MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives.

IF 2.6 4区 医学 Q2 BEHAVIORAL SCIENCES Behavior Genetics Pub Date : 2023-02-01 Epub Date: 2022-11-02 DOI:10.1007/s10519-022-10122-x
Luis F S Castro-de-Araujo, Madhurbain Singh, Yi Zhou, Philip Vinh, Brad Verhulst, Conor V Dolan, Michael C Neale
{"title":"MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives.","authors":"Luis F S Castro-de-Araujo, Madhurbain Singh, Yi Zhou, Philip Vinh, Brad Verhulst, Conor V Dolan, Michael C Neale","doi":"10.1007/s10519-022-10122-x","DOIUrl":null,"url":null,"abstract":"<p><p>Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non-familial sources. Our model extends the MRDoC model (Minică et al. in Behav Genet 48:337-349,  https://doi.org/10.1007/s10519-018-9904-4 , 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al. in Behav Genet 23:29-50,  https://doi.org/10.1007/BF01067552 , 1993).</p>","PeriodicalId":8715,"journal":{"name":"Behavior Genetics","volume":"53 1","pages":"63-73"},"PeriodicalIF":2.6000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823046/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavior Genetics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10519-022-10122-x","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/11/2 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non-familial sources. Our model extends the MRDoC model (Minică et al. in Behav Genet 48:337-349,  https://doi.org/10.1007/s10519-018-9904-4 , 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al. in Behav Genet 23:29-50,  https://doi.org/10.1007/BF01067552 , 1993).

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
MR-DoC2:利用工具变量和亲属数据进行双向因果建模。
确定因果关系是针对精神障碍、药物使用和许多其他疾病制定干预措施的重要一步。虽然随机对照试验(RCT)被认为是因果关系推断的黄金标准,但在很多情况下并不道德。在这种情况下,可以使用孟德尔随机法(MR),但重要的是,随机对照试验和孟德尔随机法都假定了单向因果关系。在本文中,我们建立了一个新模型 MRDoC2,该模型可用于在存在家族和非家族来源混杂的情况下识别双向因果关系。我们的模型扩展了 MRDoC 模型(Minică et al. in Behav Genet 48:337-349, https://doi.org/10.1007/s10519-018-9904-4 , 2018),同时包含了每个性状的风险评分。此外,MRDoC2 中检测因果效应的能力并不要求表型具有不同的加性遗传或共享环境变异源,这与因果方向双胞胎模型(Heath 等人,载于 Behav Genet 23:29-50, https://doi.org/10.1007/BF01067552 , 1993)的情况相同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Behavior Genetics
Behavior Genetics 生物-行为科学
CiteScore
4.90
自引率
7.70%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Behavior Genetics - the leading journal concerned with the genetic analysis of complex traits - is published in cooperation with the Behavior Genetics Association. This timely journal disseminates the most current original research on the inheritance and evolution of behavioral characteristics in man and other species. Contributions from eminent international researchers focus on both the application of various genetic perspectives to the study of behavioral characteristics and the influence of behavioral differences on the genetic structure of populations.
期刊最新文献
Negative Life Events and Epigenetic Ageing: A Study in the Netherlands Twin Register. No Evidence of Interaction Between FADS2 Genotype and Breastfeeding on Cognitive or Other Traits in the UK Biobank. Can a Hybrid Line Break a Selection Limit on Behavioral Evolution in Mice? On the Detection of Population Heterogeneity in Causation Between Two Variables: Finite Mixture Modeling of Data Collected from Twin Pairs. Experimental Evolution Induced by Maternal Post-copulatory Factors in Drosophila.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1