Institute of Rheumatology, Tokyo Women's Medical University, Tokyo, Japan.
J Rheumatol. 2013 Aug;40(8):1374-8. doi: 10.3899/jrheum.121244. Epub 2013 Jun 1.
To validate the association between genetic polymorphisms and gout in Japanese patients, and to investigate the cumulative effects of multiple genetic factors on the development of gout.
Subjects were 153 Japanese male patients with gout and 532 male controls. The genotypes of 11 polymorphisms in the 10 genes that have been indicated to be associated with serum uric acid levels or gout were determined. The cumulative effects of the genetic polymorphisms were investigated using a weighted genotype risk score (wGRS) based on the number of risk alleles and the OR for gout. A model to discriminate between patients with gout and controls was constructed by incorporating the wGRS and clinical factors. C statistics method was applied to evaluate the capability of the model to discriminate gout patients from controls.
Seven polymorphisms were shown to be associated with gout. The mean wGRS was significantly higher in patients with gout (15.2 ± 2.01) compared to controls (13.4 ± 2.10; p < 0.0001). The C statistic for the model using genetic information alone was 0.72, while the C statistic was 0.81 for the full model that incorporated all genetic and clinical factors.
Accumulation of multiple genetic factors is associated with the development of gout. A prediction model for gout that incorporates genetic and clinical factors may be useful for identifying individuals who are at risk of gout.
验证遗传多态性与日本痛风患者之间的关联，并探讨多种遗传因素对痛风发展的累积效应。
研究对象为 153 名日本男性痛风患者和 532 名男性对照者。确定了与血清尿酸水平或痛风相关的 10 个基因中的 11 个基因多态性的基因型。基于风险等位基因的数量和痛风的比值比（OR），使用加权基因型风险评分（wGRS）来研究遗传多态性的累积效应。通过纳入 wGRS 和临床因素构建了一个区分痛风患者和对照组的模型。应用 C 统计量法评估模型区分痛风患者和对照组的能力。
有 7 个多态性与痛风相关。痛风患者的平均 wGRS（15.2 ± 2.01）明显高于对照组（13.4 ± 2.10；p < 0.0001）。仅使用遗传信息的模型的 C 统计量为 0.72，而纳入所有遗传和临床因素的全模型的 C 统计量为 0.81。
多种遗传因素的累积与痛风的发生有关。纳入遗传和临床因素的痛风预测模型可能有助于识别易患痛风的个体。
