DataSheet_3_Susceptibility identification for seasonal influenza A/H3N2 based on baseline blood transcriptome.csv (23.85 kB)
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DataSheet_3_Susceptibility identification for seasonal influenza A/H3N2 based on baseline blood transcriptome.csv

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posted on 2023-01-12, 05:46 authored by Jing Tang, Qiumei Xu, Kang Tang, Xiaoyan Ye, Zicheng Cao, Min Zou, Jinfeng Zeng, Xinyan Guan, Jinglin Han, Yihan Wang, Lan Yang, Yishan Lin, Kaiao Jiang, Xiaoliang Chen, Yang Zhao, Dechao Tian, Chunwei Li, Wei Shen, Xiangjun Du

Influenza susceptibility difference is a widely existing trait that has great practical significance for the accurate prevention and control of influenza.


Here, we focused on the human susceptibility to the seasonal influenza A/H3N2 of healthy adults at baseline level. Whole blood expression data for influenza A/H3N2 susceptibility from GEO were collected firstly (30 symptomatic and 19 asymptomatic). Then to explore the differences at baseline, a suite of systems biology approaches - the differential expression analysis, co-expression network analysis, and immune cell frequencies analysis were utilized.


We found the baseline condition, especially immune condition between symptomatic and asymptomatic, was different. Co-expression module that is positively related to asymptomatic is also related to immune cell type of naïve B cell. Function enrichment analysis showed significantly correlation with “B cell receptor signaling pathway”, “immune response−activating cell surface receptor signaling pathway” and so on. Also, modules that are positively related to symptomatic are also correlated to immune cell type of neutrophils, with function enrichment analysis showing significantly correlations with “response to bacterium”, “inflammatory response”, “cAMP−dependent protein kinase complex” and so on. Responses of symptomatic and asymptomatic hosts after virus exposure show differences on resisting the virus, with more effective frontline defense for asymptomatic hosts. A prediction model was also built based on only baseline transcription information to differentiate symptomatic and asymptomatic population with accuracy of 0.79.


The results not only improve our understanding of the immune system and influenza susceptibility, but also provide a new direction for precise and targeted prevention and therapy of influenza.