Deciphering crucial genes in pelvic inflammatory disease and their relationship with infertility through systems biology studies

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Abstract

Background. Pelvic inflammatory disease (PID) is an infection of the female reproductive system. PID is usually caused by infection with Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG). Women with PID have an increased risk of becoming infertility. The aim of this study was to determine the molecular mechanisms that influence infertility and embryonic development in PID with CT and NG infections.

Materials and methods. Microarray data were extracted from the Gene Expression Omnibus (GEO), and the protein-protein interaction network was constructed using Cytoscape software. Network analysis was performed to identify hub-bottlenecks and sub-networks. The functional mechanisms for critical genes were identified using the webgestalt server. Results. RPL13, EEF1G, JAK2, MYC, IL7R, CD74, IMPDH2, and NFAT5 were identified as crucial genes in protein-protein interactions and gene regulatory networks in CT and NG infections of PID. Ribosome, hematopoietic cell lineage, platelet activation, and Chagas disease, JAK-STAT pathway, eukaryotic translation elongation, Rap1 pathway, apoptosis, protein processing in the endoplasmic reticulum, progesterone-mediated oocyte maturation, and Epstein–Barr virus infection were identified as significant signaling pathways involving in CT and NG infections.

Conclusion. Our model suggests novel critical genes, and functional pathways involved in CT and NG infections, establishing a link between these infections and infertility. However, further studies in vitro and in vivo are needed.

About the authors

F. Saberi

Shahid Beheshti University of Medical Sciences

Email: Hakimehzali@gmail.com

Student Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Cellular and Molecular Biology Research Center

Iran, Islamic Republic of, Tehran

Z. Dehghan

Shiraz University of Medical Sciences

Email: Hakimehzali@gmail.com

Department of Comparative Biomedical Sciences, School of Advanced Medical Sciences and Technologies, Autoimmune Diseases Research Center

Iran, Islamic Republic of, Shiraz

T. Pilehchi

Shahid Beheshti University of Medical Sciences

Email: Hakimehzali@gmail.com

Student Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Cellular and Molecular Biology Research Center

Iran, Islamic Republic of, Tehran

Sh. Mehdinejadiani

University of Calgary

Email: Hakimehzali@gmail.com

Faculty of Veterinary Medicine, University of Calgary

Canada, Calgary

Z. Taheri

Pavia University

Email: Hakimehzali@gmail.com

Department of Biology and Biotechnology

Italy, Pavia

Hakimeh Zali

Shahid Beheshti University of Medical Sciences

Author for correspondence.
Email: Hakimehzali@gmail.com

PhD, Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine

Iran, Islamic Republic of, Tehran

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Supplementary files

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1. JATS XML
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2. Figure 1. Workflow of study

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3. Figure 2. PPIN. A) The results of shared nodes with the highest degree and betweenness Centrality in PPIN of CT (A) and NG (B). The nodes with big size and dark color have highest degree

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4. Figure 3. The subnetwork obtained from the MCODE app with score > 3 in PPIN CT (A) and NG (B)

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5. Figure 4. GRN. The results of shared nodes with the highest degree and betweenness Centrality in GRN of CT (A), NG (B), and (C) share nodes between GRN of CT and NG infections. Nodes with bigger sizes have the highest degree. The miRNAs, TFs, and genes are shown with yellow, pink, and yellow colors, respectively

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Copyright (c) 2025 Saberi F., Dehghan Z., Pilehchi T., Mehdinejadiani S., Taheri Z., Zali H.

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