Meta-analysis of high-throughput transcriptomics uncovers aberrant endometrial microRNAmessengerRNA networks in recurrent implantation failure

Objectives: Recurrent implantation failure (RIF) poses a significant challenge in assisted reproductive technology, with a poorly understood molecular mechanism. Endometrial receptivity, central to successful embryo implantation, is governed by various factors, including intricate gene regulatory networks. Emerging evidence implicates dysregulated messenger ribonucleic acid (mRNA) and microRNA (miRNA) interactions in the pathogenesis of RIF, yet comprehensive network-level analysis remains scarce. This meta-analysis systematically integrates mRNA and miRNA expression profiles in the endometrial tissue of RIF women to elucidate the molecular basis of the disease. Materials and Methods: We analyzed two mRNA GEO series (GSE) datasets (GSE26787, GSE111974) and two miRNA datasets (GSE71332, GSE108966), encompassing a total of 168 endometrial tissue samples (RIF and controls). Data were pre-processed to correct for batch effects, and differential expression analysis was performed using robust statistical methods. Meta-analytic approaches were applied to identify high-confidence differentially expressed mRNAs (DE-mRNAs) and miRNAs (DE-miRNAs) across the datasets. Validated miRNA–mRNA interactions were retrieved and visualized using network analysis tools. Results: We identified 14 key miRNAs and 1670 dysregulated mRNAs from the datasets. Integration revealed a miRNA–mRNA interaction network comprising 2,641 validated interactions (1,086 unique mRNAs and 14 unique miRNAs), with 12 hub genes identified. Pathway enrichment analysis highlighted the phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling pathway as the most significantly enriched, underscoring its central role in RIF pathogenesis. The key miRNAs were found to be associated with angiogenesis, immune modulation, and stromal cell function. Conclusion: This meta-analysis provides a comprehensive, network-based perspective on the miRNA–mRNA regulatory landscape in RIF. The PI3K-AKT pathway emerged as the central node of dysregulation and warrants further investigation. This work lays the foundation for experimentally validating our findings, aiming at improving pregnancy outcomes in women with a history of RIF.

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Publication Details

Journal
Journal of Reproductive Healthcare and Medicine
Published
2025-10-28
DOI
https://doi.org/10.25259/jrhm_29_2025
Citations
1
Primary Topic
Reproductive System and Pregnancy
Type
article
Field-Weighted Citation Impact
0.80
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article

Meta-analysis of high-throughput transcriptomics uncovers aberrant endometrial microRNAmessengerRNA networks in recurrent implantation failure

Ashutosh Sahu, Partha Sarathi Paul, Koel Chaudhury, Imon Mitra et al.
1 citations
Journal of Reproductive Healthcare and Medicine
Reproductive System and Pregnancy
0.80
article

Meta-analysis of high-throughput transcriptomics uncovers aberrant endometrial microRNAmessengerRNA networks in recurrent implantation failure

Ashutosh Sahu, Partha Sarathi Paul, Koel Chaudhury, Imon Mitra, Bishnupriya Saha
article en
1 citations

Abstract

Objectives: Recurrent implantation failure (RIF) poses a significant challenge in assisted reproductive technology, with a poorly understood molecular mechanism. Endometrial receptivity, central to successful embryo implantation, is governed by various factors, including intricate gene regulatory networks. Emerging evidence implicates dysregulated messenger ribonucleic acid (mRNA) and microRNA (miRNA) interactions in the pathogenesis of RIF, yet comprehensive network-level analysis remains scarce. This meta-analysis systematically integrates mRNA and miRNA expression profiles in the endometrial tissue of RIF women to elucidate the molecular basis of the disease. Materials and Methods: We analyzed two mRNA GEO series (GSE) datasets (GSE26787, GSE111974) and two miRNA datasets (GSE71332, GSE108966), encompassing a total of 168 endometrial tissue samples (RIF and controls). Data were pre-processed to correct for batch effects, and differential expression analysis was performed using robust statistical methods. Meta-analytic approaches were applied to identify high-confidence differentially expressed mRNAs (DE-mRNAs) and miRNAs (DE-miRNAs) across the datasets. Validated miRNA–mRNA interactions were retrieved and visualized using network analysis tools. Results: We identified 14 key miRNAs and 1670 dysregulated mRNAs from the datasets. Integration revealed a miRNA–mRNA interaction network comprising 2,641 validated interactions (1,086 unique mRNAs and 14 unique miRNAs), with 12 hub genes identified. Pathway enrichment analysis highlighted the phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling pathway as the most significantly enriched, underscoring its central role in RIF pathogenesis. The key miRNAs were found to be associated with angiogenesis, immune modulation, and stromal cell function. Conclusion: This meta-analysis provides a comprehensive, network-based perspective on the miRNA–mRNA regulatory landscape in RIF. The PI3K-AKT pathway emerged as the central node of dysregulation and warrants further investigation. This work lays the foundation for experimentally validating our findings, aiming at improving pregnancy outcomes in women with a history of RIF.

Journal of Reproductive Healthcare and MedicineVol. 6
Indian Institute of Technology Kharagpur (IN)
Openalex Percentile: Top 22%
Reproductive System and Pregnancy
0.80
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