Bioinformatics Analysis Reveals Novel Differentially Expressed Genes Between Ectopic and Eutopic Endometrium in Women with Endometriosis

Background Endometriosis is one of the chronic and prevalent diseases among women. There is limited knowledge about its pathophysiology at the cellular and molecular levels, causing a lack of a definite cure for this disease. In this study, differentially expressed genes (DEGs) between ectopic and paired eutopic endometrium in women with endometriosis were analyzed through bioinformatics analysis for better understanding of the molecular pathogenesis of endometriosis.

Gene expression data of ectopic and paired eutopic endometrium were taken from the Gene Expression Omnibus database. DEGs were screened by the Limma package in R with considering specific criteria. Then, the protein–protein interaction network was reconstructed between DEGs. The fast unfolding clustering algorithm was used to find sub-networks (modules). Finally, the three most relevant modules were selected and the functional and pathway enrichment analyses were performed for the selected modules.

A total of 380 DEGs (245 up-regulated and 135 down-regulated) were identified in the ectopic endometrium and compared with paired eutopic endometrium. The DEGs were predominantly enriched in an ensemble of genes encoding the extracellular matrix and associated proteins, metabolic pathways, cell adhesions and the innate immune system. Importantly, DPT, ASPN, CHRDL1, CSTA, HGD, MPZ, PED1A, and CLEC10A were identified as novel DEGs between the human ectopic tissue of endometrium and its paired eutopic endometrium.

The results of this study can open up a new window to better understanding of the molecular pathogenesis of endometriosis and can be considered for designing new treatment modalities. Similar content being viewed by others

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We thank Dr. Mohadeseh Zarei ghobadi (Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran) for assistance with methodology and for comments that greatly improved the manuscript. Funding No funding. Author information Authors and Affiliations Corresponding author Ethics declarations Conflict of interest The authors declare that they have no conflict of interest. Ethical approval Our study was a bioinformatic analysis and involving information freely available in the public domain (GEO database). The analysis of online datasets, from an open source, where the data are properly anonymized and informed consent was obtained at the time of original data collection, do not require ethical approval. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Sepideh Abdollahi (MS) is a PhD candidate, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Dr. Pantea Izadi (PhD) is an Associate Professor, Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Dr. Ghasem Azizi-Tabesh (PhD) is Reacher in Genomic Research center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Rights and permissions Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. About this article Cite this article Abdollahi, S., Izadi, P. & Azizi-Tabesh, G. Bioinformatics Analysis Reveals Novel Differentially Expressed Genes Between Ectopic and Eutopic Endometrium in Women with Endometriosis. J Obstet Gynecol India 73 (Suppl 1), 115–123 (2023). https://doi.org/10.1007/s13224-023-01749-9 Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1007/s13224-023-01749-9