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Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics.从 GWAS 汇总统计数据中同时估计双向因果效应和可遗传混杂。
Nat Commun. 2021 Dec 14;12(1):7274. doi: 10.1038/s41467-021-26970-w.
2
Prescription Opioid Use and Risk for Major Depressive Disorder and Anxiety and Stress-Related Disorders: A Multivariable Mendelian Randomization Analysis.处方阿片类药物使用与重度抑郁障碍和焦虑及应激相关障碍的风险:多变量孟德尔随机分析。
JAMA Psychiatry. 2021 Feb 1;78(2):151-160. doi: 10.1001/jamapsychiatry.2020.3554.
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An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression.一种用于识别可预防抑郁症的可调节因素的广泛暴露和孟德尔随机化方法。
Am J Psychiatry. 2020 Oct 1;177(10):944-954. doi: 10.1176/appi.ajp.2020.19111158. Epub 2020 Aug 14.
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Can Depression Be Prevented? If So, How?抑郁症可以预防吗?如果可以,该如何预防?
JAMA Psychiatry. 2020 Nov 1;77(11):1095-1096. doi: 10.1001/jamapsychiatry.2020.1273.
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A Mendelian randomization study of the causal association between anxiety phenotypes and schizophrenia.一项关于焦虑表型与精神分裂症因果关联的孟德尔随机化研究。
Am J Med Genet B Neuropsychiatr Genet. 2020 Sep;183(6):360-369. doi: 10.1002/ajmg.b.32808. Epub 2020 Jun 24.
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Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics.基于全基因组汇总统计数据,采用孟德尔随机化方法同时考虑相关和不相关的多效性效应。
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Minimal phenotyping yields genome-wide association signals of low specificity for major depression.最小表型分析产生的广泛性抑郁症全基因组关联信号特异性低。
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A robust and efficient method for Mendelian randomization with hundreds of genetic variants.一种用于数百种遗传变异的孟德尔随机化的强大而高效的方法。
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Factorial Mendelian randomization: using genetic variants to assess interactions.析因孟德尔随机化:利用遗传变异评估交互作用。
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Commentary: Orienting causal relationships between two phenotypes using bidirectional Mendelian randomization.评论:使用双向孟德尔随机化确定两种表型之间的因果关系
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精神医学中的孟德尔随机化:它是如何运作的,又能告诉我们什么?

Mendelian randomisation for psychiatry: how does it work, and what can it tell us?

机构信息

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

出版信息

Mol Psychiatry. 2022 Jan;27(1):53-57. doi: 10.1038/s41380-021-01173-3. Epub 2021 Jun 4.

DOI:10.1038/s41380-021-01173-3
PMID:34088980
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8960388/
Abstract

The successful prevention of mental illness relies upon the identification of causal, modifiable risk factors. However, observational evidence exploring such risk factors often produces contradictory results and randomised control trials are often expensive, time-consuming or unethical to conduct. Mendelian randomisation (MR) is a complementary approach that uses naturally occurring genetic variation to identify possible causal effects between a risk factor and an outcome in a time-efficient and low-cost manner. MR utilises genetic variants as instrumental variables for the risk factor of interest. MR studies are becoming more frequent in the field of psychiatry, warranting a reflection upon both the possibilities and the pitfalls. In this Perspective, we consider several limitations of the MR method that are of particular relevance to psychiatry. We also present new MR methods that have exciting applications to questions of mental illness. While we believe that MR can make an important contribution to the field of psychiatry, we also wish to emphasise the importance of clear causal questions, thorough sensitivity analyses, and triangulation with other forms of evidence.

摘要

成功预防精神疾病依赖于识别因果可调节风险因素。然而,观察性证据经常产生相互矛盾的结果,并且随机对照试验往往昂贵、耗时或不道德。孟德尔随机化(MR)是一种补充方法,它利用自然发生的遗传变异,以高效和低成本的方式识别风险因素与结果之间可能的因果关系。MR 将遗传变异用作感兴趣的风险因素的工具变量。MR 研究在精神病学领域越来越频繁,因此有必要对其可能性和陷阱进行反思。在本文中,我们考虑了 MR 方法对精神病学特别相关的几个局限性。我们还介绍了新的 MR 方法,这些方法对精神疾病的问题具有令人兴奋的应用。虽然我们认为 MR 可以为精神病学领域做出重要贡献,但我们也希望强调提出明确的因果问题、进行彻底的敏感性分析以及与其他形式的证据进行三角验证的重要性。