Graduate School of Information Sciences, Tohoku University, Sendai, Japan.
Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
PLoS One. 2024 Nov 7;19(11):e0305803. doi: 10.1371/journal.pone.0305803. eCollection 2024.
Chronic obstructive pulmonary disease (COPD) is a highly prevalent disease, making it a leading cause of death worldwide. Several genome-wide association studies (GWAS) have been conducted to identify loci associated with COPD. However, different ancestral genetic compositions for the same disease across various populations present challenges in studies involving multi-population data. In this study, we aimed to identify protein-coding genes associated with COPD by prioritizing genes for each population's GWAS data, and then combining these results instead of performing a common meta-GWAS due to significant sample differences in different population cohorts. Lung function measurements are often used as indicators for COPD risk prediction; therefore, we used lung function GWAS data from two populations, Japanese and European, and re-evaluated them using a multi-population gene prioritization approach. This study identified significant single nucleotide variants (SNPs) in both Japanese and European populations. The Japanese GWAS revealed nine significant SNPs and four lead SNPs in three genomic risk loci. In comparison, the European population showed five lead SNPs and 17 independent significant SNPs in 21 genomic risk loci. A comparative analysis of the results found 28 similar genes in the prioritized gene lists of both populations. We also performed a standard meta-analysis for comparison and identified 18 common genes in both populations. Our approach demonstrated that trans-ethnic linkage disequilibrium (LD) could detect some significant novel associations and genes that have yet to be reported or were missed in previous analyses. The study suggests that a gene prioritization approach for multi-population analysis using GWAS data may be a feasible method to identify new associations in data with genetic diversity across different populations. It also highlights the possibility of identifying generalized and population-specific treatment and diagnostic options.
慢性阻塞性肺疾病(COPD)是一种高发疾病,使其成为全球主要死亡原因之一。已经进行了几项全基因组关联研究(GWAS),以确定与 COPD 相关的基因座。然而,不同人群中同一疾病的遗传组成不同,这给涉及多人群数据的研究带来了挑战。在这项研究中,我们旨在通过优先考虑每个人群的 GWAS 数据中的基因来识别与 COPD 相关的蛋白质编码基因,然后合并这些结果,而不是由于不同人群队列中的样本差异很大而进行常见的元 GWAS。肺功能测量通常用作 COPD 风险预测的指标;因此,我们使用来自日本和欧洲的两个人群的肺功能 GWAS 数据,并使用多人群基因优先级方法重新评估它们。这项研究在日本和欧洲人群中都确定了显著的单核苷酸变异(SNP)。日本 GWAS 揭示了三个基因组风险位点的九个显著 SNP 和四个主要 SNP。相比之下,欧洲人群在 21 个基因组风险位点中显示了五个主要 SNP 和 17 个独立的显著 SNP。对结果的比较分析发现,两个人群的优先基因列表中有 28 个相似的基因。我们还进行了标准的荟萃分析进行比较,在两个人群中都发现了 18 个共同的基因。我们的方法表明,使用 GWAS 数据进行多人群分析的跨种族连锁不平衡(LD)可以检测到一些以前的分析中尚未报道或遗漏的重要新关联和基因。该研究表明,使用 GWAS 数据对多人群分析进行基因优先级分析可能是一种可行的方法,可以在具有不同人群遗传多样性的数据中识别新的关联。它还强调了识别通用和特定于人群的治疗和诊断选择的可能性。