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环境对青春期晚期和成年早期抑郁症状的影响:全暴露组关联研究和双胞胎建模 ...

已有 204 次阅读2023-11-30 16:11 |个人分类:心理学、心理健康、心理咨询|系统分类:科技教育分享到微信

环境对青春期晚期和成年早期抑郁症状的影响:全暴露组关联研究和双胞胎建模 

The effect of environment on depressive symptoms in late adolescence and early adulthood: an exposome-wide association study and twin modeling

 

——原载《自然-心理健康》2023年第1卷第10期——

<Nature - Mental Health> 1 (10), 2023

 

【摘要】暴露组代表了环境影响的总体,但其与抑郁症状之间的系统评价还很少。在这里,我们试图全面确定暴露组与青春期晚期和成年早期抑郁症状的关联,并确定它们之间的遗传和环境协方差。基于FinnTwin12队列(3,025名青年期参与者和4,12717岁参与者),采用全暴露组关联研究 (ExWAS) 设计来识别来自12个领域的显著暴露。双变量Cholesky双胞胎模型适合暴露组评分和抑郁症状。在ExWAS中,分别有2946次接触与青年期和17岁时的抑郁症状显著相关,其中家庭接触影响最大。双胞胎模型表明,暴露组评分和抑郁症状之间存在相当大的遗传和环境协方差,且存在性别差异。研究结果强调了暴露组的系统方法以及对相关遗传效应的考虑。

 

[Abstract] The exposome represents the totality of environmental effects, but systematic evaluation between it and depressive symptoms is scant. Here we sought to comprehensively identify the association of the exposome with depressive symptoms in late adolescence and early adulthood and determine genetic and environmental covariances between them. Based on the FinnTwin12 cohort (3,025 participants in young adulthood and 4,127 at age 17), the exposome-wide association study (ExWAS) design was used to identify significant exposures from 12 domains. Bivariate Cholesky twin models were fitted to an exposome score and depressive symptoms. In ExWASes, 29 and 46 exposures were significantly associated with depressive symptoms in young adulthood and at age 17, respectively, and familial exposures were the most influential. Twin models indicated considerable genetic and environmental covariances between the exposome score and depressive symptoms with sex differences. The findings underscore the systematic approach of the exposome and the consideration of relevant genetic effects.

 

论文原文:Wang Zhiyang, Stephanie Zellers, Alyce M. Whipp, Marja Heinonen-Guzejev, Maria Foraster, Jordi Júlvez, Irene van Kamp & Jaakko Kaprio (2023). The effect of environment on depressive symptoms in late adolescence and early adulthood: an exposome-wide association study and twin modeling. Nature - Mental Health, 1(10), 751–760.

https://doi.org/10.1038/s44220-023-00124-x


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