Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control

Abstract

69Serum urate is the end-product of purine metabolism. Elevated serum urate is causal of 70 gout and a predictor of renal disease, cardiovascular disease and other metabolic 71 conditions. Genome-wide association studies (GWAS) have reported dozens of loci 72 associated with serum urate control, however there has been little progress in 73 understanding the molecular basis of the associated loci. Here we employed trans-74 ancestral meta-analysis using data from European and East Asian populations to 75 identify ten new loci for serum urate levels. Genome-wide colocalization with cis-76 expression quantitative trait loci (eQTL) identified a further five new loci. By cis-and 77 trans-eQTL colocalization analysis we identified 24 and 20 genes respectively where 78 the causal eQTL variant has a high likelihood that it is shared with the serum urate-79 associated locus. One new locus identified was SLC22A9 that encodes organic anion 80 transporter 7 (OAT7). We demonstrate that OAT7 is a very weak urate-butyrate 81 exchanger. Newly implicated genes identified in the eQTL analysis include those 82 encoding proteins that make up the dystrophin complex, a scaffold for signaling 83 proteins and transporters at the cell membrane; MLXIP that, with the previously 84 identified MLXIPL, is a transcription factor that may regulate serum urate via the 85 pentose-phosphate pathway; and MRPS7 and IDH2 that encode proteins necessary for 86 mitochondrial function. Trans-ancestral functional fine-mapping identified six loci 87 (RREB1, INHBC, HLF, UBE2Q2, SFMBT1, HNF4G) with colocalized eQTL that 88 contained putative causal SNPs (posterior probability of causality > 0.8). This 89 systematic analysis of serum urate GWAS loci has identified candidate causal genes at 90 19 loci and a network of previously unidentified genes likely involved in control of 91 serum urate levels, further illuminating the molecular mechanisms of urate control. 92 93 Author Summary 94 High serum urate is a prerequisite for gout and a risk factor for metabolic disease. 95Previous GWAS have identified numerous loci that are associated with serum urate 96 control, however, only a small handful of these loci have known molecular 97 consequences. The majority of loci are within the non-coding regions of the genome 98 and therefore it is difficult to ascertain how these variants might influence serum urate 99 levels without tangible links to gene expression and / or protein function. We have 100 applied a novel bioinformatic pipeline where we combined population-specific GWAS 101 4 data with gene expression and genome connectivity information to identify putative 102 causal genes for serum urate associated loci. Overall, we identified 15 novel serum 103 urate loci and show that these loci along with previously identified loci are linked to 104 the expression of 44 genes. We show that some of the variants within these loci have 105 strong predicted regulatory function which can be further tested in functional analyses. 106 This study expands on previous GWAS by ident...

Pleiotropic effect of ABCG2 in gout: involvement in serum urate levels and progression from hyperuricemia to gout

“…Thus, it is reasonable to hypothesise that rs10011796 marks an effect that influences gene expression. This is consistent with the presence of an expression QTL (regulatory) effect independent of rs2231142 in the ABCG2 urate GWAS signal (47). The rs10011796 C-allele (that associates with reduced serum urate and risk of gout) does associate with reduced ABCG2 and increased PPM1K-DT (a long non-coding RNA 100kb downstream of ABCG2 ) expression (www.gtex.org).…”

“…The molecular mechanism driving the non-additive interaction between ABCG2 SNPs rs2231142 and rs10011796 is unclear. Given that rs10011796 is a noncoding intronic variant outside any known Encode regulatory motif features (www.encodeproject.org), it is likely that rs10011796 is in linkage disequilibrium with the causal variant, rather than the causal variant itself, although other intronic variants in ABCG2 have been associated with ABCG2 expression (46, 47). The majority of common phenotype associations identified by GWAS are expression quantitative trait loci (48), influencing gene expression and transcript stability, and these variants can therefore modify the penetrance of coding variants (49).…”

Pleiotropic effect of ABCG2 in gout: involvement in serum urate levels and progression from hyperuricemia to gout

“…Thus, it is reasonable to hypothesise that rs10011796 marks an effect that influences gene expression. This is consistent with the presence of an expression QTL (regulatory) effect independent of rs2231142 in the ABCG2 urate GWAS signal(47). The rs10011796 C-allele (that associates with reduced serum urate and risk of gout) does associate with reduced ABCG2 and increased PPM1K-DT (a long non-coding RNA 100 kb downstream of ABCG2) expression (www.gtex.org).…”

“…Future studies that investigate and compare IL-1β production in response to MSU and autophagy in cells with the different 141Q and 141K alleles would be illuminating.The molecular mechanism driving the non-additive interaction between ABCG2 SNPs rs2231142 and rs10011796 is unclear. Given that rs10011796 is a noncoding intronic variant outside any known Encode regulatory motif features (www.encodeproject.org), it is likely that rs10011796 is in linkage disequilibrium with the causal variant, rather than the causal variant itself, although other intronic variants in ABCG2 have been associated with ABCG2 expression(46,47). The majority of common phenotype associations identified by GWAS are expression quantitative trait loci(48), influencing gene expression and transcript stability, and these variants can therefore modify the penetrance of coding variants(49).…”

Population-specific Interaction of the TRIM46 / MUC1 Locus With Cigarette Smoking May Influence the Risk of Gout

“…Causal candidate genes have been identi ed at the TRIM46 (rs11264341) locus by colocalising the GWAS signal with cis expression quantitative trait locus (eQTL) analysis [45]. These include SHE, MUC1, GBAP1, and FAM189B, but not TRIM46 itself or PKLR which were previously suggested to be causal candidates by the less accurate Gene Relationships Across Implicated Loci (GRAIL) tool [3,46].…”