With the global pandemic of COVID-19, the research on influenza virus has entered a new stage, but it is difficult to elucidate the pathogenesis of influenza disease. Genome-wide association studies (GWASs) have greatly shed light on the role of host genetic background in influenza pathogenesis and prognosis, whereas single-cell RNA sequencing (scRNA-seq) has enabled unprecedented resolution of cellular diversity and in vivo following influenza disease. Here, we performed a comprehensive analysis of influenza GWAS and scRNA-seq data to reveal cell types associated with influenza disease and provide clues to understanding pathogenesis. We downloaded two GWAS summary data, two scRNA-seq data on influenza disease. After defining cell types for each scRNA-seq data, we used RolyPoly and LDSC-cts to integrate GWAS and scRNA-seq. Furthermore, we analyzed scRNA-seq data from the peripheral blood mononuclear cells (PBMCs) of a healthy population to validate and compare our results. After processing the scRNA-seq data, we obtained approximately 70 000 cells and identified up to 13 cell types. For the European population analysis, we determined an association between neutrophils and influenza disease. For the East Asian population analysis, we identified an association between monocytes and influenza disease. In addition, we also identified monocytes as a significantly related cell type in a dataset of healthy human PBMCs. In this comprehensive analysis, we identified neutrophils and monocytes as influenza disease-associated cell types. More attention and validation should be given in future studies.

中文翻译：

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将单细胞 RNA 测序数据与全基因组关联分析数据相结合，识别甲型流感病毒感染和 COVID-19 中的重要细胞类型

随着COVID-19的全球大流行，流感病毒的研究进入了新阶段，但阐明流感疾病的发病机制却很困难。全基因组关联研究 (GWAS) 极大地揭示了宿主遗传背景在流感发病机制和预后中的作用，而单细胞 RNA 测序 (scRNA-seq) 使细胞多样性和流感疾病后体内的细胞多样性得到了前所未有的解决。在这里，我们对流感 GWAS 和 scRNA-seq 数据进行了全面分析，以揭示与流感疾病相关的细胞类型，并为了解发病机制提供线索。我们下载了两份 GWAS 摘要数据、两份关于流感疾病的 scRNA-seq 数据。在为每个 scRNA-seq 数据定义细胞类型后，我们使用 RolyPoly 和 LDSC-cts 来整合 GWAS 和 scRNA-seq。此外，我们分析了健康人群外周血单核细胞 (PBMC) 的 scRNA-seq 数据，以验证和比较我们的结果。处理 scRNA-seq 数据后，我们获得了大约 70,000 个细胞，并鉴定了多达 13 种细胞类型。对于欧洲人口分析，我们确定了中性粒细胞与流感疾病之间的关联。对于东亚人群分析，我们确定了单核细胞与流感疾病之间的关联。此外，我们还在健康人类 PBMC 数据集中鉴定出单核细胞是一种显着相关的细胞类型。在这项综合分析中，我们将中性粒细胞和单核细胞确定为与流感疾病相关的细胞类型。在未来的研究中应给予更多的关注和验证。