A Transethnic Mendelian Randomization Study Identifies Causality of Obesity on Risk of Psoriasis.
A Transethnic Mendelian Randomization Study Identifies Causality of Obesity on Risk of Psoriasis.
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一项跨种族孟德尔随机研究确定了肥胖与牛皮癣风险的因果关系。
DOI：
10.1016/j.jid.2018.11.023
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Okada,Yukinori
中科院分区：
文献类型：
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作者：
Ogawa,Kotaro;Stuart,PhilipE;Tsoi,LamC;Suzuki,Ken;Nair,RajanP;Mochizuki,Hideki;Elder,JamesT;Okada,Yukinori
牛皮癣是一种以皮肤和全身表现为特征的慢性疾病。流行病学研究报告称，银屑病与代谢临床测量等多种复杂疾病的合并症有所增加（Greb 等人，2016；Naito 和 Imafuku，2016）。然而，迄今为止，对合并症的解释仍然存在争议，因为仅依靠流行病学研究很难推断相关表型之间的因果关系。相关表型之间因果推断的识别具有重大的临床影响，因为因果表型的修改可能有利于结果表型的治疗。因果表型所指示的药物也可能是针对结果表型进行药物重新定位的有希望的目标（Holmes 等人，2017）。因此，有必要采取替代方法来加强银屑病的因果推断。为此目的而流行的一种方法是使用遗传数据（Pingault 等人，2018）。遗传确定的表型特征对于一生中获得的混杂因素具有鲁棒性，这可以解释为受试者的理想随机化。孟德尔随机化 (MR) 是一种使用全基因组关联研究 (GWAS) 结果来推断表型之间因果关系的方法（Holmes 等，2017；Hemani 等，2018）。由于 (i) 通过公共数据存储实现了各种人类表型的大规模 GWAS，以及 (ii) 开发了稳健推断因果关系的 MR 分析方法，例如 MR-Egger（Burgess 和 Thompson，2017），MR 现在是推断因果关系的最佳方法之一。一般来说，单一祖先中最大的可用 GWAS 结果用于 MR 分析，以提供可靠的结论。因此，MR 分析结果的确认需要使用具有独立血统的 GWAS 进行额外验证。
Psoriasis is a chronic disorder characterized by cutaneous and systemic manifestations. Epidemiological studies have reported increased comorbidity of psoriasis with numerous complex diseases such as metabolic clinical measurements (Greb et al., 2016, Naito and Imafuku, 2016). However, interpretation of the comorbidity remains controversial to date, because causal inference between correlated phenotypes is difficult when depending solely on epidemiological studies. Identification of causal inference between correlated phenotypes has significant clinical impacts, because modification of the causal phenotypes could benefit treatment of the outcome phenotypes. Drugs indicated by the causal phenotypes could also be promising targets of drug repositioning for the outcome phenotypes (Holmes et al., 2017). Therefore, alternative approaches to strengthen causal inference on psoriasis are warranted.An approach becoming popular for this purpose is use of genetic data (Pingault et al., 2018). Genetically determined phenotype profiles are robust to confounding factors acquired during a lifetime, which could be interpreted as ideal randomization of subjects. Mendelian randomization (MR) is an approach to infer causal inference between phenotypes using the genome-wide association study (GWAS) results (Holmes et al., 2017, Hemani et al., 2018). Because of (i) achievement of large-scale GWASs of a variety of human phenotypes with public data deposit and (ii) development of MR analytical methods that robustly infer causality, such as MR-Egger (Burgess and Thompson, 2017), MR is now one of the best approaches to infer causality. Generally, the largest available GWAS result within a single ancestry is used for an MR analysis to afford robust conclusions. Thus, confirmation of the MR analysis results requires additional validation using GWAS with independent ancestry.