Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders.,Genes, Brain and Behavior

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Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders.
Genes, Brain and Behavior ( IF 2.4 ) Pub Date : 2020-04-29 , DOI: 10.1111/gbb.12660
Alison K Merikangas _{1,

2,

3} , Laura Almasy _{1,

2,

3}

Affiliation

Many neuropsychiatric disorders exhibit differences in prevalence, age of onset, symptoms or course of illness between males and females. For the most part, the origins of these differences are not well understood. In this article, we provide an overview of sex differences in psychiatric disorders including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), anxiety, depression, alcohol and substance abuse, schizophrenia, eating disorders and risk of suicide. We discuss both genetic and nongenetic mechanisms that have been hypothesized to underlie these differences, including ascertainment bias, environmental stressors, X‐ or Y‐linked risk loci, and differential liability thresholds in males and females. We then review the use of twin, family and genome‐wide association approaches to study potential genetic mechanisms of sex differences and the extent to which these designs have been employed in studies of psychiatric disorders. We describe the utility of genetic epidemiologic study designs, including classical twin and family studies, large‐scale studies of population registries, derived recurrence risks, and molecular genetic analyses of genome‐wide variation that may enhance our understanding sex differences in neuropsychiatric disorders.

中文翻译：

使用遗传流行病学工具了解神经精神疾病的性别差异。

许多神经精神疾病在男性和女性之间在患病率，发病年龄，症状或病程方面表现出差异。在大多数情况下，人们对这些差异的起源还没有很好的了解。在本文中，我们概述了包括自闭症谱系障碍（ASD），注意力不足/多动症（ADHD），焦虑症，抑郁症，酒精和药物滥用，精神分裂症，饮食失调和自杀风险在内的精神病患者的性别差异。我们讨论了被认为是造成这些差异的基础的遗传和非遗传机制，包括确定性偏倚，环境压力因素，X或Y相关的风险基因座以及男性和女性的差异责任阈值。然后，我们回顾一下twin的用法，家庭和全基因组关联方法来研究性别差异的潜在遗传机制以及这些设计在精神疾病研究中的应用程度。我们描述了遗传流行病学研究设计的实用性，包括经典的双胞胎和家庭研究，大规模的人口登记研究，衍生复发风险以及全基因组变异的分子遗传学分析，这些分析可能会加深我们对神经精神疾病的性别差异的了解。

更新日期：2020-04-29

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