Association of the LEP gene with immune infiltration as a diagnostic biomarker in preeclampsia.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37635936", "kind": "science-record", "revision": 4, "content_hash": "sha256:81f897c06e0068efbca973db52dab0ecd19f30f6434b5894424afb86e4551180", "created_at": "2026-11-01T19:02:25Z", "updated_at": "2026-11-01T22:52:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Association of the LEP gene with immune infiltration as a diagnostic biomarker in preeclampsia.", "doi": "10.3389/fmolb.2023.1209144", "pmid": "37635936", "authors": ["Shaorong Chen", "Yumin Ke", "Weihong Chen", "Sijia Wu", "Xuanxuan Zhuang", "Qiuya Lin", "Qirong Shi", "Zhuna Wu"], "journal": "Frontiers in molecular biosciences", "year": 2023, "abstract": "Objective: Preeclampsia (PE) is a serious condition in pregnant women and hence an important topic in obstetrics. The current research aimed to recognize the potential and significant immune-related diagnostic biomarkers for PE. Methods: From the Gene Expression Omnibus (GEO) data sets, three public gene expression profiles (GSE24129, GSE54618, and GSE60438) from the placental samples of PE and normotensive pregnancy were downloaded. Differentially expressed genes (DEGs) were selected and determined among 73 PE and 85 normotensive control pregnancy samples. The DEGs were used for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analysis. The receiver operating characteristic curve (ROC) was applied to evaluate diagnostic ability. For further confirmation, the expression levels and diagnostic value of biomarkers in PE were verified in the GSE75010 data set (80 PE and 77 controls) and validated by qRT-RCR, Western blot, and immunohistochemistry (IHC). The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in PE. Results: In total, 15 DEGs were recognized. The GO and KEGG analyses revealed that the DEGs were enriched in the steroid metabolic process, receptor ligand activity, GnRH secretion, and neuroactive ligand-receptor interaction. The recognized DEGs were primarily implicated in cell-type benign neoplasm, kidney failure, infertility, and PE. Gene sets related to hormone activity, glycosylation, multicellular organism process, and response to BMP were activated in PE. The LEP gene was distinguished as a diagnostic biomarker of PE (AUC = 0.712) and further certified in the GSE75010 data set (AUC = 0.850). The high expression of LEP was associated with PE in clinical samples. In addition, the analysis of the immune microenvironment showed that gamma delta T cells, memory B cells, M0 macrophages, and regulatory T cells were positively correlated with LEP expression (P < 0.05). Conclusion: LEP expression can be considered to be a diagnostic biomarker of PE and can offer a novel perspective for future studies regarding the occurrence and molecular mechanisms of PE.", "claims": [{"id": "claim-method", "statement": "The Mann–Whitney U test was used to compare the PE and normotensive control groups. The LASSO regression analysis, SVM algorithm, ROC curve analysis, Pearson’s correlation, and unpaired t-test were used as described above.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37635936", "locator": "sections[13] \"Statistical analysis\" paragraph 2", "quote": "The Mann–Whitney U test was used to compare the PE and normotensive control groups. The LASSO regression analysis, SVM algorithm, ROC curve analysis, Pearson’s correlation, and unpaired t-test were used as described above."}], "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 authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37635936", "locator": "sections[26] \"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 authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "LEP was distinguished as a diagnostic biomarker of PE, with an AUC of 0.712 in the metadata cohort and an AUC of 0.850 in the GSE75010 validation dataset.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37635936", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The LEP gene was distinguished as a diagnostic biomarker of PE (AUC = 0.712) and further certified in the GSE75010 data set (AUC = 0.850)."}, {"asset": "source:pmid:37635936", "locator": "sections[19] \"Effectiveness of featured diagnostic biomarkers in PE\" paragraph 2", "quote": "Furthermore, a forceful discerning capacity was verified in the GSE75010 data set with an AUC of 0.850 in LEP (Figure 6B), showing that the LEP gene had a higher diagnostic capacity."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "LEP was distinguished as a diagnostic biomarker of PE, with an AUC of 0.712 in the metadata cohort and an AUC of 0.850 in the GSE75010 validation dataset.", "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:37635936"], "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. 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