当前位置: X-MOL 学术BMC Genomics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics.
BMC Genomics ( IF 3.5 ) Pub Date : 2020-03-14 , DOI: 10.1186/s12864-020-6626-9
Chani J Hodonsky 1, 2 , Antoine R Baldassari 1 , Stephanie A Bien 3 , Laura M Raffield 4 , Heather M Highland 1 , Colleen M Sitlani 5 , Genevieve L Wojcik 6 , Ran Tao 7 , Marielisa Graff 1 , Weihong Tang 8 , Bharat Thyagarajan 8 , Steve Buyske 9 , Myriam Fornage 10 , Lucia A Hindorff 11 , Yun Li 1 , Danyu Lin 1 , Alex P Reiner 3, 12 , Kari E North 1, 4 , Ruth J F Loos 13 , Charles Kooperberg 12 , Christy L Avery 1
Affiliation  

BACKGROUND Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. RESULTS We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. CONCLUSION This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.

中文翻译:


在红细胞性状的全基因组组合表型研究中发现的祖先特异性关联强调了基因组学多样性的好处。



背景 红细胞定量 (RBC) 性状是高度多基因的临床相关性状,已报道约 500 个 GWAS 位点。大多数红细胞性状 GWAS 是在欧洲或东亚血统人群中进行的,尽管有证据表明罕见或血统特异性变异对红细胞性状遗传性有很大贡献。最近开发的利用遗传性状相关性来提高统计功效的组合表型方法尚未应用于这些性状。在这里,我们利用七个红细胞定量性状的相关性在多种族研究人群中进行组合表型分析。结果我们使用自适应动力得分总和 (aSPU) 测试来评估多种族人群中约 2100 万个 SNP 和 7 个 RBC 性状之间的组合表型关联(最多 n = 67,885 名参与者;24% 为非裔美国人,30% 为西班牙裔/拉丁裔,43% 为欧洲裔美国人;76% 为女性)。我们的多种族人群中的 39 个位点至少包含一个显着关联信号 (p < 5E-9),其中 9 个位点的先导 SNP 与 3 个或更多 RBC 性状显着相关。大多数先导 SNP 在所有祖先群体中都是常见的 (MAF > 5%)。在 7 个已知基因座(HFE、KIT、HBS1L/MYB、CITED2/FILNC1、ABO、HBA1/2 和 PLIN4/5)上鉴定了 19 个额外的独立关联信号。例如,HBA1/2 基因座包含 14 个条件独立关联信号,其中 11 个以前未报告,并且是非洲和美洲印第安人血统特有的。该区域的一种变异在所有血统中都很常见,但在非裔美国人中表现出比欧洲裔美国人或西班牙裔/拉丁美洲人更窄的 LD 区。 对所有独立先导 SNP 的 GTEx eQTL 分析在相关组织中产生了 31 个显着关联,其中一半以上不在紧邻先导 SNP 的基因处。结论 这项工作使用组合表型方法确定了包含红细胞性状多个独立关联信号的七个基因座,这可能会改善遗传相关性状的发现。 HBA1/2 基因座高度复杂的遗传结构只有通过纳入非裔美国人和西班牙裔/拉丁裔才得以揭示,这强调了扩大大型 GWAS 以纳入祖先多样化人群的持续重要性。
更新日期:2020-03-16
down
wechat
bug