Abstract
Increased serum uric acid (SUA) levels cause gout and are associated with multiple diseases, including chronic kidney disease. Previous genome-wide association studies (GWAS) have identified more than 180 loci that contribute to SUA levels. Here, we investigated genetic determinants of SUA level in the Korean population. We conducted a GWAS for SUA in 6,881 Korean individuals, calculated polygenic risk scores (PRSs) for common variants, and validated the association of low-frequency variants and PRS with SUA levels in 3,194 individuals. We identified two low-frequency and six common independent variants associated with SUA. Despite the overall similar effect sizes of variants in Korean and European populations, the proportion of variance for SUA levels explained by the variants was greater in the Korean population. A rare, nonsense variant SLC22A12 p.W258X showed the most significant association with reduced SUA levels, and PRSs of common variants associated with SUA levels were significant in multiple Korean cohorts. Interestingly, an East Asian-specific missense variant (rs671) in ALDH2 displayed a significant association on chromosome 12 with the SUA level. Further genetic epidemiological studies on SUA are needed in ethnically diverse cohorts to investigate rare or low-frequency variants and determine the influence of genetic and environmental factors on SUA.
Highlights
Uric acid is the final product of purine metabolism in humans[1]
Our study evaluates the contribution of both low-frequency and common variants to serum uric acid (SUA) levels by using an Haplotype Reference Consortium (HRC)-based imputation
Our results demonstrate the benefits of using a large imputation panel such as the HRC reference panel for discovery, and characterisation of common and low-frequency variants contributing to SUA levels in the general population
Summary
Uric acid is the final product of purine metabolism in humans[1]. Uric acid is produced primarily in the liver, and 70% of daily uric acid excretion occurs via the kidney[1]. We analysed a total of 6,129,701 SNPs in the discovery phase to identify the association with SUA levels in individuals using linear regression and discovered eight independent SNPs (two low-frequency and six common) that reached the threshold of statistical significance (Table 2).
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