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用于检验胎儿驱动因果效应的统计框架。

A statistical framework for testing the causal effects of fetal drive.

作者信息

Liu Nianjun, Archer Edward, Srinivasasainagendra Vinodh, Allison David B

机构信息

Department of Biostatistics, School of Public Health, University of Alabama at Birmingham Birmingham, AL, USA.

Office of Energetics, School of Public Health, University of Alabama at Birmingham Birmingham, AL, USA.

出版信息

Front Genet. 2015 Jan 13;5:464. doi: 10.3389/fgene.2014.00464. eCollection 2014.

Abstract

Maternal genetic and phenotypic characteristics (e.g., metabolic and behavioral) affect both the intrauterine milieu and lifelong health trajectories of their fetuses. Yet at the same time, fetal genotype may affect processes that alter pre and postnatal maternal physiology, and the subsequent health of both fetus and mother. We refer to these latter effects as 'fetal drive.' If fetal genotype is driving physiologic, metabolic, and behavioral phenotypic changes in the mother, there is a possibility of differential effects with different fetal genomes inducing different long-term effects on both maternal and fetal health, mediated through intrauterine environment. This proposed mechanistic path remains largely unexamined and untested. In this study, we offer a statistical method to rigorously test this hypothesis and make causal inferences in humans by relying on the (conditional) randomization inherent in the process of meiosis. For illustration, we apply this method to a dataset from the Framingham Heart Study.

摘要

母亲的遗传和表型特征(如代谢和行为方面)会影响其胎儿的宫内环境和终生健康轨迹。然而与此同时,胎儿基因型可能会影响改变产前和产后母亲生理状况以及胎儿和母亲后续健康的过程。我们将这些后者的影响称为“胎儿驱动”。如果胎儿基因型驱动着母亲生理、代谢和行为表型的变化,那么不同的胎儿基因组可能会通过宫内环境对母亲和胎儿的健康产生不同的长期影响,这种差异效应是有可能存在的。这条提出的机制路径在很大程度上仍未得到检验。在本研究中,我们提供一种统计方法,通过依赖减数分裂过程中固有的(条件)随机化来严格检验这一假设并在人类中进行因果推断。为了说明,我们将此方法应用于弗雷明汉心脏研究的一个数据集。

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