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Identification of novel genes for glucose metabolism based upon expression pattern in human islets and effect on insulin secretion and glycemia.

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Author

Summary, in English

Normal glucose homeostasis is characterized by appropriate insulin secretion and low HbA1c. Gene expression signatures associated with these two phenotypes could be essential for islet function and patho-physiology of type 2 diabetes (T2D). Herein, we employed a novel approach to identify candidate genes involved in T2D by correlating islet microarray gene expression data (78 donors) with insulin secretion and HbA1c level. Expression of 649 genes (p<0.05) was correlated with insulin secretion and HbA1c. Of them, 5 genes (GLR1A, PPP1R1A, PLCDXD3, FAM105A and ENO2) correlated positively with insulin secretion/negatively with HbA1c and one gene (GNG5) correlated negatively with insulin secretion/positively with HbA1c were followed up. The 5 positively correlated genes have lower expression levels in diabetic islets, whereas, GNG5 expression is higher. Exposure of human islets to high glucose for 24 hrs resulted in up-regulation of GNG5 and PPP1R1A expression, while expression of ENO2 and GLRA1 was down-regulated. No effect was seen on the expression of FAM105A and PLCXD3. siRNA silencing in INS-1 832/13 cells showed reduction in insulin secretion for PPP1R1A, PLXCD3, ENO2, FAM105A and GNG5 but not GLRA1. Although, no SNP in these gene loci passed the genome-wide significance for association with T2D in DIAGRAM+ database, four SNPs influenced gene expression in cis in human islets. In conclusion, we identified and confirmed PPP1R1A, FAM105A, ENO2, PLCDX3 and GNG5 as potential regulators of islet function. We provide a list of candidate genes as a resource for exploring their role in the pathogenesis of T2D.

Publishing year

2015

Language

English

Pages

1945-1955

Publication/Series

Human Molecular Genetics

Volume

24

Issue

7

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Medical Genetics

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology

ISBN/ISSN/Other

  • ISSN: 0964-6906