Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation

Abstract

One of the key barriers for early identification and intervention of severe influenza cases is a lack of reliable immunologic indicators. In this study, we utilized differentially expressed genes screening incorporating weighted gene co‐expression network analysis in one eligible influenza GEO data set ( GSE111368 ) to identify hub genes associated with clinical severity. A total of 10 genes ( PBI , MMP8 , TCN1 , RETN , OLFM4 , ELANE , LTF , LCN2 , DEFA4 and HP ) were identified. Gene set enrichment analysis (GSEA) for single hub gene revealed that these genes had a close association with antimicrobial response and neutrophils activity. To further evaluate these genes' ability for diagnosis/prognosis of disease developments, we adopted double validation with (a) another new independent data set ( GSE101702 ); and (b) plasma samples collected from hospitalized influenza patients. We found that 10 hub genes presented highly correlation with disease severity. In particular, BPI and MMP8 encoding proteins in plasma achieved higher expression in severe and dead cases, which indicated an adverse disease development and suggested a frustrating prognosis. These findings provide new insight into severe influenza pathogenesis and identify two significant candidate genes that were superior to the conventional clinical indicators. These candidate genes or encoding proteins could be biomarker for clinical diagnosis and therapeutic targets for severe influenza infection.

Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

“…Fatty acid metabolism, α-linolenic acid metabolism and arachidonic acid metabolism inhibit the initiation and metastasis of cancer (Fig. 5 B) [ 20 , 21 ].…”

Cycling and activated CD8+ T lymphocytes and their association with disease severity in influenza patients

“…The genes expression within cell cycle module displayed obvious differences between moderate and severe influenza infection [ 4 ]. Since the cell cycle has been widely believed to be required for cellular homeostasis [ 17 ], changes of several critical transition points in cell cycle pathways could be a clear immune signature for disease severity.…”

“…Several viral, host and environmental factors impact disease severity leading to increased hospitalization and mortality [2]. Some studies identified that immune response, neutrophil function and cell cycle, as three distinct pathogenic mechanisms, were linked to disease progression of influenza infection [3][4][5]. T lymphocyte responses correlated with protection following influenza infection could be a sign to predict the disease severity [6].…”

Predictive role of bactericidal/permeability-increasing protein and C-reactive protein in a personalized approach to the treatment of children with acute pneumonia

“…In this regard, it is very promising to determine BPI in plasma as a marker of systemic inflammation and bacterial infection. Additionally, BPI is an endogenous inhibitor of angiogenesis by inducing apoptosis of vascular endothelial cells [19,20].…”