Bayesian mixed model analysis uncovered 21 risk loci for chronic kidney disease in boxer dogs

Abstract

Chronic kidney disease (CKD) affects 10% of the human population, with only a small fraction genetically defined. CKD is also common in dogs and has been diagnosed in nearly all breeds, but its genetic basis remains unclear. Here, we performed a Bayesian mixed model genome-wide association analysis for canine CKD in a boxer population of 117 canine cases and 137 controls, and identified 21 genetic regions associated with the disease. At the top markers from each CKD region, the cases carried an average of 20.2 risk alleles, significantly higher than controls (15.6 risk alleles). An ANOVA test showed that the 21 CKD regions together explained 57% of CKD phenotypic variation in the population. Based on whole genome sequencing data of 20 boxers, we identified 5,206 variants in LD with the top 50 BayesR markers. Following comparative analysis with human regulatory data, 17 putative regulatory variants were identified and tested with electrophoretic mobility shift assays. In total four variants, three intronic variants from the MAGI2 and GALNT18 genes, and one variant in an intergenic region on chr28, showed alternative binding ability for the risk and protective alleles in kidney cell lines. Many genes from the 21 CKD regions, RELN, MAGI2, FGFR2 and others, have been implicated in human kidney development or disease. The results from this study provide new information that may enlighten the etiology of CKD in both dogs and humans.

Fig 1. Association analysis of chronic kidney disease (CKD).

(A) Manhattan plot of absolute SNP effect from BayesR analysis. The top 50 markers (green dots) with the highest effect were selected as candidates. 21 CKD regions were identified when merging linkage disequilibrium blocks of candidate markers. Genes relevant to kidney development or human disease were exhibited near the CKD region. (B) Risk allele frequency at the top marker from each of 21 CKD regions in cases (red) and controls (blue). Based on coordinates, appendix (1), (2), and (3) were added for the markers from the same chromosome. (C) Distribution of risk allele load for the cases (red) and controls (blue). On average, the cases carried 20.2 risk alleles, which is 4.6 higher than the controls (grey dash lines indicated the average load for cases and controls).

Fig 2. Chronic kidney disease (CKD) region on chr18 (chr18:13.9–19.1 Mb).

(A) Eighteen Bayesian candidate markers (green dots) were observed in this region, and are present in two linkage disequilibrium (LD) blocks. (B) Annotated genes were identified around the CKD region. One selection signal of dog domestication and a ~500 Kb reported genomic duplicates were observed in this region. 2,064 imputed variants were found within the same LD of Bayesian candidate markers. (C) 76 imputed SNPs with phyloP score > 1 were lifted to human genome (hg38), and intersected with the regulatory elements from the candidate cis-Regulatory Elements (cCRE; red bars) and GeneHancer databases (blue bars), as well as the hypersensitivity (HS) signal from 95 cell lines (the height of the bar indicated the number of cell lines with the HS signal). (D) Eight putative regulatory SNPs (C3-C10) from the CKD region were tested with electrophoretic mobility shift assays (EMSAs). SNPs C8 and C9 showed alternative binding ability between the risk and protective alleles in HEK293 cell line.

Fig 3. Chronic kidney disease (CKD) region on chr28 (chr28:30.8–31.4 Mb).

Three candidate markers (green dots) from Bayesian analysis were found in this CKD region with the highest effect of 0.002. One selection signal was found nearby the candidate markers. Most of the imputed variants were located in the intergenic region between the WDR11 and FGFR2 genes in the same TAD.

Fig 4. Chronic kidney disease (CKD) region on chr21 (chr21:34.7–35.2 Mb).

Four Bayesian candidate markers (green dots) were identified in this 510 Kb CKD region. Within the LD of the candidate markers, two putative regulatory SNPs, C12 and C13, were identified from the downstream region and intron of GALNT18 gene. EMSA validation illustrated allele-specific protein-nucleic acid binding of C13 in both HEK293 and MDCK cell lines.

Fig 5. Pictures of boxer kidney with chronic kidney disease (CKD).

(A) A non-decapsulated kidney from an 8-month-old female boxer dog with CKD revealing a coarse nodular irregular cortical surface; (B) sagittal section of the kidney revealing an irregularly pale and thinned cortex; (C) LM revealing cortical interstitial fibrosis with tubular atrophy and multifocal infiltration of mononuclear inflammatory cells, (D) glomerulocystic atrophy (HE x10) and (E) hyperplasia of medullary collecting duct epithelium consistent with so-called “atypical tubuli” or “adenomatoid change” (HE x20).