Identification of Potential Molecular Mechanism Related to Infertile Endometriosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35419445", "kind": "science-record", "revision": 4, "content_hash": "sha256:94483a0d372f188e87937a5bc85ee9f46015367b387f972ca5f3cf3afdb43e6b", "created_at": "2026-11-01T18:14:14Z", "updated_at": "2026-11-01T22:06:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Potential Molecular Mechanism Related to Infertile Endometriosis.", "doi": "10.3389/fvets.2022.845709", "pmid": "35419445", "authors": ["Xiushen Li", "Li Guo", "Weiwen Zhang", "Junli He", "Lisha Ai", "Chengwei Yu", "Hao Wang", "Weizheng Liang"], "journal": "Frontiers in veterinary science", "year": 2022, "abstract": "Objectives: In this research, we aim to explore the bioinformatic mechanism of infertile endometriosis in order to identify new treatment targets and molecular mechanism.\nMethods: The Gene Expression Omnibus (GEO) database was used to download MRNA sequencing data from infertile endometriosis patients. The \"limma\" package in R software was used to find differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis. The intersection genes of the most disease-related modular genes and DEGs are called gene set 1. To clarify the molecular mechanisms and potential therapeutic targets for infertile endometriosis, we used Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) enrichment, Protein-Protein Interaction (PPI) networks, and Gene Set Enrichment Analysis (GSEA) on these intersecting genes. We identified lncRNAs and miRNAs linked with infertility and created competing endogenous RNAs (ceRNA) regulation networks using the Human MicroRNA Disease Database (HMDD), mirTarBase database, and LncRNA Disease database.\nResults: Firstly, WGCNA enrichment analysis was used to examine the infertile endometriosis dataset GSE120103, and we discovered that the Meorangered1 module was the most significantly related with infertile endometriosis. The intersection genes were mostly enriched in the metabolism of different amino acids, the cGMP-PKG signaling pathway, and the cAMP signaling pathway according to KEGG enrichment analysis. The Meorangered1 module genes and DEGs were then subjected to bioinformatic analysis. The hub genes in the PPI network were performed KEGG enrichment analysis, and the results were consistent with the intersection gene analysis. Finally, we used the database to identify 13 miRNAs and two lncRNAs linked to infertility in order to create the ceRNA regulatory network linked to infertile endometriosis.\nConclusion: In this study, we used a bioinformatics approach for the first time to identify amino acid metabolism as a possible major cause of infertility in patients with endometriosis and to provide potential targets for the diagnosis and treatment of these patients.", "claims": [{"id": "claim-method", "statement": "Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35419445", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Weighted gene co-expression network analysis (WGCNA) was used to classify genes into modules, further obtained the correlation coefficient between the modules and infertility endometriosis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35419445", "locator": "sections[20] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The MEorangered1 module had the strongest relationship with infertile endometriosis (R = 0.93, p = 2e-8).", "kind": "quantitative", "target": {"value": 0.93, "unit": "correlation coefficient", "tolerance": null, "source": "As shown in Figure 2B, the MEorangered1 module (Supplementary Table 2) had the strongest relationship with infertile endometriosis (R = 0.93, p = 2e-8)."}, "evidence": [{"asset": "source:pmid:35419445", "locator": "sections[12] \"Results of the WGCNA\" paragraph 2", "quote": "As shown in Figure 2B, the MEorangered1 module (Supplementary Table 2) had the strongest relationship with infertile endometriosis (R = 0.93, p = 2e-8)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The MEorangered1 module had the strongest relationship with infertile endometriosis (R = 0.93, p = 2e-8).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35419445"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE120103"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE120103"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35419445", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fvets.2022.845709", "sha256": "sha256:9239789db13ef768a1d783ca1695c3c13edc91083eeb88f3a6c76418d33c0bf6", "bytes": 36613, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fvets.2022.845709", "version": null, "note": "Full article fetched from PMC; 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