Data from: Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes
Skol, Andrew et al. (2020), Data from: Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes, Dryad, Dataset, https://doi.org/10.5061/dryad.zkh18938j
We determined differential gene expression in response to high glucose in lymphoblastoid cell lines derived from matched individuals with type 1 diabetes with and without retinopathy. Those genes exhibiting the largest difference in glucose response were assessed for association to diabetic retinopathy in a genome-wide association study meta-analysis. Expression Quantitative Trait Loci (eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the eQTLs from the glucose response genes among small association p-values and identified FLCN as a susceptibility gene for diabetic retinopathy. Expression of FLCN in response to glucose was greater in individuals with diabetic retinopathy. Independent cohorts of individuals with diabetes revealed an association of FLCN eQTLs to diabetic retinopathy. Mendelian randomization confirmed a direct positive effect of increased FLCN expression on retinopathy. Integrating genetic association with gene expression implicated FLCN as a disease gene for diabetic retinopathy.
GWAS for EDIC and Gokind was processed using Plink 1.9. Data was downloaded from DbGap. Data for GTEX EQTLs was downloaded from their website: https://gtexportal.org/home/.
Data for GWAS and GTEX was merged in R versions 3.4.0. Meta analysis was performed using http://csg.sph.umich.edu/abecasis/metal/.