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MR-PheWAS:利用 UK Biobank 中的遗传工具探索 SUA 水平对多种疾病结局的因果效应。

MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank.

机构信息

Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.

Centre for Population Health Sciences, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.

出版信息

Ann Rheum Dis. 2018 Jul;77(7):1039-1047. doi: 10.1136/annrheumdis-2017-212534. Epub 2018 Feb 6.

Abstract

OBJECTIVES

We aimed to investigate the role of serum uric acid (SUA) level in a broad spectrum of disease outcomes using data for 120 091 individuals from UK Biobank.

METHODS

We performed a phenome-wide association study (PheWAS) to identify disease outcomes associated with SUA genetic risk loci. We then implemented conventional Mendelianrandomisation (MR) analysis to investigate the causal relevance between SUA level and disease outcomes identified from PheWAS. We next applied MR Egger analysis to detect and account for potential pleiotropy, which conventional MR analysis might mistake for causality, and used the HEIDI (heterogeneity in dependent instruments) test to remove cross-phenotype associations that were likely due to genetic linkage.

RESULTS

Our PheWAS identified 25 disease groups/outcomes associated with SUA genetic risk loci after multiple testing correction (P<8.57e-05). Our conventional MR analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. Our analysis highlighted a locus () that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy.

CONCLUSIONS

Elevated SUA level is convincing to cause gout and inflammatory polyarthropathies, and might act as a marker for the wider range of diseases with which it associates. Our findings support further investigation on the clinical relevance of SUA level with cardiovascular, metabolic, autoimmune and respiratory diseases.

摘要

目的

我们旨在利用英国生物库中 120091 个人的数据,通过全基因组关联研究(PheWAS)来探究血清尿酸(SUA)水平在广泛疾病结局中的作用。

方法

我们进行了一项表型全基因组关联研究(PheWAS),以鉴定与 SUA 遗传风险基因座相关的疾病结局。然后,我们实施了传统的孟德尔随机化(MR)分析,以探究 SUA 水平与 PheWAS 中鉴定出的疾病结局之间的因果关系。接下来,我们应用 MR Egger 分析来检测和解释潜在的多效性,传统的 MR 分析可能会将其误认为因果关系,并使用 HEIDI(依赖工具变量的异质性)检验来消除可能由于遗传连锁而产生的跨表型关联。

结果

我们的 PheWAS 在经过多次测试校正(P<8.57e-05)后,确定了 25 个与 SUA 遗传风险基因座相关的疾病组/结局。我们的传统 MR 分析表明,SUA 水平与三种疾病组之间存在因果关系:炎症性多关节炎(OR=1.22,95%CI 1.11 至 1.34)、高血压疾病(OR=1.08,95%CI 1.03 至 1.14)和代谢紊乱(OR=1.07,95%CI 1.01 至 1.14);以及四种疾病结局:痛风(OR=4.88,95%CI 3.91 至 6.09)、原发性高血压(OR=1.08,95%CI 1.03 至 1.14)、心肌梗死(OR=1.16,95%CI 1.03 至 1.30)和乳糜泻(OR=1.41,95%CI 1.05 至 1.89)。在 MR Egger 分析中平衡多效性效应后,只有痛风及其包含的炎症性多关节炎疾病组被认为与 SUA 水平有因果关系。我们的分析强调了一个可能通过多效性影响 SUA 水平和多种心血管及自身免疫性疾病的基因座()。

结论

SUA 水平升高足以引起痛风和炎症性多关节炎,并且可能作为与它相关的更广泛疾病的标志物。我们的研究结果支持进一步研究 SUA 水平与心血管、代谢、自身免疫和呼吸系统疾病的临床相关性。

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