journal article·2021-04-08Open access

A Comparative Cross-Platform Meta-Analysis to Identify Potential Biomarker Genes Common to Endometriosis and Recurrent Pregnancy Loss

Pokhraj Guha, Shubhadeep Roychoudhury, Sobita Singha, Jogen C. Kalita, Adriana Kolesarova, Qazi Mohammad Sajid Jamal, Niraj Kumar Jha, Dhruv Kumar, Janne Ruokolainen, Kavindra Kumar Kesari

Applied Sciences· Volume 11· Issue 8

Abstract

Endometriosis is characterized by unwanted growth of endometrial tissue in different locations of the female reproductive tract. It may lead to recurrent pregnancy loss, which is one of the worst curses for the reproductive age group of human populations around the world. Thus, there is an urgent need for unveiling any common source of origin of both these diseases and connections, if any. Herein, we aimed to identify common potential biomarker genes of these two diseases via in silico approach using meta-analysis of microarray data. Datasets were selected for the study based on certain exclusion criteria. Those datasets were subjected to comparative meta-analyses for the identification of differentially expressed genes (DEGs), that are common to both diagnoses. The DEGs were then subjected to protein-protein networking and subsequent functional enrichment analyses for unveiling their role/function in connecting two diseases. From the analyses, 120 DEGs are reported to be significant out of which four genes have been found to be prominent. These include the CTNNB1, HNRNPAB, SNRPF and TWIST2 genes. The significantly enriched pathways based on the above-mentioned genes are mainly centered on signaling and developmental events. These findings could significantly elucidate the underlying molecular events in endometriosis-based recurrent miscarriages.
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Research context

OpenAlex topics: Endometriosis Research and Treatment · Bone Metabolism and Diseases

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Zoology, Garhbeta College, Paschim Medinipur 721127, India

Department of Life Science and Bioinformatics, Assam University, Silchar 788011, India

Department of Zoology, Gauhati University, Guwahati 781014, India

Faculty of Biotechnology and Food Sciences, Slovak University of Agriculture in Nitra, 94976 Nitra, Slovakia

Department of Health Informatics, College of Public Health and Health Informatics, Qassim University, Al Bukayriyah 52741, Saudi Arabia

Department of Biotechnology, School of Engineering & Technology, Sharda University, Greater Noida 201310, India

Amity Institute of Molecular Medicine and Stem Cell Research, Amity University, Uttar Pradesh, Noida 201313, India

Department of Applied Physics, Aalto University, 00076 Espoo, Finland

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