An atlas of genetic correlations across human diseases and traits.
An atlas of genetic correlations across human diseases and traits.
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DOI：
10.1038/ng.3406
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发表时间：
2015-11
期刊：
影响因子：
30.8
通讯作者：
Neale BM
中科院分区：
文献类型：
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作者：
Bulik-Sullivan B;Finucane HK;Anttila V;Gusev A;Day FR;Loh PR;ReproGen Consortium;Psychiatric Genomics Consortium;Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3;Duncan L;Perry JR;Patterson N;Robinson EB;Daly MJ;Price AL;Neale BM
识别复杂性状和疾病之间的遗传相关性能够提供有用的病因学见解，并有助于对可能的因果关系进行优先级排序。当前方法在利用全基因组关联研究（GWAS）数据估计遗传相关性时面临的主要挑战是缺乏个体基因型数据以及荟萃分析中普遍存在样本重叠。我们通过引入一种技术——跨性状连锁不平衡（LD）得分回归来规避这些困难，该技术用于估计遗传相关性，仅需GWAS汇总统计数据，且不受样本重叠的影响。我们使用这种方法估计了24种性状之间的276个遗传相关性。结果包括神经性厌食症与精神分裂症之间、厌食症与肥胖症之间的遗传相关性，以及受教育程度与几种疾病之间的关联。这些结果凸显了全基因组分析的威力，因为目前神经性厌食症没有显著相关的单核苷酸多态性（SNP），而受教育程度也仅有三个。
Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique – cross-trait LD Score regression – for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity and associations between educational attainment and several diseases. These results highlight the power of genome-wide analyses, since there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.