Shared diagnostic genes and potential mechanisms between polycystic ovary syndrome and recurrent miscarriage revealed by integrated transcriptomics analysis and machine learning.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39398336", "kind": "science-record", "revision": 1, "content_hash": "sha256:955b397d593d1b524798609e8967aed264d0e9f356576d4d25dd7c599c14b8be", "created_at": "2026-11-01T20:29:37Z", "updated_at": "2026-11-01T20:29:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Shared diagnostic genes and potential mechanisms between polycystic ovary syndrome and recurrent miscarriage revealed by integrated transcriptomics analysis and machine learning.", "doi": "10.3389/fendo.2024.1335106", "pmid": "39398336", "authors": ["Juanjuan He", "Ahui Liu", "Haofei Shen", "Yanbiao Jiang", "Min Gao", "Liulin Yu", "Wenjing Du", "Xuehong Zhang", "Fen Fu"], "journal": "Frontiers in endocrinology", "year": 2024, "abstract": "Objective: More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear.\nMethods: Based on the GEO database, we downloaded the PCOS (GSE10946, GSE6798 and GSE137684) and RSA (GSE165004, GSE26787 and GSE22490) datasets and performed differential analysis, weighted gene co-expression network (WGCNA), functional enrichment, and machine learning, respectively, on the datasets of the two diseases, Nomogram and integrated bioinformatics analysis such as immune infiltration analysis. Finally, the reliability of the diagnostic gene was verified by external verification and collection of human specimens.\nResults: In this study, PCOS and RSA datasets were obtained from Gene Expression Omnibus (GEO) database, and a total of 23 shared genes were obtained by differential analysis and WGCNA analysis. GO results showed that the shared genes were mainly enriched in the functions of lipid catabolism and cell cycle transition (G1/S). DO enrichment revealed that shared genes are mainly involved in ovarian diseases, lipid metabolism disorders and psychological disorders. KEGG analysis showed significant enrichment of Regulation of lipolysis in adipocytes, Prolactin signaling pathway, FoxO signaling pathway, Hippo signaling pathway and other pathways. A diagnostic gene FAM166 B was obtained by machine learning and Nomogram screening, which mainly played an important role in Cellular component. GSEA analysis revealed that FAM166B may be involved in the development of PCOS and RSA by regulating the cell cycle, amino acid metabolism, lipid metabolism, and carbohydrate metabolism. CIBERSORT analysis showed that the high expression of FAM166 B was closely related to the imbalance of multiple immune cells. Further verification by qPCR suggested that FAM166 B could be used as a common marker of PCOS and RSA.\nConclusions: In summary, this study identified FAM166B as a common biomarker for PCOS and RSA, and conducted in-depth research and analysis of this gene, providing new data for basic experimental research and early prognosis, diagnosis and treatment of clinical diseases.", "claims": [{"id": "claim-data-access", "statement": "Publicly available datasets used in this study can be downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The PCOS group includes three datasets with GSE10946 and GSE6798 and GSE137684. GSE165004 and GSE26787 and GSE22490 are involved in the RSA group. If necessary, please contact the corresponding author to obtain the original data.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39398336", "locator": "sections[30] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets used in this study can be downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The PCOS group includes three datasets with GSE10946 and GSE6798 and GSE137684. GSE165004 and GSE26787 and GSE22490 are involved in the RSA group. If necessary, please contact the corresponding author to obtain the original data."}], "state": "complete"}, {"id": "claim-target-result", "statement": "FAM166B was identified as the best shared diagnostic gene for PCOS and RSA.", "kind": "quantitative", "target": {"value": 0.772, "unit": "auc", "tolerance": null, "source": "In addition, in the external validation cohorts of PCOS and RSA, the expression level of FAM166B was consistent with that of the training group ( Figures 6C, G ), and had higher diagnostic performance in the validation cohorts of PCOS and RSA (AUC = 0.772, 0.859) ( Figures 6D, H )."}, "evidence": [{"asset": "source:pmid:39398336", "locator": "sections[22] \"Identification and verification of shared diagnostic genes\" paragraph 2", "quote": "Finally, FAM166B was identified as the best shared diagnostic gene."}, {"asset": "source:pmid:39398336", "locator": "sections[22] \"Identification and verification of shared diagnostic genes\" paragraph 4", "quote": "In addition, in the external validation cohorts of PCOS and RSA, the expression level of FAM166B was consistent with that of the training group ( Figures 6C, G ), and had higher diagnostic performance in the validation cohorts of PCOS and RSA (AUC = 0.772, 0.859) ( Figures 6D, H )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "FAM166B was identified as the best shared diagnostic gene for PCOS and RSA.", "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:39398336"], "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:GSE10946"], "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:GSE10946"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39398336", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2024.1335106", "sha256": "sha256:352780fabb0e894de6c8dfe7a9f1a20bf8f0c2521c2b8c75b3592fb416e8e56b", "bytes": 59491, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2024.1335106", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11466764", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10946", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10946", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10946", "version": null, "note": "Publicly available datasets used in this study can be downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The PCOS group includes three datasets with GSE10946 and GSE6798 and GSE137684. GSE165004 and GSE26787 and GSE22490 are involved in the RSA group. If necessary, please contact the corresponding author to obtain the original data.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets used in this study can be downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The PCOS group includes three datasets with GSE10946 and GSE6798 and GSE137684. GSE165004 and GSE26787 and GSE22490 are involved in the RSA group. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE10946", "GSE6798", "GSE137684", "GSE165004", "GSE26787", "GSE22490"], "resolved_accessions": ["GSE10946", "GSE6798", "GSE137684", "GSE165004", "GSE26787", "GSE22490"], "statements": ["Publicly available datasets used in this study can be downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). The PCOS group includes three datasets with GSE10946 and GSE6798 and GSE137684. GSE165004 and GSE26787 and GSE22490 are involved in the RSA group. If necessary, please contact the corresponding author to obtain the original data."], "basis": "The paper names GSE10946, GSE6798, GSE137684, GSE165004, GSE26787, GSE22490 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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Further verification by qPCR suggested that FAM166 B could be used as a c", "ator for freezing and storage for subsequent RT-qPCR. In addition, chorionic villus tissue sample", "igerated tube at -80°C for use in subsequent RT-qPCR. The study was approved by the Ethics Commit", "due to the small sample size. Validation of RT-qPCR in human tissues. (A) The expression level o"], "order_basis": "paper_text_order:1992", "id": "assay:1"}]}