Department of Computational Biology, Institut Pasteur, Université Paris Cité, Paris, F-75015, France.
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
BMC Genomics. 2024 Apr 17;25(1):375. doi: 10.1186/s12864-024-10293-3.
Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.
Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)).
We detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria.
Multi-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.
在单变量全基因组关联研究（GWAS）中，约 95%的分析样本来自欧洲血统。这种在关联筛选中偏向欧洲血统人群的偏差也存在于其他分析方法中，这些分析方法通常仅在欧洲血统人群中开发和测试。然而，来自非欧洲人群的现有数据通常样本量较小，但可以从创新方法中受益，最近在多基因风险评分方面就得到了证明。
在这里，我们扩展和评估了我们的多性状 GWAS 管道 JASS（汇总统计联合分析）用于非欧洲血统分析的潜在局限性和收益。为此，我们对五个血统（欧洲（EUR）、混合血统的美洲人（AMR）、非洲人（AFR）、东亚人（EAS）和东南亚人（SAS））的 19 个血液性状和血糖性状进行了联合 GWAS。
我们在非欧洲人群中检测到 367 个新的全基因组显著关联（在混合美洲人群中检测到 15 个，在非洲人群中检测到 72 个，在东亚人群中检测到 280 个）。新检测到的关联分别占 AFR、AMR 和 EAS 人群中关联的 5%、17%和 13%。总体而言，多性状检验将欧洲相关位点在非欧洲血统中的复制率提高了 15%。在不同血统的显著位点，多性状遗传效应的表现出高度相似（例如，EUR 和 EAS 血统之间多性状遗传效应的平均相关性为 0.88）。对于血液性状，多性状遗传效应的强烈差异与已知的进化分歧有关：ARKC1 基因座，它是适应性的，以克服 p.vivax 诱导的疟疾。
多性状 GWAS 可以成为缩小欧洲和非欧洲人群之间遗传知识差距的有价值的工具。
