Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.

ABSTRACT:

Aims/hypothesis

Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.

Methods

We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene,

SUBMITTER: Sandholm N 

PROVIDER: S-EPMC9345823 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature