孟德尔随机化
病因学
因果关系(物理学)
混淆
医学
疾病
遗传倾向
免疫学
因果推理
遗传关联
生物信息学
遗传学
生物
单核苷酸多态性
病理
内科学
基因型
物理
基因
量子力学
遗传变异
作者
Cong Chen,Peng Wang,Ruo-Di Zhang,Fang Yang,Ling-Qiong Jiang,Xi Fang,Yan Zhao,De‐Guang Wang,Jing Ni,Hai‐Feng Pan
标识
DOI:10.1016/j.autrev.2022.103210
摘要
Autoimmune diseases (ADs) are a broad range of disorders which are characterized by long-term inflammation and tissue damage arising from an immune response against one's own tissues. It is now widely accepted that the causes of ADs include environmental factors, genetic susceptibility and immune dysregulation. However, the exact etiology of ADs has not been fully elucidated to date. Because observational studies are plagued by confounding factors and reverse causality, no firm conclusions can be drawn about the etiology of ADs. Over the years, Mendelian randomization (MR) analysis has come into focus, offering unique perspectives and insights into the etiology of ADs and promising the discovery of potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly dispensed during meiosis, usually irrespective of environmental or lifestyle factors) is used instead of modifiable exposure to explore the link between exposure factors and disease or other outcomes. Therefore, MR analysis can provide a valuable method for exploring the causal relationship between different risk factors and ADs when its inherent assumptions and limitations are fully considered. This review summarized the recent findings of MR in major ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1DM), focused on the effects of different risk factors on ADs risks. In addition, we also discussed the opportunities and challenges of MR methods in ADs research.
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