Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments

Abstract

The functional interpretation of GWAS remains challenging due to cell-type dependent influences of genetic variants.Here, we generated comprehensive maps of expression quantitative trait loci (eQTL) for 659 microdissected human kidney samples and identified cell-type eQTLs by mapping interactions between cell type abundance and genotype. Separately, we generated single cell open chromatin maps (by snATAC-seq) for human kidney samples. We highlight critical enrichment of proximal tubules in kidney function and endothelial cells and distal tubule segments in blood pressure by partitioning heritability using stratified LD-score regression to integrate GWAS with scRNA-seq and snATAC-seq data. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of the most commonly used antihypertensive and renal protective drugs and identifies drug repurposing opportunities for kidney disease.One Sentence SummaryWe define causal cell types, genes and mechanism for kidney dysfunction.

Transcriptome-wide association analysis identifies DACH1 as a kidney disease risk gene that contributes to fibrosis

“…Most loci contain dozens, sometimes hundreds, of SNPs that pass the genome-wide significance for disease association. Recently, epigenetic information, such as functional annotation of the noncoding genomic regions, has been successfully used to prioritize GWAS variants (15). Functionally important GWAS variants are more likely to be on a cell-type-specific regulatory region; therefore, the intersection of GWAS loci with open chromatin regions identified by transposase insertion (ATAC-Seq) or histone ChIP (ChIP-Seq) can be powerful for causal variant prioritization.…”

“…Functionally important GWAS variants are more likely to be on a cell-type-specific regulatory region; therefore, the intersection of GWAS loci with open chromatin regions identified by transposase insertion (ATAC-Seq) or histone ChIP (ChIP-Seq) can be powerful for causal variant prioritization. Regulatory regions are cell-type specific; therefore, new single-cell analytical methods open new avenues for causal variant prioritization that were missed in prior bulk experiments (15).…”

Kidney pathology alters cell-clustering in single cell RNA sequencing

“…As such, scRNA-Seq in whole kidney compartments (cortex or interstitium) or cell collections not enriched for glomerular cells may result in the loss of podocytes and other glomerular cells during clustering due to dilution from massive volumes of tubule cells 11 . The technique of microdissection requires highly trained personnel to complete the process in a short time; however, cell dissociation is still required 1 .…”

“…Due to the heterogeneity of cell types in the kidney, researchers have proposed and performed microdissection-based expression quantitative trait loci (eQTL) analyses on human kidney cell fractions[1]. More recently, single-cell RNA sequencing (scRNA-Seq) has been recognized as a cutting-edge technique in the classification of cell-specific gene expression profiles, particularly important to determine cell-specific mechanisms underlying kidney disease.…”

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

“…Interactions with score ≥ 5 were considered significant. We queried chromatin accessibility in kidney single-nucleus ATAC-sequencing (snATACseq) data available at https://susztaklab.com/human_kidney/igv/ (accessed 24 June 2021) 36 . Detailed gene expression in kidney single cell RNA sequencing (scRNAseq) data was queried in the Human Diabetic Kidney data set (23,980 nuclei) by Wilson et al 37 , accessed through http://humphreyslab.com/SingleCell.…”