Genetic-Variation-Driven Gene-Expression Changes Highlight Genes with Important Functions for Kidney Disease

Abstract

Chronic kidney disease (CKD) is a complex gene-environmental disease affecting close to 10% of the US population. Genome-wide association studies (GWASs) have identified sequence variants, localized to non-coding genomic regions, associated with kidney function. Despite these robust observations, the mechanism by which variants lead to CKD remains a critical unanswered question. Expression quantitative trait loci (eQTL) analysis is a method to identify genetic variation associated with gene expression changes in specific tissue types. We hypothesized that an integrative analysis combining CKD GWAS and kidney eQTL results can identify candidate genes for CKD. We performed eQTL analysis by correlating genotype with RNA-seq-based gene expression levels in 96 human kidney samples. Applying stringent statistical criteria, we detected 1,886 genes whose expression differs with the sequence variants. Using direct overlap and Bayesian methods, we identified new potential target genes for CKD. With respect to one of the target genes, lysosomal beta A mannosidase (MANBA), we observed that genetic variants associated with MANBA expression in the kidney showed statistically significant colocalization with variants identified in CKD GWASs, indicating that MANBA is a potential target gene for CKD. The expression of MANBA was significantly lower in kidneys of subjects with risk alleles. Suppressing manba expression in zebrafish resulted in renal tubule defects and pericardial edema, phenotypes typically induced by kidney dysfunction. Our analysis shows that gene-expression changes driven by genetic variation in the kidney can highlight potential new target genes for CKD development.

An eQTL landscape of kidney tissue in human nephrotic syndrome

“…Transcriptome wide association study with IgA Nephropathy GWAS Previous studies have shown that risk alleles from genome-wide association studies (GWAS) are enriched for eQTLs 40 , and others have used eQTL data to pinpoint genes whose expression was regulated by GWAS alleles 16 . Here, we integrated our GLOM and TI eQTL data with summary statistics from the largest published GWAS of glomerular disease, in IgA Nephropathy 41 (IgAN), and performed a transcriptome wide association study (TWAS) using an approach adapted from the PrediXcan and MetaXcan methods 42; 43 .…”

“…The most comprehensive kidney eQTL study thus far discovered kidney eQTLs using unaffected portions of 96 nephrectomy samples from The Cancer Genome Atlas 16 . The investigators integrated these eQTL with risk loci for chronic kidney disease (CKD) to establish links between these risk alleles and molecular mechansims 16 . A limitation of this study was that bulk renal cortex was used for association, which is known to be 80% proximal tubule cells.…”

Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis

“…Gene sets with more than 25% overlap were collapsed into a single set for construction of the network diagram, as previously done 61 . Colocalization analysis of the kidney association results with GTEx V7 22 , NephQTL 21 , and Ko et al 20 eQTL data was performed using the R package coloc 62 . Priors for p1, p2, and p12 within the coloc analysis were set to 1x10 -4 , 1x10 -4 , and 1x10 -6 , respectively.…”

Genome-wide association study of diabetic kidney disease highlights biology involved in renal basement membrane collagen

“…We interrogated gene expression datasets in relevant tissues to determine whether our top signals underlie expression quantitative trait loci (eQTL). We first analyzed genotype and RNAseq gene expression data from 96 whole human kidney cortical samples 42 and microdissected human kidney samples (121 tubule and 119 glomerular samples 43 from subjects of European descent without any evidence of renal disease (Figure S8). No findings in this data set achieved significance after correction for multiple testing.…”