Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments.
Xin ShengYuting GuanZiyuan MaJunnan WuHongbo LiuChengxiang QiuSteven VitaleZhen MiaoMatthew J SeasockMatthew PalmerMyung K ShinKevin L DuffinSteven S PullenTodd L EdwardsJacklyn N HellwegeAdriana M HungMingyao LiBenjamin F VoightThomas M CoffmanChristopher D BrownKatalin SusztákPublished in: Nature genetics (2021)
The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease.
Keyphrases
- genome wide
- endothelial cells
- single cell
- blood pressure
- dna methylation
- genome wide association
- high resolution
- rna seq
- copy number
- high throughput
- hypertensive patients
- high glucose
- high throughput sequencing
- poor prognosis
- gene expression
- high density
- induced pluripotent stem cells
- pluripotent stem cells
- stem cells
- vascular endothelial growth factor
- machine learning
- adipose tissue
- dna damage
- electronic health record
- cell therapy
- drug induced
- skeletal muscle
- genome wide association study
- metabolic syndrome
- data analysis
- human health
- mesenchymal stem cells
- hiv infected