Prediction of Shared Target Genes in Cardiac Complications Induced by IAV and SARS-CoV-2 Using Machine Learning and Validation in H1N1 Infection Models

Yuansheng LIAO; Heng LI; Yun LIAO; Yunguang HU; Anguo YIN; Meijun KONG; Longding LIU; Ying ZHANG

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Prediction of Shared Target Genes in Cardiac Complications Induced by IAV and SARS-CoV-2 Using Machine Learning and Validation in H1N1 Infection Models

VernacularTitle:机器学习预测IAV和SARS-CoV-2感染引起心脏并发症中的共同靶点基因及H1N1感染模型验证
Author: Yuansheng LIAO ¹ ; Heng LI ; Yun LIAO ; Yunguang HU ; Anguo YIN ; Meijun KONG ; Longding LIU ; Ying ZHANG
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1. 中国医学科学院 & 北京协和医学院医学生物学研究所,云南昆明 650118
Keywords: Influenza A virus; SARS-CoV-2; Heart disease; Machine learning
From: Journal of Kunming Medical University 2025;46(5):75-88
CountryChina
Language:Chinese
Abstract: Objective To predict and preliminarily validate potential shared key genes involved in cardiac complications caused by influenza A virus(IAV)and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infections.Methods Differentially expressed genes(DEGs)associated with cardiac complications were obtained from the Gene Expression Omnibus(GEO)database.A hierarchical intersection strategy was applied.First,cardiac complication related DEGs were overlapped with 2 independent virus related gene sets:3 454 human genes linked to IAV infection in GeneCards and 333 human protein-coding genes interacting with SARS-CoV-2 in the Human Protein Atlas.The 2 overlap results were then intersected to yield 22 hub genes.Lasso regression,random forest(RF)and support vector machine algorithms(SVM)were employed to refine this list.Predicted genes were validated in vitro in H1N1-infected human cardiomyocyte AC16 cells and in vivo in IFITM3 knockout mice challenged with H1N1,assessing transcriptional changes.Results A total of 22 hub genes were identified through integrative bioinformatics analysis.Application of the 3 machine learning algorithms resulted in 5 common key genes:ACE2,TBK1,NUP210,PUSL1,and MEPCE.In vitro infection of AC16 cells with H1N1 revealed dynamic transcriptional changes in all 5 genes post-infection(P<0.05).In vivo experiments using H1N1-infected IFITM3 knockout mice confirmed the dynamic mRNA expression changes of these 5 genes,consistent with the in vitro results(P<0.05).Conclusion By combining multilayered bioinformatics analysis with 3 machine learning approaches,5 common key genes are identified:ACE2,TBK1,NUP210,PUSL1 and MEPCE.Validation in H1N1 infection models confirms their relevance to IAV-induced cardiac complications.