Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci

Abstract

Background DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach. Methods The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses. Results We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development. Conclusions We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations

“…Specifically, FORGE2 outputs: a web-based interactive table, a web-based dimple ( http://dimplejs.org ) d3 interactive graphic using rCharts, a tab-separated values (TSV) file, a PDF file, R code source files for generating the charts and the table, as well as a compressed file with the input data. FORGE2 provides output similar to FORGE [ 10 ], eFORGE v1.0, and eFORGE v2.0 [ 35 , 36 , 40 ], and additional information can be found in those references as well as in a recently published EWAS where eFORGE analysis was applied [ 41 ].…”

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

“…Indeed, large-scale analysis of DNA methylation in blood cells revealed that methylation of several CpG sites is associated with the magnitude of BP elevation 71,72 and kidney function. 73 The findings by Kato et al 74 further show that at least some SNPs associated with BP in GWASs operate as methylation-associated SNPs in blood. Many epigenetic patterns are tissue and cell type specific; hence, the availability of renal tissue banks is critical to identifying epigenetic patterns clustering with kidney disease, BP, and hypertension.…”

Diversity in EWAS: current state, challenges, and solutions

“…Studies have reported notable population-specific DNAm differences [ 1 , 4 ], showing that population diversity is critical to the interpretation of EWAS. However, the extent of population diversity in current DNAm data has not received sufficient attention.…”

“…Our prior work illustrated this issue in EWAS by applying an integrative epigenomic analysis method, eFORGE, on four DNAm meta-analyses of estimated glomerular filtration rate (eGFR): 1) European Americans (EA), 2) African Americans (AA), 3) Hispanic/Latinos (H/L), and 4) a combination of EA, AA, and H/L (transethnic analysis) [ 4 ]. Despite having a similar number of epigenome-wide associated loci when comparing EA and AA, enrichments in kidney regulatory elements—critical for a phenotype such as eGFR, where the kidney is a key player—were only detected for top EA CpGs, with much weaker results for other analyses [ 4 , 10 ]. These findings may be the result of a lack of epigenetic data for non-EA populations, leading to a gap in the functional interpretation of study loci.…”