遗传力
遗传力缺失问题
全基因组关联研究
遗传关联
连锁不平衡
生物
缺少数据
遗传学
进化生物学
遗传变异
统计
基因型
单核苷酸多态性
数学
基因
作者
Ilja M. Nolte,Felix C. Tropf,Harold Snieder
标识
DOI:10.1002/9780470015902.a0028223
摘要
Abstract Genome‐wide association studies (GWASs) have identified thousands of genetic variants involved in complex traits and diseases, but these only explain a minor fraction of the heritability. New methodologies that scrutinise the GWAS data indicate where the missing heritability might be found. About half of the heritability is still hidden in the GWAS data as this concerns common variants with small effects. Furthermore, a large part is still missing because this involves rare variants, which cannot be detected by GWAS due to low linkage disequilibrium. Nevertheless, even estimates of the most sophisticated methods do not fully reach the total genetic contributions derived from twin and family studies, suggesting that these heritabilities may be overestimated due to violation of the underlying assumptions or heterogeneity in heritability estimation across populations. Future variant discovery for complex traits and diseases will capture an ever larger part of the genetic predisposition and eventually bring health care applications within reach. Key Concepts Genome‐wide association studies (GWAS) have so far been able to only explain a minority of the heritability of complex traits or diseases, a large part is missing. The missing heritability can be divided in hidden heritability, still‐missing heritability and phantom heritability. Part of the missing heritability is hidden in the GWAS data meaning that due to lack of power the underlying common genetic variants have not yet been identified. About half of the heritability of complex traits or diseases is expected to be caused by common variants and can ultimately be found by GWAS. The still‐missing heritability can be explained by rare and structural genetic variants, dominance effects and epistasis. The effects of dominance and epistasis are likely not very large. Heritability estimates from twin and family studies may be overestimated due to violation of underlying model assumptions and therefore cause phantom heritability. Heritability is likely also missing due to heterogeneity of effects between and within populations, as estimates from twin and family studies are calculated in homogeneous populations.
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