Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39229380", "kind": "science-record", "revision": 4, "content_hash": "sha256:4ebb89142a5d17416c7145241c91aa3f97404b400a41348027fa8486954db990", "created_at": "2026-11-01T20:29:22Z", "updated_at": "2026-11-01T22:55:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.", "doi": "10.3389/fendo.2024.1440436", "pmid": "39229380", "authors": ["Wenqi Lv", "Han Xie", "Shengyu Wu", "Jiaqi Dong", "Yuanhui Jia", "Hao Ying"], "journal": "Frontiers in endocrinology", "year": 2024, "abstract": "Background: Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets.\nMethods: In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the \"Deseq2\" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta.\nResults: We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients.\nConclusion: Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.", "claims": [{"id": "claim-method", "statement": "Significantly differentially expressed genes (DEGs) were identified with the R package “DESeq2” under the criteria of p-adjustment < 0.05 and log2 | fold-change (FC) | >0.5.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39229380", "locator": "sections[5] \"Identification of differentially expressed genes with batch effect removal\" paragraph 2", "quote": "Significantly differentially expressed genes (DEGs) were identified with the R package “DESeq2” under the criteria of p-adjustment < 0.05 and log2 | fold-change (FC) | >0.5."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39229380", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 228 sPTB-related differentially expressed genes enriched in pathways including arachidonic acid and glutathione metabolism.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39229380", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 228 sPTB-related differentially expressed genes enriched in pathways including arachidonic acid and glutathione metabolism.", "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:39229380"], "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:GSE120480"], "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:GSE120480"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39229380", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2024.1440436", "sha256": "sha256:fb83555d18cd8fb091578e2ad7076a40482ec508162c95dec5225f98774546f4", "bytes": 61499, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2024.1440436", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11368757", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE120480", "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=GSE120480", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE120480", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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