Genome-Wide Association Studies of CKD and Related Traits

Abstract

The past few years have seen major advances in genome-wide association studies (GWAS) of CKD and kidney function-related traits in several areas: increases in sample size from >100,000 to >1 million, enabling the discovery of >250 associated genetic loci that are highly reproducible; the inclusion of participants not only of European but also of non-European ancestries; and the use of advanced computational methods to integrate additional genomic and other unbiased, high-dimensional data to characterize the underlying genetic architecture and prioritize potentially causal genes and variants. Together with other large-scale biobank and genetic association studies of complex traits, these GWAS of kidney function-related traits have also provided novel insight into the relationship of kidney function to other diseases with respect to their genetic associations, genetic correlation, and directional relationships. A number of studies also included functional experiments using model organisms or cell lines to validate prioritized potentially causal genes and/or variants. In this review article, we will summarize these recent GWAS of CKD and kidney function-related traits, explain approaches for downstream characterization of associated genetic loci and the value of such computational follow-up analyses, and discuss related challenges along with potential solutions to ultimately enable improved treatment and prevention of kidney diseases through genetics.

Keywords: Biological Specimen Banks; Cell Line; Chronic; Follow-Up Studies; Genetic Association Studies; Genetic Loci; Genome; Genome-Wide Association Study; Genomics; Kidney Genomics Series; Multifactorial Inheritance; Renal Insufficiency; Sample Size; chronic kidney disease; genetic renal disease.

Figure 1.

Methods and objectives for the downstream characterization of findings from large-scale meta-analyses of GWAS. (A) Tissue and/or cell type enrichment analyses can identify the organs or cell types that affect the trait and inform on its genetic architecture. (B) Colocalization of gene association patterns between the trait and gene expression can reveal the potential causal gene in a locus and its tissues of action. (C) Fine-mapping and functional annotation focus on narrowing down the set of potential causal variants in a locus. (D) Genetic correlation analysis can reveal the shared genetic basis between traits, whereas Mendelian randomization aims to assess their causal relation using genetic information. (E) Polygenic risk scores can provide an estimate of disease risk. When used in the context of a phenome-wide association study, it can discover new genetic relations between diseases. (F) Experimental follow-up studies provide biologic evidence for causal genes and variants.

Figure 2.

Studies of continuous kidney traits in the general population deliver insights that are relevant to clinical phenotypes. (A) Genetic variants associated with lower eGFR are also associated with higher odds of acute and CKD. (B) Genetic variants associated with higher UACR are also associated with higher odds of microalbuminuria. (C) Genetic variants associated with higher serum urate are also associated with higher odds of gout, with a 100-fold difference across the range of a genetic risk score. GRS, genetic risk score; OR, odds ratio; UACR, urinary albumin-to-creatinine ratio. *Logistic regression two-sided P<0.05; **P<5 × 10^-10; ***P<5 × 10^-100.

Figure 3.

Necessity of using additional kidney function markers for understanding genetic associations with eGFR and with the UACR. (A) BUN, (B) Cystatin C, and (C) both components of the ratio. Cys, cystatin C; UKBB, UK Biobank.

Figure 4.

Concept of colocalization of genetic associations to prioritize genes underlying the association with UACR. The genetic associations with UACR in a chromosome 11 region with several genes (A) colocalized with gene expression of OAF (but none of the other genes) in tubulointerstitial kidney portions (B), as well as with plasma protein levels of OAF (but none of the other gene products) (C). The region of interest on chromosome 11 contains several genes of interest, but colocalization was only observed with transcript and protein levels of one of the genes, OAF. This implicates OAF as the gene in the region that underlies the association signal and a regulatory variant acting through altered gene expression as the most likely mechanism.

Figure 5.

Vignette illustrates how genome-wide association studies (GWAS) followed by experimental validation and characterization can reveal previously unknown and important biological mechanisms for potential therapeutic use. Genome-wide significant signals at ABCG2 in a GWAS of serum urate levels were followed up with experimental studies that revealed the previously unknown function of ABCG2 as an urate transporter and the GWAS index SNP, rs2231142, as the causal variant. Each copy of the T allele of rs2231142 is associated with 0.2 mg/dl higher serum urate levels and two-fold higher odds of gout. ABCG2 therefore represents a potential therapeutic target for lowering urate levels and preventing gout. (A) Regional association plot from Woodward et al. 2008, with genomic location on the x axis and –log₁₀(P value) on the y axis. (B) Transport assays using radioactively labeled urate in Xenopus oocytes: over a wide range of extracellular urate concentrations (x axis), oocytes expressing wild-type ABCG2 (red) showed significantly lower intracellular accumulation of urate (y axis) than water-injected control oocytes (blue) or a loss-of-function mutation of ABCG2 (black). This indicates that the function of ABCG2 is the active export of urate out of oocytes. (C) Immunofluorescence of polarized porcine renal epithelial cells (LLC-PK1) shows expression of ABCG2 at the apical brush border membrane. Together with urate accumulation in the cells after application of an ABCG2 inhibitor, these experiments establish that ABCG2 is a secretory urate transporter in the proximal tubule. (D) The ABCG2 Q141K variant encoded by rs2231142 results in reduced urate transport as indicated by higher intracellular urate accumulation, establishing rs2231142 as the causal variant. (E) Conceptual model of the role of ABCG2 in urate handling in the kidney in the context of other urate transport proteins. WT, wild type.