Multi-ancestry genome-wide association studies (GWASs) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-sequencing data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172,385 cells); then, we tested whether variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWASs of 31 diseases and complex traits (average n ∼ 90,000 and ∼ 267,000 in EAS and EUR, respectively). We observed that ancDE genes tended to be cell-type specific and enriched in genes interacting with the environment and in variants with ancestry-specific disease effect sizes, which suggests cell-type-specific, gene-by-environment interactions shared between regulatory and disease architectures. Finally, we illustrated how different environments might have led to ancestry-specific myeloid cell leukemia 1 (MCL1) expression in B cells and ancestry-specific allele effect sizes in lymphocyte count GWASs for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets from diverse ancestries are required to improve our understanding of human diseases.

中文翻译：

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跨祖先表达差异的基因在祖先特异性疾病效应中富集，这可能是由于基因与环境的相互作用


多祖先全基因组关联研究 （GWASs） 强调了具有祖先特异性效应大小的变异的存在。了解这些祖先特异性影响发生的位置和原因对于了解人类疾病和复杂特征的遗传基础至关重要。在这里，我们通过利用 21 名具有东亚 （EAS） 血统的个体和 23 名具有欧洲 （EUR） 血统的个体（172,385 个细胞）的外周血单核细胞中的单细胞 RNA 测序数据，在细胞类型水平上表征了跨祖先差异表达的基因 （ancDE 基因）;然后，我们通过利用 31 种疾病和复杂性状的祖先匹配的 GWAS（EAS 和 EUR 中的平均 n ∼ 90,000 和 ∼ 267,000）测试了围绕这些基因的变异是否在具有祖先特异性效应大小的疾病变异中富集。我们观察到 ancDE 基因往往是细胞类型特异性的，并且富含与环境相互作用的基因以及具有祖先特异性疾病效应大小的变体，这表明细胞类型特异性、基因-环境相互作用在调节和疾病结构之间共享。最后，我们说明了不同的环境如何导致 B 细胞中祖先特异性髓系细胞白血病 1 （MCL1） 表达以及 MCL1 周围变异的淋巴细胞计数 GWAS 中的祖先特异性等位基因效应大小。我们的结果表明，需要来自不同祖先的大型单细胞和 GWAS 数据集来提高我们对人类疾病的理解。