Identification of a valuable gene network for the diagnosis and treatment of non-obstructive azoospermia: in-silico analyses - experimental research

Mohammad Reza Zabihi; Narges Norouzkhani; Samad Karkhah; Mohammad Akhoondian

doi:10.1097/MS9.0000000000001358

Identification of a valuable gene network for the diagnosis and treatment of non-obstructive azoospermia: in-silico analyses - experimental research

Ann Med Surg (Lond). 2023 Nov 1;85(12):5941-5951. doi: 10.1097/MS9.0000000000001358. eCollection 2023 Dec.

Authors

Mohammad Reza Zabihi¹, Narges Norouzkhani², Samad Karkhah^{3

4}, Mohammad Akhoondian⁵

Affiliations

¹ Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran.
² Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad.
³ Department of Medical-Surgical Nursing, School of Nursing and Midwifery.
⁴ Burn and Regenerative Medicine Research Center.
⁵ Department of Physiology, School of Medicine, Cellular and The Molecular Research Center, Guilan University of Medical Science, Rasht, Iran.

Abstract

Introduction: Non-obstructive azoospermia (NOA) is an etiology of infertility in men. NOA may have various classifications; however, hypogonadotropic hypogonadism can be regarded as a class of NOA associated with genetic factors. Former studies have shown that noncoding RNA (ncRNA) plays an essential role in NOA incidence, but few studies have been performed on the NOA-related ncRNA interaction network. In the current study, genes, NOA-related microRNA (miRNA), and circular RNA (circRNA) were found by bioinformatics methods to offer a new perspective on NOA treatment.

Methods: The gonadotropin-releasing hormone receptor (GnRHR)-related protein-protein interaction (PPI) network was extracted by searching in 'string-database'. GO, KEGG, and Enrichr databases were used to identify pathways, molecular function, and biological processing. Four databases, including TargetScan, mirDIP, miRmap, and miRWalk, were used to extract miRNAs. At last, the circ2GO, circBase, and literature were used to identify circRNAs and their genes.

Results: The current study identified the four proteins associated with the GnRHR signaling; eight shared miRNAs that affect the expression of found proteins and 25 circRNAs and their origin genes that regulate the miRNAs' function.

Conclusion: The two miRNAs, hsa-miR-134-3p and hsa-miR-513C-3p, the three genes, VCAN, NFATC3, and PRDM5, and their associated circRNAs can perform as a valuable gene network in the diagnosis and treatment of NOA pathogenesis.

Keywords: GNRHR protein; azoospermia; bioinformatics; circular RNA; microRNAs.