System network analysis of genomics and transcriptomics data identified type 1 diabetes-associated pathway and genes.

Genes and Immunity
Jun-Min LuHong-Wen Deng

Abstract

Genome-wide association studies (GWASs) have discovered >50 risk loci for type 1 diabetes (T1D). However, those variations only have modest effects on the genetic risk of T1D. In recent years, accumulated studies have suggested that gene-gene interactions might explain part of the missing heritability. The purpose of our research was to identify potential and novel risk genes for T1D by systematically considering the gene-gene interactions through network analyses. We carried out a novel system network analysis of summary GWAS statistics jointly with transcriptomic gene expression data to identify some of the missing heritability for T1D using weighted gene co-expression network analysis (WGCNA). Using WGCNA, seven modules for 1852 nominally significant (P ≤ 0.05) GWAS genes were identified by analyzing microarray data for gene expression profile. One module (tagged as green module) showed significant association (P ≤ 0.05) between the module eigengenes and the trait. This module also displayed a high correlation (r = 0.45, P ≤ 0.05) between module membership (MM) and gene significant (GS), which indicated that the green module of co-expressed genes is of significant biological importance for T1D status. By further describing t...Continue Reading

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Citations

Jul 20, 2019·International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society·Renato Moretti-MarquesKathleen M Schmeler
Nov 7, 2019·Current Diabetes Reports·Marina BakayHakon Hakonarson

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Datasets Mentioned

BETA
GSE55100

Software Mentioned

Versatile Gene - based Association Study - 2 ( VEGAS - 2 )
VisANT
WGCNA package
ImmunoChip
R
VEGAS
Affy package
WGCNA

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