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用于理解早期暴露后果的转化流行病学方法。

Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures.

作者信息

D'Onofrio Brian M, Class Quetzal A, Rickert Martin E, Sujan Ayesha C, Larsson Henrik, Kuja-Halkola Ralf, Sjölander Arvid, Almqvist Catarina, Lichtenstein Paul, Oberg A Sara

机构信息

Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN, 47405, USA.

Karolinska Institutet, Stockholm, Sweden.

出版信息

Behav Genet. 2016 May;46(3):315-28. doi: 10.1007/s10519-015-9769-8. Epub 2015 Nov 21.

Abstract

Prominent developmental theories posit a causal link between early-life exposures and later functioning. Yet, observed associations with early exposures may not reflect causal effects because of genetic and environmental confounding. The current manuscript describes how a systematic series of epidemiologic analyses that combine several genetically-informative designs and statistical approaches can help distinguish between competing theories. In particular, the manuscript details how combining the use of measured covariates with sibling-comparisons, cousin-comparisons, and additional designs can help elucidate the sources of covariation between early-life exposures and later outcomes, including the roles of (a) factors that are not shared in families, including a potential causal effect of the exposure; (b) carryover effects from the exposure of one child to the next; and (c) familial confounding. We also describe key assumptions and how they can be critically evaluated. Furthermore, we outline how subsequent analyses, including effect decomposition with respect to measured, plausible mediators, and quantitative genetic models can help further specify the underlying processes that account for the associations between early-life exposures and offspring outcomes.

摘要

著名的发展理论假定早期经历与后期机能之间存在因果联系。然而,由于基因和环境混杂因素,观察到的早期经历关联可能无法反映因果效应。本手稿描述了一系列系统的流行病学分析如何结合多种基因信息设计和统计方法,有助于区分相互竞争的理论。特别是,手稿详细说明了如何将测量协变量的使用与兄弟姐妹比较、堂兄弟姐妹比较及其他设计相结合,以阐明早期经历与后期结果之间的协变来源,包括以下因素的作用:(a)家庭中不共享的因素,包括暴露的潜在因果效应;(b)一个孩子的暴露对另一个孩子的遗留效应;以及(c)家族混杂因素。我们还描述了关键假设以及如何对其进行严格评估。此外,我们概述了后续分析,包括针对测量的、合理的中介因素的效应分解和定量遗传模型,如何有助于进一步明确解释早期经历与后代结果之间关联的潜在过程。

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