孟德尔随机化在神经病学研究中的应用进展
Advances in the Application of Mendelian Randomization in Neurological Research
摘要: 孟德尔随机化(Mendelian randomization, MR)利用遗传信息进行因果推断。近年来，随着与脑组织基因表达、脑成像及神经系统疾病等表型相关的大规模公共遗传关联数据的扩展，孟德尔随机化被广泛应用于神经病学领域的研究当中。本文将围绕孟德尔随机化的基本原理和局限性以及它在神经病学领域中的多种应用进行综述。另外，本文还提供了孟德尔随机化分析的部分案例，它们不仅解决了某些长期存在的流行病学争议、为探寻神经系统疾病的病理生理学机制提供了独特方法，还为筛选潜在药物靶点及拓展药物新适应症提供了路径。随着全基因组关联研究(GWAS)数据的不断增加，孟德尔随机化必将极大推动神经病学领域的研究进展，该领域相关人员有必要熟悉此研究方法。
Abstract: Mendelian randomization (MR) utilizes genetic information for causal inference. In recent years, with the expansion of large-scale public genetic association data related to phenotypes such as brain tissue gene expression, brain imaging, and neurological diseases, Mendelian randomization has been widely applied in the field of neurology research. This article will review the basic principles and limitations of Mendelian randomization, as well as its various applications in the field of neurology. In addition, this article also provides some cases of Mendelian randomization analysis, which not only solves some long-standing epidemiological controversies and provides a unique method for exploring the pathophysiological mechanisms of neurological diseases, but also provides a pathway for screening potential drug targets and expanding new drug indications. With the continuous increase of genome-wide association studies (GWAS) data, Mendelian randomization will greatly promote research progress in the field of neurology, and it is necessary for relevant personnel in this field to be familiar with this research method.
文章引用：吴含, 李长清. 孟德尔随机化在神经病学研究中的应用进展[J]. 临床医学进展, 2024, 14(7): 380-388. https://doi.org/10.12677/acm.2024.1472025

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