Explaining additional genetic variation in complex traits

被引:101
|
作者
Robinson, Matthew R. [1 ]
Wray, Naomi R. [1 ]
Visscher, Peter M. [1 ,2 ]
机构
[1] Univ Queensland, Queensland Brain Inst, Brisbane, Qld 4072, Australia
[2] Univ Queensland, Diamantina Inst, Translat Res Inst, Brisbane, Qld 4102, Australia
基金
澳大利亚研究理事会; 美国国家卫生研究院; 英国医学研究理事会;
关键词
GENOME-WIDE ASSOCIATION; ANALYSIS IDENTIFIES 13; COPY-NUMBER VARIATION; MISSING HERITABILITY; VARIANTS; DISEASE; LOCI; RARE; MUTATIONS; COMMON;
D O I
10.1016/j.tig.2014.02.003
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those that influence phenotype, because there are likely to be many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping, including recording of nongenetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power.
引用
收藏
页码:124 / 132
页数:9
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