Literature DB >> 28575649

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

Yi-An Ko1, Huiguang Yi1, Chengxiang Qiu1, Shizheng Huang1, Jihwan Park1, Nora Ledo1, Anna Köttgen2, Hongzhe Li3, Daniel J Rader4, Michael A Pack5, Christopher D Brown4, Katalin Susztak6.   

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.
Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CKD; GWAS; eQTL; gene network; gene regulation; kidney

Mesh:

Substances:

Year:  2017        PMID: 28575649      PMCID: PMC5473735          DOI: 10.1016/j.ajhg.2017.05.004

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


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