxidative stress, documented by up-regulation of metallothionein genes; 3) few changes in the major genes associated with cell cycle, apoptosis or endoplasmic reticulum stress; 4) differential expression of genes associated with pancreatic regeneration, most notably up-regulation of members of the regenerating islet gene (REG) family and metalloproteinase 7; and 5) differential expression of some genes found in genome wide association studies to be related to T2D (IGF2BP2, TSPAN8, and HNF1B were up-regulated, while JAZF1 and SLC30A8 were down-regulated). In conclusion, this study has identified many novel changes in pancreatic beta-cell gene expression that enhance the understanding of the pathogenesis of T2D. The gene expression profile of beta-cells obtained from cadaver pancreases of 10 control and 10 type 2 diabetic subjects was evaluated. Beta-cells were acquired from pancreatic tissue sections using the laser capture microdissection technique. RNA was extracted, amplified, biotinylated and hybridized to GeneChip Human X3P Array (Affymetrix). Array data were normalized and analysis was performed using the DNA-Chip Analyzer software.