Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
J Transl Med. 2022 Sep 23;20(1):424. doi: 10.1186/s12967-022-03637-8.
Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking.
By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement.
Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones.
Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.
检测跨种族共同相关的遗传基因座可以为不同大陆人群中复杂疾病/特征的共同遗传成分提供重要的见解。然而，目前缺乏实现这一目标的有效统计方法。
通过利用来自全球范围内全基因组关联研究的汇总统计数据，我们从高维复合零假设检验的角度提出了一种新的遗传重叠检测方法，称为 CONTO（跨种族遗传重叠的复合零假设检验）。与通常分析个体遗传变异的先前研究不同，CONTO 是一种基于基因的方法，它集中在一组位于一个基因内的遗传变异上，同时评估它们与感兴趣特征的联合显著性。通过借鉴联合显著性检验（JST）的相似原理，CONTO 将多个关联的最大 P 值作为显著性测量值。
与通常过于保守的 JST 相比，CONTO 在两个方面得到了改进，包括三组分混合零分布的构建和跨种族遗传相关性的调整。因此，CONTO 通过精心校准的 P 值纠正了 JST 的保守性，并且通过广泛的模拟研究得到了更有力的验证。我们应用 CONTO 发现了东亚和欧洲人群之间 31 种复杂疾病/特征的共同相关基因，并确定了许多被 JST 遗漏的共同特征相关基因。我们进一步表明，群体共同基因通常比群体特异性或无效基因更具进化保守性。
总的来说，CONTO 代表了一种在不同祖先群体中检测共同相关基因的强大方法；我们的结果为在一个群体中进行的 GWAS 发现转移到其他群体提供了重要的启示。
