rs10788884 - SLC5A9
Magnitude 2.2 · 4 studies on file
Reported associations
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A genome-wide association analysis reveals new pathogenic pathways in gout. - Nature genetics (2024) · Major TJ, Takei R, Matsuo H, Leask MP, Sumpter NA, Topless RK, Shirai Y, Wang W, Cadzow MJ, Phipps-Green AJ, Li Z, Ji A, Merriman ME, Morice E, Kelley EE, Wei WH, McCormick SPA, Bixley MJ, Reynolds RJ, Saag KG, Fadason T, Golovina E, O'Sullivan JM, Stamp LK, Dalbeth N, Abhishek A, Doherty M, Roddy E, Jacobsson LTH, Kapetanovic MC, Melander O, Andrés M, Pérez-Ruiz F, Torres RJ, Radstake T, Jansen TL, Janssen M, Joosten LAB, Liu R, Gaal OI, Crişan TO, Rednic S, Kurreeman F, Huizinga TWJ, Toes R, Lioté F, Richette P, Bardin T, Ea HK, Pascart T, McCarthy GM, Helbert L, Stibůrková B, Tausche AK, Uhlig T, Vitart V, Boutin TS, Hayward C, Riches PL, Ralston SH, Campbell A, MacDonald TM, Nakayama A, Takada T, Nakatochi M, Shimizu S, Kawamura Y, Toyoda Y, Nakaoka H, Yamamoto K, Matsuo K, Shinomiya N, Ichida K, Lee C, Bradbury LA, Brown MA, Robinson PC, Buchanan RRC, Hill CL, Lester S, Smith MD, Rischmueller M, Choi HK, Stahl EA, Miner JN, Solomon DH, Cui J, Giacomini KM, Brackman DJ, Jorgenson EM, Liu H, Susztak K, Shringarpure S, So A, Okada Y, Li C, Shi Y, Merriman TR · PubMed 39406924
Gout is a chronic disease that is caused by an innate immune response to deposited monosodium urate crystals in the setting of hyperuricemia. Here, we provide insights into the molecular mechanism of the poorly understood inflammatory component of gout from a genome-wide association study (GWAS) of 2.6 million people, including 120,295 people with prevalent gout. We detected 377 loci and 410 genetically independent signals (149 previously unreported loci in urate and gout). An additional 65 loci with signals in urate (from a GWAS of 630,117 individuals) but not gout were identified. A prioritization scheme identified candidate genes in the inflammatory process of gout, including genes involved in epigenetic remodeling, cell osmolarity and regulation of NOD-like receptor protein 3 (NLRP3) i
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A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286
ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%
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Genetic studies of paired metabolomes reveal enzymatic and transport processes at the interface of plasma and urine - Unknown journal (n.d.) · Unknown authors · PubMed 37277652
ABSTRACT: The kidneys operate at the interface of plasma and urine by clearing molecular waste products while retaining valuable solutes. Genetic studies of paired plasma and urine metabolomes may identify underlying processes. We conducted genome-wide studies of 1,916 plasma and urine metabolites and detected 1,299 significant associations. Associations with 40% of implicated metabolites would have been missed by studying plasma alone. We detected urine-specific findings that provide information about metabolite reabsorption in the kidney, such as aquaporin (AQP)-7-mediated glycerol transport, and different metabolomic footprints of kidney-expressed proteins in plasma and urine that are consistent with their localization and function, including the transporters NaDC3 (SLC13A3) and ASBT (S
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Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function - Unknown journal (n.d.) · Unknown authors · PubMed 39746953
ABSTRACT: Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10−10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. S
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