Bioinformatics analysis of microarray data to identify hub genes, as diagnostic biomarker of HELLP syndrome: System biology approach.

BACKGROUND

HELLP syndrome is one of the disorders characterized by hemolysis, increased liver enzymes and decreased platelet count. So far, many molecular pathways and genes have been identified in relation to the pathogenesis of this syndrome; however, the main cause of the incidence and progression of the disease has not been identified. Using the biological system approach is a way to target patients by identifying genes and molecular pathways. In this study, we investigated genes and important molecular factors in the pathogenesis of HELLP syndrome.

MATERIAL AND METHODS

In this study, the microarray dataset was downloaded from Gene Expression Omnibus (GEO) database and analyzed using the GEO2R online tool for identifying differentially expressed genes (DEGs). Enrichment analysis of DEGs was evaluated using the Enrichr database. Then, protein-protein interaction (PPI) networks were constructed via the STRING database; they were visualized by Cytoscape. Then the STRING database was used to construct PPI networks. The hub genes were recognized using the cytoHubba. Ultimately, the interaction of the miRNA-hub genes and drug-hub genes were also evaluated.

RESULT

After analysis, it was found that some genes with the highest degree of connectivity are involved in the pathogenesis of HELLP syndrome, which are known as the hub genes. These genes are as follows: KIT, JAK2, LEP, EP300, HIST1H4L, HIST1H4F, HIST1H4H, MMP9, THBS2, and ADAMTS3. Has-miR-34a-5p was also most associated with hub genes.

CONCLUSION

Finally, it can be said, that the identification of genes and molecular pathways in HELLP syndrome can be helpful in identifying the pathogenesis pathways of the disease, and designing therapeutic targets.