A catalog of genetic loci associated with kidney function from analyses of a million individuals

Abstract

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.

Fig. 1 |. Trans-ancestry GWAS meta-analysis identifies 308 loci associated with eGFR.

Circos plot. The red band corresponds to −log₁₀(P) for association with eGFR (y axis truncated at 30), by chromosomal position. The blue line indicates genome-wide significance (P=5×10⁻⁸). Black gene labels indicate new loci, while blue labels indicate known loci. Non-replicating loci are colored in gray (new) or light blue (known). The green band corresponds to measures of heterogeneity related to the index SNPs associated with eGFR. Dot sizes are proportional to I² or ancestry-related heterogeneity (P_anc-het). The blue band corresponds to −log₁₀(P) for association with CKD (y axis truncated at 20), by chromosomal position. The red line indicates genome-wide significance (P = 5×10⁻⁸). Radial lines mark regions with P_anc-het <1.6×10⁻⁴ = 0.05/308 or I²>25%. Inset, effects of all 308 index SNPs on log(eGFR)by minor allele frequency, colored by the associated OR for CKD (red scale for OR≤1, blue scale for OR>1). The largest effects on CKD were observed for rs77924615 at UMOD-PDILT (0R = 0.81, 95% confidence interval (CI) = 0.80, 0.83), rs187355703 at HOXD8 (0R = 0.82, 95% CI = 0.77, 0.87) and rs10254101 at PRKAG2 (0R = 1.11, 95% CI =1.09, 1.11). Triangles highlight SNPs that were associated with CKD (one-sided P<0.05).

Fig. 2 |. Generalizability with respect to other populations and other kidney function markers.

a, Measures of heterogeneity for the 308 eGFR-associated index SNPs. Each variant’s heterogeneity quantified as I² from the trans-ancestry meta-analysis (y axis) is compared to the ancestry-related heterogeneity from meta-regression (−log₁₀(P_anc-het); x axis). Histograms summarize the distribution of the heterogeneity measures on both axes. SNPs with ancestry-related heterogeneity (P_anc-het<1.6×10⁻⁴ = 0.05/308) are marked in blue and labeled; SNPs with I²>50% are labeled. b, Comparison of genetic effect estimates between CKDGen Consortium discovery (x axis) and MVP replication (y axis). Blue font indicates one-sided P<0.05 in the MVP. Error bars correspond to 95% CIs. The dashed line corresponds to the line of best fit. Pearson’s correlation coefficient r = 0.92 (95% CI = 0.90, 0.94). c, The magnitude of genetic effects on eGFR (x axis) as compared to BUN (y axis) for the 264 replicated eGFR-associated index SNPs. Color coding reflects evidence of kidney function relevance (Methods), which is coded as ‘likely’ (blue), ‘inconclusive’ (gray) or ‘unlikely’ (green). Error bars correspond to 95% CIs. The dashed line corresponds to the line of best fit. Pearson’s correlation coefficient r=−0.65 (95% CI = −0.72, −0.58). d, Association of lower genetically predicted eGFR based on a GRS of 147 SNPs likely to be most relevant for kidney function with ICD-10-based clinical diagnoses for 452,264 individuals from the UK Biobank. Asthma was included as a negative control. Results are displayed as the OR and 95% CI per 10% lower GRS-predicted eGFR (Methods).

Fig. 3 |. Human orthologs of genes with renal phenotypes in genetically manipulated mice are enriched for association signals with eGFR.

a-c, Signals in candidate genes identified on the basis of the mouse phenotypes of abnormal GFR (a), abnormal kidney physiology (b) and abnormal kidney morphology (c). The y axis shows −log₁₀ (P) for association with eGFR in the trans-ancestry meta-analysis for the variant with the lowest P value in each candidate gene. The dashed line corresponds to genome-wide significance (P = 5×10⁻⁸), and the solid gray line corresponds to the experiment-wide significance threshold for each nested candidate gene analysis. Orange, genome-wide significance; red, experiment-wide but not genome-wide significance; blue, no significantly associated SNPs. Genes are labeled if they reached experiment- but not genome-wide significance; black font indicates genes not mapping to loci reported in the main analysis. Enrichment P values correspond to the observed number of genes with association signals below the experiment-wide threshold against the number expected on the basis of the complementary cumulative binomial distribution (Methods).

Fig. 4 |. credible set size plotted against variant posterior probability for 3,655 sNPs in 253 99% credible sets according to variant annotation.

a, Exonic variants. SNPs are marked by triangles, with triangle size proportional to CADD score. Red triangles indicate missense SNPs mapping to small credible sets (≤5 SNPs) or to sets containing SNPs with high individual PP of driving the association signal (>50%). b, SNPs with regulatory potential. Symbol color corresponds to regulatory potential as derived from DNase I hypersensitivity analysis in target tissues (Methods). Annotation was restricted to variants with PP>1%; SNPs with PP≥90% contained in credible sets with ≤10 SNPs are labeled. Data are plotted as credible set size (x axis) against variant PP(y axis). Blue and green color coding for gene and SNP labels refers to kidney-function relevance and has the same meaning as in Fig. 2.

Fig. 5 |. colocalization of eGFR association signals with gene expression in kidney tissues.

All eGFR loci were tested for colocalization with all eQTLs where the eQTL cis window overlapped (±100 kb) the sentinel genetic variant. Genes with at least one positive colocalization (PP of one common causal variant (H₄)≥80%) in a kidney tissue are shown with the respective sentinel SNP (y axis). Colocalizations across all tissues (x axis) are illustrated as dots, where dot size corresponds to the PP of colocalization. Negative colocalizations (PP for H₄<80%) are gray, while positive colocalizations are colored according to the predicted change in expression relative to the allele associated with lower eGFR.

Fig. 6 |. Colocalization of independent eGFR association signals at the UMOD-PDILT locus with urinary uromodulin concentrations (UUCR) supports UMOD as the effector gene.

Association plots show association −log₁₀(P value) (y axis) plotted against chromosomal position (x axis). a, Approximate conditional analyses among European-ancestry individuals support the presence of two independent eGFR-associated signals. b, The association signal for uromodulin (UUCR) levels is similar; r² = 0.93 between rs34882080 and rs34262842. c,d, Colocalization of association with eGFR (top) and uromodulin (UUCR) levels (bottom) for the independent regions centered on UMOD (c) and PDILT (d) supports a shared underlying variant in both regions with high PP.