Establishment of a Risk Score Model for Early Prediction of Severe H1N1 Influenza.

Siran Lin,Lingyun Shao,Yubing Peng,Wei Zhang,Yuzhen Xu,Jing Wu,Yan Gao,Wenhong Zhang

doi:10.3389/fcimb.2021.776840

Abstract

H1N1 is the most common subtype of influenza virus circulating worldwide and can cause severe disease in some populations. Early prediction and intervention for patients who develop severe influenza will greatly reduce their mortality. In this study, we conducted a comprehensive analysis of 180 PBMC samples from three published datasets from the GEO DataSets. Differentially expressed gene (DEG) analysis and weighted correlation network analysis (WGCNA) were performed to provide candidate DEGs for model building. Functional enrichment and CIBERSORT analyses were also performed to evaluate the differences in composition and function of PBMCs between patients with severe and mild disease. Finally, a risk score model was built using lasso regression analysis, with six genes (CX3CR1, KLRD1, MMP8, PRTN3, RETN and SCD) involved. The model performed moderately in the early identification of patients that develop severe H1N1 disease.

Highlights

H1N1 is one of the most widespread influenza A viruses in humans, which first appeared in Mexico and the United States in April 2009, and brought extensive influenza outbreaks (Garten et al, 2009)
A total of 172 Differentially expressed gene (DEG) were identified from the primary dataset, with 105 genes upregulated and 67 genes downregulated in patients with severe disease compared to patients with mild disease
The detailed distribution of all the DEGs on the two dimensions of -log10 (FDR) and log2 (FC) were shown through a volcano map (Figure 2B), with the top ten upregulated and downregulated genes marked in the figure

Summary

Introduction

H1N1 is one of the most widespread influenza A viruses in humans, which first appeared in Mexico and the United States in April 2009, and brought extensive influenza outbreaks (Garten et al, 2009). Patients infected with H1N1 generally show mild symptoms, some patients are severely affected, with viral pneumonia and sometimes multiple organ failure. Patients with severe influenza often miss the best intervention time because physicians cannot tell at an early stage whether the disease will develop in a severe form. High viral loads and excessive host response are thought to contribute to severe influenza (de Jong et al, 2006; Peiris et al, 2009). Previous studies have revealed that severe disease is often seen among persons aged > 65 years, infants, pregnant women, and individuals of any age with underlying health conditions (Bautista et al, 2010; Hui et al, 2010).

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Conclusion