Cadzow, M. | Search bioRxiv

bioRxiv2020

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

BackgroundThe ABCG2 Q141K (rs2231142) and rs10011796 variants associate with hyperuricaemia (HU). The effect size of ABCG2 rs2231142 on urate is [~]60% that of SLC2A9, yet the effect size on gout is greater. We tested the hypothesis that ABCG2 plays a role in the progression from HU to gout by testing for association of ABCG2 rs2231142 and rs10011796 with gout using HU controls. MethodsWe analysed 1,699 European gout cases and 14,350 normourciemic (NU) and HU controls, and 912 New Zealand (NZ) Polynesian (divided into Eastern and Western Polynesian) gout cases and 696 controls. Association testing was performed using logistic and linear regression with multivariate adjusting for confounding variables. ResultsIn Europeans and Polynesians, the ABCG2 141K (T) allele was associated with gout using HU controls (OR=1.85, P=3.8E-21 and ORmeta =1.85, P=1.3E-03, respectively). There was evidence for an effect of 141K in determining HU in European (OR=1.56, P=1.7E-18) but not in Polynesian (ORmeta=1.49, P=0.057). For SLC2A9 rs11942223, the T allele associated with gout in the presence of HU in European (OR=1.37, P=4.7E-06), however significantly weaker than ABCG2 rs2231142 141K (PHet=0.0023). In Western Polynesian and European, there was epistatic interaction between ABCG2 rs2231142 and the genetically-independent rs10011796. Combining the presence of the 141K allele with the rs10011796 CC-genotype increased gout risk, in the presence of HU, 21.5-fold in Western Polynesian (P=0.009) and 2.6-fold in European (P=9.9E-06). The 141K allele positively associated with flare frequency in Polynesian (Pmeta =2.5E-03). ConclusionThese data are consistent with a role for ABCG2 141K in gout in the presence of established HU.

genetics↗

bioRxiv2019

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

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

genetics↗