Academic Rheumatology, University of Nottingham, Nottingham, UK
Nottingham Biomedical Research Centre, NIHR, Nottingham, UK.
Ann Rheum Dis. 2021 Sep;80(9):1220-1226. doi: 10.1136/annrheumdis-2020-219796. Epub 2021 Apr 8.
To perform a genome-wide association study (GWAS) of gout cases versus asymptomatic hyperuricaemia (AH) controls, and gout cases versus normouricaemia controls, and to generate a polygenic risk score (PRS) to determine gout-case versus AH-control status.
Gout cases and AH controls (serum urate (SU) ≥6.0 mg/dL) from the UK Biobank were divided into discovery (4934 cases, 56 948 controls) and replication (2115 cases, 24 406 controls) cohorts. GWAS was conducted and PRS generated using summary statistics in discovery cohort as the base dataset and the replication cohort as the target dataset. The predictive ability of the model was evaluated. GWAS were performed to identify variants associated with gout compared with normouricaemic controls using SU <6.0 mg/dL and <7.0 mg/dL thresholds, respectively.
Thirteen independent single nucleotide polymorphisms (SNPs) in ABCG2, SLC2A9, SLC22A11, GCKR, MEPE, PPM1K-DT, LOC105377323 and ADH1B reached genome-wide significance and replicated as predictors of AH to gout transition. Twelve of 13 associations were novel for this transition, and rs1229984 (ADH1B) was identified as GWAS locus for gout for the first time. The best PRS model was generated from association data of 17 SNPs; and had predictive ability of 58.5% that increased to 69.2% on including demographic factors. Two novel SNPs rs760077(MTX1) and rs3800307(PRSS16) achieved GWAS significance for association with gout compared with normouricaemic controls using both SU thresholds.
The association of urate transporters with gout supports the central role of hyperuricaemia in its pathogenesis. Larger GWAS are required to identify if variants in inflammatory pathways contribute to progression from AH to gout.
对痛风病例与无症状高尿酸血症（AH）对照、痛风病例与正常尿酸对照进行全基因组关联研究（GWAS），并生成多基因风险评分（PRS），以确定痛风病例与 AH 对照的状态。
英国生物库中的痛风病例和 AH 对照（血清尿酸（SU）≥6.0mg/dL）分为发现（4934 例，56948 例对照）和复制（2115 例，24406 例对照）队列。在发现队列中使用汇总统计数据进行 GWAS，并生成 PRS，将其作为基础数据集，将复制队列作为目标数据集。评估模型的预测能力。使用 SU<6.0mg/dL 和<7.0mg/dL 阈值，分别进行 GWAS 以鉴定与痛风相比与正常尿酸对照相关的变异。
在 ABCG2、SLC2A9、SLC22A11、GCKR、MEPE、PPM1K-DT、LOC105377323 和 ADH1B 中发现了 13 个独立的单核苷酸多态性（SNP），达到了全基因组显著水平，并作为 AH 向痛风转变的预测因子得到了复制。这 13 个关联中有 12 个是该转变的新关联，并且首次确定 rs1229984（ADH1B）为痛风的 GWAS 基因座。从 17 个 SNP 的关联数据中生成了最佳 PRS 模型；并具有 58.5%的预测能力，包括人口统计学因素后增加到 69.2%。使用两个 SU 阈值，两个新的 SNP rs760077（MTX1）和 rs3800307（PRSS16）在与正常尿酸对照相比时达到了与痛风的 GWAS 显著关联。
尿酸转运体与痛风的关联支持高尿酸血症在其发病机制中的核心作用。需要更大的 GWAS 来确定炎症途径中的变异是否有助于从 AH 向痛风的进展。
