Open AccessNovel diabetes gene discovery through comprehensive characterization and integrative analysis of longitudinal gene expression changes
Author(s) -
HungHsin Chen,
Lauren E. Petty,
Kari E. North,
Joseph B. McCormick,
Susan P. FisherHoch,
Eric R. Gamazon,
Jennifer E. Below
Publication year - 2022
Publication title -
human molecular genetics online/human molecular genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.811
H-Index - 276
eISSN - 1460-2083
pISSN - 0964-6906
DOI - 10.1093/hmg/ddac039
Subject(s) - type 2 diabetes , biology , gene , genetics , diabetes mellitus , disease , gene regulatory network , gene expression , enhancer , biobank , computational biology , bioinformatics , medicine , endocrinology
Type 2 diabetes is a complex, systemic disease affected by both genetic and environmental factors. Previous research has identified genetic variants associated with type 2 diabetes risk; however, gene regulatory changes underlying progression to metabolic dysfunction are still largely unknown. We investigated RNA expression changes that occur during diabetes progression using a two-stage approach. In our discovery stage, we compared changes in gene expression using two longitudinally collected blood samples from subjects whose fasting blood glucose transitioned to a level consistent with type 2 diabetes diagnosis between the time points against those who did not with a novel analytical network approach. Our network methodology identified 17 networks, one of which was significantly associated with transition status. This 822-gene network harbors many genes novel to the type 2 diabetes literature but is also significantly enriched for genes previously associated with type 2 diabetes. In the validation stage, we queried associations of genetically determined expression with diabetes-related traits in a large biobank with linked electronic health records. We observed a significant enrichment of genes in our identified network whose genetically determined expression is associated with type 2 diabetes and other metabolic traits and validated 31 genes that are not near previously reported type 2 diabetes loci. Finally, we provide additional functional support, which suggests that the genes in this network are regulated by enhancers that operate in human pancreatic islet cells. We present an innovative and systematic approach that identified and validated key gene expression changes associated with type 2 diabetes transition status and demonstrated their translational relevance in a large clinical resource.