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Transcriptome signatures reveal candidate key genes in the whole blood of patients with lumbar disc prolapse.

ABSTRACT: The present study aimed to investigate differentially expressed genes (DEGs) in whole blood (WB) obtained from patients with lumbar disc prolapse (LDP) and healthy volunteers. A total of 8 patients with LDP and 8 healthy volunteers were recruited. An Agilent SurePrint G3 human gene expression microarray 8×60 K was used to perform the microarray analyses. R was employed to identify DEGs, which were then subjected to bioinformatics analysis, including a Gene Ontology (GO) analysis, Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network analysis. DEGs in the degenerative annulus fibrosis (AF) and nucleus pulposus (NP) compared with non-degenerative tissues were also identified based on microarray data and the intersections of the three were assessed. Furthermore, reverse transcription-quantitative (RT-q)PCR was performed to confirm the aberrant expression levels of selected DEGs in the WB of all subjects. A total of 161 DEGs between LDP patients and the healthy controls were identified (128 upregulated and 33 downregulated). These DEGs were enriched in 293 biological process, 36 cellular component and 21 molecular function GO terms, as well as in 24 KEGG pathways. The PPI network contained 4 submodules, and Toll-like receptor 4 had the highest degree centrality. A total of 22 DEGs were common to the three groups of DEGs. The RT-qPCR assay confirmed that the expression levels of cytochrome P450 family 27 subfamily A member 1, superoxide dismutase 2, protein disulfide isomerase family A member 4, FKBP prolyl isomerase 11 and ectonucleotide pyrophosphatase/phosphodiesterase 4 were significantly different between the patient group and the volunteer group. In conclusion, several genes were identified as potential biomarkers in WB that should be further explored in future studies to determine their potential application in the clinical treatment and diagnosis of LDP, and the present bioinformatics analysis revealed several GO terms, KEGG pathways and submodules of the PPI network that may be involved in LDP, although the exact mechanisms remain elusive.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6862187 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Transcriptome signatures reveal candidate key genes in the whole blood of patients with lumbar disc prolapse.

Wang Yi Y Dai Guogang G Li Lengtao L Liu Lijuan L Jiang Ling L Li Shengwu S Liao Shichuan S Wang Feng F Du Wanli W Li Yuewen Y

Experimental and therapeutic medicine 20191025 6

The present study aimed to investigate differentially expressed genes (DEGs) in whole blood (WB) obtained from patients with lumbar disc prolapse (LDP) and healthy volunteers. A total of 8 patients with LDP and 8 healthy volunteers were recruited. An Agilent SurePrint G3 human gene expression microarray 8×60 K was used to perform the microarray analyses. R was employed to identify DEGs, which were then subjected to bioinformatics analysis, including a Gene Ontology (GO) analysis, Kyoto Encyclopa ...[more]

PMID: 31777557

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Project description:BackgroundTo understand how Plasmodium falciparum malaria is controlled, it is essential to elucidate the transcriptomic responses of the human host in naturally-exposed populations. Various individual studies of the human transcriptomic responses to naturally transmitted P. falciparum infections have been reported with varying results. Multicohort gene expression analysis by aggregating data from diverse populations into a single analysis will increase the reproducibility and reliability of the results.MethodsIn this study, discovery cohorts GSE1124-GPL96, GSE34404, GSE117613, and validation cohort GSE35858 were obtained from the Gene Expression Omnibus. A meta-analysis using data from the multicohort studies was performed to identify the differentially expressed genes (DEGs) between malaria-infected and noninfected individuals using the MetaIntegrator R package. Subsequently, the protein-protein interaction (PPI) networks of the DEGs were constructed using Cytoscape software. Significant modules were selected, and the hub genes were identified using the CytoHubba and MCODE plug-ins. Multicohort WGCNA was conducted to find a correlation between modules and malaria infection. Furthermore, the immune cell profile of the peripheral blood in different groups was identified using ssGSEA.ResultsThese analyses reveal that neutrophil activation, neutrophil-mediated immunity, and neutrophil degranulation are involved in the human response to natural malaria infection. However, neutrophil cell enrichment and activation were not significantly different between mild malaria and severe malaria groups. Malaria infection also downregulates host genes in ribosome synthesis and protein translation and upregulates host cell division-related genes. Furthermore, immune cell profiling analysis shows that activated dendritic cells and type 2 T helper cells are upregulated, while activated B cells, immature B cells, and monocytes are downregulated in the malaria-infected patients relative to the noninfected individuals. Significantly higher enrichment of activated dendritic cell-related genes and significantly lower enrichment of monocyte-related genes are also observed in the peripheral blood of the severe malaria group than in the mild malaria group.ConclusionThese results reveal important molecular signatures of host responses to malaria infections, providing some bases for developing malaria control strategies and protective vaccines.

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Transcriptome signatures reveal candidate key genes in the whole blood of patients with lumbar disc prolapse.

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Transcriptome signatures reveal candidate key genes in the whole blood of patients with lumbar disc prolapse.

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