How to estimate heritability: a guide for genetic epidemiologists.
How to estimate heritability: a guide for genetic epidemiologists.
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DOI：
10.1093/ije/dyac224
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发表时间：
2023-04-19
影响因子：
7.7
通讯作者：
中科院分区：
文献类型：
--
作者：
传统上，遗传能力是通过基于家庭的方法来估计的，比如双胞胎研究。分子基因组学的进步促进了使用大量（不相关或相关）基因分型个体样本的方法的发展。在这里，我们概述了遗传流行病学中用于估计遗传力的常用方法，即由遗传变异解释的表型变异的比例。我们提供了理解遗传力估计方法所需的关键遗传概念指南，包括基于家庭的设计（双胞胎和家庭研究），基于非亲属个体的基因组设计[连锁不平衡评分回归，基因组亲缘关系限制最大似然（GREML）估计]和基于家庭的基因组设计(兄弟姐妹回归，GREML-亲属关系，三基因组-全基因组复杂性状分析，母亲-全基因组复杂性状分析，相关性不平衡回归)。我们描述了如何估计每种方法的遗传力及其估计的假设，并讨论了当这些假设不满足时的影响。我们进一步讨论了与相关个体样本相比，在非相关个体样本中估计遗传力的好处和局限性。总之，本文旨在帮助读者确定每种方法在什么情况下是合适的以及为什么合适。
Traditionally, heritability has been estimated using family-based methods such as twin studies. Advancements in molecular genomics have facilitated the development of methods that use large samples of (unrelated or related) genotyped individuals. Here, we provide an overview of common methods applied in genetic epidemiology to estimate heritability, i.e. the proportion of phenotypic variation explained by genetic variation. We provide a guide to key genetic concepts required to understand heritability estimation methods from family-based designs (twin and family studies), genomic designs based on unrelated individuals [linkage disequilibrium score regression, genomic relatedness restricted maximum-likelihood (GREML) estimation] and family-based genomic designs (sibling regression, GREML-kinship, trio-genome-wide complex trait analysis, maternal-genome-wide complex trait analysis, relatedness disequilibrium regression). We describe how heritability is estimated for each method and the assumptions underlying its estimation, and discuss the implications when these assumptions are not met. We further discuss the benefits and limitations of estimating heritability within samples of unrelated individuals compared with samples of related individuals. Overall, this article is intended to help the reader determine the circumstances when each method would be appropriate and why.
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影响因子：
4.5
作者：
Zaitlen N;Kraft P;Patterson N;Pasaniuc B;Bhatia G;Pollack S;Price AL
通讯作者：
Price AL
影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
影响因子：
64.8
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通讯作者：
Skol, Andrew
影响因子：
2.6
作者：
Mayhew AJ;Meyre D
通讯作者：
Meyre D
影响因子：
2.4
作者：
Choo SY
通讯作者：
Choo SY