Identification of potential key genes associated with severe pneumonia using mRNA‑seq

Abstract

This study aimed to identify the potential key genes associated with severe pneumonia using mRNA-seq. Nine peripheral blood samples from patients with severe pneumonia alone (SP group, n=3) and severe pneumonia accompanied with chronic obstructive pulmonary disease (COPD; CSP group, n=3), as well as volunteers without pneumonia (control group, n=3) underwent mRNA-seq. Based on the sequencing data, differentially expressed genes (DEGs) were identified by Limma package. Following the pathway enrichment analysis of DEGs, the genes that were differentially expressed in the SP and CSP groups were selected for pathway enrichment analysis and coexpression analysis. In addition, potential genes related to pneumonia were identified based on the information in the Comparative Toxicogenomics Database. In total, 645 and 528 DEGs were identified in the SP and CSP groups, respectively, compared with the normal controls. Among these DEGs, 88 upregulated genes and 80 downregulated genes were common between the two groups. The functions of the common DEGs were similar to those of the DEGs in the SP group. In the coexpression network, the commonly downregulated genes (including ND1, ND3, ND4L, and ND6) and the commonly upregulated genes (including TSPY6P and CDY10P) exhibited a higher degree. In addition, 131 DEGs (including ND1, ND3, ND6, MIR449A and TAS2R43) were predicted to be potential pneumonia-related genes. In conclusion, the present study demonstrated that the common DEGs may be associated with the progression of severe pneumonia.

A multicenter prospective study of comprehensive metagenomic and transcriptomic signatures for predicting outcomes of patients with severe community-acquired pneumonia

“…In blood, genes enriched in aminoacyl-tRNA biosynthesis were negatively modulated in the 30-day death group versus the surviving group, which was similar to the observation that genes related to aminoacyl-tRNA biosynthesis such as TRNS1 and TRNM were downregulated in patients with severe pneumonia in comparison with healthy individuals. 57 Besides, genes related to mitochondrial functions were also downregulated in non-survivors in our study, including electron transport chain: OXPHOS system in mitochondria, energy coupled proton transmembrane transport against electrochemical gradient, and mitochondrial cytochrome c oxidase. Previous findings demonstrated that genes associated with oxidative phosphorylation such as electron transport chain complex I, IV and V were downregulated in blood of non-surviving patients with sepsis caused by CAP.…”

Acidic leucine-rich nuclear phosphoprotein-32A expression contributes to adverse outcome in acute myeloid leukemia

“…There is a growing number of evidences demonstrated that aberrant gene expression, microRNA post-transcriptional regulation and DNA methylation played significant role in leukemogenesis (74)(75)(76)(77). Our study further discussed how overexpression of ANP32A affected prognosis from these three aspects.…”

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations

“…With the high prevalence of neural networks and Deep Learning-based algorithms in the Computational Biology, it is clear that the advantages of optimization in a highly non-linear space are welcomed improvements in biomedicine [1][2][3][4][5][6][7]. In Bioinformatics, significant effort has been committed to harnessing transcriptomic data for multiple analyses [7][8][9][10][11][12][13] especially cancer survival prognosis [14,15]. Faraggi and Simon [16] was the first study to use clinical information to predict prostate cancer survival through an artificial neural network model.…”