Dataset Information

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders.

ABSTRACT: Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool's rich library was used for comprehensive functional enrichment and pathway analysis which revealed "mRNA Splicing" and "SUMO E3 ligases SUMOylate target proteins" among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers.

SUBMITTER: Jha PK

PROVIDER: S-EPMC5125005 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders.

Jha Prabhash Kumar PK Vijay Aatira A Sahu Anita A Ashraf Mohammad Zahid MZ

Scientific reports 20161128

Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping bio ...[more]

PMID: 27892526

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Project description:Increasing evidence has suggested an association between carotid atherosclerosis (CAS) and periodontitis (PD); however, the mechanisms have not been fully understood. This study aims to investigate the shared genes and molecular mechanisms underlying the co-pathogenesis of CAS and PD. Gene Expression Omnibus (GEO) datasets GSE100927 and GSE10334 were downloaded, and differentially expressed genes (DEGs) shared by both datasets were identified. The functional enrichment analysis of these overlapping DEGs was then conducted. A protein-protein interaction (PPI) network was created using the STRING database and Cytoscape software, and PPI key genes were identified using the cytoHubba plugin. Then, weighted gene co-expression network analysis (WGCNA) was performed on GSE100927 and GSE10334, and the gene modules most correlated with CAS and PD were identified as key modules. The genes in key modules overlapping with PPI key genes were determined to be the key crosstalk genes. Subsequently, the key crosstalk genes were validated in three independent external datasets (GSE43292 [CAS microarray dataset], GSE16134 [PD microarray dataset], and GSE28829 [CAS microarray dataset]). In addition, the immune cell patterns of PD and CAS were evaluated by single-sample gene set enrichment analysis (ssGSEA), and the correlation of key crosstalk genes with each immune cell was calculated. Finally, we investigated the transcription factors (TFs) that regulate key crosstalk genes using NetworkAnalyst 3.0 platform. 355 overlapping DEGs of CAS and PD were identified. Functional enrichment analysis highlighted the vital role of immune and inflammatory pathways in CAS and PD. The PPI network was constructed, and eight PPI key genes were identified by cytoHubba, including CD4, FCGR2A, IL1B, ITGAM, ITGAX, LCK, PTPRC, and TNF. By WGCNA, the turquoise module was identified as the most correlated module with CAS, and the blue module was identified as the most correlated module with PD. Ultimately, ITGAM and LCK were identified as key crosstalk genes as they appeared both in key modules and PPI key genes. Expression levels of ITGAM and LCK were significantly elevated in the case groups of the test datasets (GSE100927 and GSE10334) and validation datasets (GSE43292, GSE16134, and GSE28829). In addition, the expression of multiple immune cells was significantly elevated in PD and CAS compared to controls, and the two key crosstalk genes were both significantly associated with CD4 T cells. Finally, SPI1 was identified as a potential key TF, which regulates the two key crosstalk genes. This study identified the key crosstalk genes and TF in PD and CAS, which provides new insights for further studies on the co-morbidity mechanisms of CAS and PD from an immune and inflammatory perspective.

Dataset Information

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders.

Publications

Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders.

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