Department of Epidemiology, National Vaccine Innovation Platform, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Department of Mathematics, School of Science, Xi'an Shiyou University, Xi'an, China.
Brief Funct Genomics. 2024 Mar 20;23(2):110-117. doi: 10.1093/bfgp/elad025.
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.
随着 COVID-19 全球大流行，流感病毒的研究进入了一个新阶段，但阐明流感疾病的发病机制仍然具有挑战性。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）则使我们能够以前所未有的分辨率研究流感疾病后的细胞多样性和体内情况。在这里，我们对流感 GWAS 和 scRNA-seq 数据进行了综合分析，以揭示与流感疾病相关的细胞类型，并为理解发病机制提供线索。我们下载了两份 GWAS 汇总数据和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 整合了 GWAS 和 scRNA-seq。此外，我们还分析了来自健康人群外周血单核细胞（PBMCs）的 scRNA-seq 数据，以验证和比较我们的结果。在处理 scRNA-seq 数据后，我们获得了大约 70,000 个细胞，并鉴定出多达 13 种细胞类型。对于欧洲人群分析，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 PBMCs 的数据集确定了单核细胞是一个与流感疾病显著相关的细胞类型。在这项综合分析中，我们确定了中性粒细胞和单核细胞是与流感疾病相关的细胞类型。未来的研究应该给予更多的关注和验证。
