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利用两样本孟德尔随机化解析母体环境暴露对后代健康和疾病的作用。

Elucidating the role of maternal environmental exposures on offspring health and disease using two-sample Mendelian randomization.

机构信息

University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

出版信息

Int J Epidemiol. 2019 Jun 1;48(3):861-875. doi: 10.1093/ije/dyz019.

Abstract

BACKGROUND

There is considerable interest in estimating the causal effect of a range of maternal environmental exposures on offspring health-related outcomes. Previous attempts to do this using Mendelian randomization methodologies have been hampered by the paucity of epidemiological cohorts with large numbers of genotyped mother-offspring pairs.

METHODS

We describe a new statistical model that we have created which can be used to estimate the effect of maternal genotypes on offspring outcomes conditional on offspring genotype, using both individual-level and summary-results data, even when the extent of sample overlap is unknown.

RESULTS

We describe how the estimates obtained from our method can subsequently be used in large-scale two-sample Mendelian randomization studies to investigate the causal effect of maternal environmental exposures on offspring outcomes. This includes studies that aim to assess the causal effect of in utero exposures related to fetal growth restriction on future risk of disease in offspring. We illustrate our framework using examples related to offspring birthweight and cardiometabolic disease, although the general principles we espouse are relevant for many other offspring phenotypes.

CONCLUSIONS

We advocate for the establishment of large-scale international genetics consortia that are focused on the identification of maternal genetic effects and committed to the public sharing of genome-wide summary-results data from such efforts. This information will facilitate the application of powerful two-sample Mendelian randomization studies of maternal exposures and offspring outcomes.

摘要

背景

人们对估计一系列母体环境暴露对后代健康相关结果的因果效应非常感兴趣。以前使用孟德尔随机化方法进行这项研究的尝试受到了缺乏大量基因分型母子对的流行病学队列的阻碍。

方法

我们描述了一种新的统计模型,该模型可以在已知样本重叠程度未知的情况下,使用个体水平和汇总结果数据,根据后代基因型来估计母体基因型对后代结局的影响。

结果

我们描述了如何使用我们的方法获得的估计值,随后可以在大规模两样本孟德尔随机化研究中,调查母体环境暴露对后代结局的因果效应。这包括旨在评估与胎儿生长受限相关的宫内暴露对后代未来疾病风险的因果效应的研究。我们使用与后代出生体重和心脏代谢疾病相关的例子来说明我们的框架,尽管我们所倡导的一般原则与许多其他后代表型有关。

结论

我们提倡建立专注于识别母体遗传效应的大型国际遗传学联盟,并致力于公开分享此类努力的全基因组汇总结果数据。这些信息将促进对母体暴露和后代结局的强大两样本孟德尔随机化研究的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd20/6659380/653bb717643d/dyz019f1.jpg

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