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Information Journal Paper

Title

Bioinformatics analysis of gene expression profile in women with major depressive disorder

Pages

  85-102

Abstract

 Introduction: Major depressive disorder (MDD) is a mental disorder occurring in women twice as much as men. In both sexes, the average age of people with MDD is roughly 25 years. Family, twin, and epidemiological studies all point to the multifactorial and polygenetic characteristics of the psychiatric traits of Major depressive disorder. The present study aimed to screen genes related to the pathogenesis of Major depressive disorder by Bioinformatics. Methods: Two hundred twenty-three different genes (DEGs) were expressed by comparing female patient samples with controls by TAC screening software using GSE98793 Microarray data from the GEO database. Hub genes were screened via STRING and Cytoscape, followed by KEGG enrichment analysis. Results: According to the obtained results, comparing female patients with control of 103 genes showed increased expression and 120 genes identified as decreased expression. The results of KEGG and panther pathway enrichment analysis comparing female patient samples with control showed that DEGs are mainly in the HIF-1 signaling pathway, FOXO signaling pathway, Th-17 cell differentiation pathway, pathway PI3K-Akt signaling, programmed cell death pathway (Ferptosis), and purine synthesis pathway were important. The results of this study revealed that IGF1R and ATM genes with increased expression and GMPS genes with decreased expression for women with this disease could also be beneficial for therapeutic purposes. Conclusion: The Key genes obtained by Microarray analysis provide essential clues for revealing the molecular mechanism and could be suitable and new candidates for future studies on major depression as well as optimization of treatment methods.

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    APA: Copy

    Esmaeili, Farnaz, & ZOLGHADRI, SAMANEH. (2021). Bioinformatics analysis of gene expression profile in women with major depressive disorder. ADVANCES IN COGNITIVE SCIENCE, 23(2 ), 85-102. SID. https://sid.ir/paper/958516/en

    Vancouver: Copy

    Esmaeili Farnaz, ZOLGHADRI SAMANEH. Bioinformatics analysis of gene expression profile in women with major depressive disorder. ADVANCES IN COGNITIVE SCIENCE[Internet]. 2021;23(2 ):85-102. Available from: https://sid.ir/paper/958516/en

    IEEE: Copy

    Farnaz Esmaeili, and SAMANEH ZOLGHADRI, “Bioinformatics analysis of gene expression profile in women with major depressive disorder,” ADVANCES IN COGNITIVE SCIENCE, vol. 23, no. 2 , pp. 85–102, 2021, [Online]. Available: https://sid.ir/paper/958516/en

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