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遗传结构解析复杂性状的连锁和关联研究。

Genetic architecture reconciles linkage and association studies of complex traits.

机构信息

Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.

QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

出版信息

Nat Genet. 2024 Nov;56(11):2352-2360. doi: 10.1038/s41588-024-01940-2. Epub 2024 Oct 7.

Abstract

Linkage studies have successfully mapped loci underlying monogenic disorders, but mostly failed when applied to common diseases. Conversely, genome-wide association studies (GWASs) have identified replicable associations between thousands of SNPs and complex traits, yet capture less than half of the total heritability. In the present study we reconcile these two approaches by showing that linkage signals of height and body mass index (BMI) from 119,000 sibling pairs colocalize with GWAS-identified loci. Concordant with polygenicity, we observed the following: a genome-wide inflation of linkage test statistics; that GWAS results predict linkage signals; and that adjusting phenotypes for polygenic scores reduces linkage signals. Finally, we developed a method using recombination rate-stratified, identity-by-descent sharing between siblings to unbiasedly estimate heritability of height (0.76 ± 0.05) and BMI (0.55 ± 0.07). Our results imply that substantial heritability remains unaccounted for by GWAS-identified loci and this residual genetic variation is polygenic and enriched near these loci.

摘要

连锁研究已经成功地定位了单基因疾病的相关基因座,但当应用于常见疾病时,大多以失败告终。相反,全基因组关联研究(GWAS)已经确定了数千个 SNP 与复杂性状之间可重复的关联,但只捕获了总遗传率的不到一半。在本研究中,我们通过显示身高和体重指数(BMI)的连锁信号从 119000 对同胞对中与 GWAS 确定的基因座共定位,从而调和了这两种方法。与多基因性一致,我们观察到以下几点:连锁测试统计数据的全基因组膨胀;GWAS 结果预测连锁信号;以及调整多基因评分的表型可以减少连锁信号。最后,我们开发了一种使用重组率分层和同胞间的血缘关系共享来无偏估计身高(0.76±0.05)和 BMI(0.55±0.07)遗传率的方法。我们的结果表明,GWAS 确定的基因座无法解释大量的遗传率,而这种剩余的遗传变异是多基因的,并在这些基因座附近富集。

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