Skip to main content
Dryad logo

Data from: Uncovering genetic mechanisms of hypertension through multi-omic analysis of the kidney

Citation

Eales, James (2020), Data from: Uncovering genetic mechanisms of hypertension through multi-omic analysis of the kidney, Dryad, Dataset, https://doi.org/10.5061/dryad.15dv41nvx

Abstract

The kidney is an organ of key relevance to blood pressure (BP) regulation, hypertension and antihypertensive treatment. However, genetically mediated renal mechanisms underlying susceptibility to hypertension remain poorly understood. We integrated genotype, gene expression, alternative splicing and DNA methylation profiles of up to 430 human kidneys to characterise the effects of BP index variants from genome-wide association studies (GWAS) on renal transcriptome and epigenome. We uncovered kidney targets for 479 (58.3%) BP-GWAS variants and paired 49 BP-GWAS kidney genes with 210 licensed drugs. Our colocalisation and Mendelian randomisation analyses identified 179 unique kidney genes with evidence of putatively causal effects on BP. Through Mendelian randomisation we uncovered effects of BP on renal outcomes commonly affecting hypertensive patients. Collectively, our studies identified genetic variants, kidney genes, molecular mechanisms and biological pathways of key relevance to the genetic regulation of BP and inherited susceptibility to hypertension.

 

Methods

Please see the Methods section of the associated publication for full details.

Gene expression and alternative splicing data are derived from poly-A RNA-sequencing.

DNA methylation data are derived from the Illumina Infinium HumanMethylation450 BeadChip.

All data sets are the normalised values used for QTL testing with FastQTL.

All values have been quantile normalised and transformed by the rank-based inverse normal method.

 

Usage Notes

Please see the Methods section of the associated publication for full details.

Gene expression

Gene IDs map to ensembl v83

Values are normalised and transformed log2(TPM+1) expression at the gene-level, calculated by Kallisto.

Alternative splicing

Intron excision isoform IDs map to GRCh38 coordinates.

Values are normalised and transformed intron usage ratios calculated by Leafcutter.

DNA Methylation

CpG IDs map to the Illumina IDs supplied in the Infinium HumanMethylation450 BeadChip manifest file.

Values are normalised and transformed M-values calculated by the R package minfi

Funding

British Heart Foundation, Award: PG/17/35/33001

British Heart Foundation, Award: PG/19/16/34270

Kidney Research UK, Award: RP_017_20180302