Identification of potential biomarkers of leprosy: A study based on GEO datasets.

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In this study, we conducted bioinformatics analysis with leprosy and normal samples acquired from the GEO database(GSE84893, GSE74481, GSE17763, GSE16844 and GSE443). Through WGCNA analysis, 85 hub genes were screened(GS > 0.7 and MM > 0.8). Through DEG analysis, 82 up-regulated and 3 down-regulated genes were screened(|Log2FC| > 3 and FDR < 0.05). Then 49 intersection genes were considered as crucial and subjected to GO annotation, KEGG pathway and PPI analysis to determine the biological significance in the pathogenesis of leprosy. Finally, we identified a gene-pathway network, suggesting ITK, CD48, IL2RG, CCR5, FGR, JAK3, STAT1, LCK, PTPRC, CXCR4 can be used as biomarkers and these genes are active in 6 immune system pathways, including Chemokine signaling pathway, Th1 and Th2 cell differentiation, Th17 cell differentiation, T cell receptor signaling pathway, Natural killer cell mediated cytotoxicity and Leukocyte transendothelial migration. We identified 10 crucial gene markers and related important pathways that acted as essential components in the etiology of leprosy. Our study provides potential targets for diagnostic biomarkers and therapy of leprosy.", "claims": [{"id": "claim-method", "statement": "Weighted Gene Co-expression Network Analysis(WGCNA) was constructed on the normalized gene expression profiles with R package “WGCNA” [18].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38739634", "locator": "sections[5] \"WGCNA analysis\" paragraph 2", "quote": "Weighted Gene Co-expression Network Analysis(WGCNA) was constructed on the normalized gene expression profiles with R package “WGCNA” [18]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All relevant data are within the paper and its supporting information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38739634", "locator": "sections[19] \"Data Availability\" paragraph 2", "quote": "All relevant data are within the paper and its supporting information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 10 candidate gene biomarkers and six related immune-system pathways for leprosy.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38739634", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We identified 10 crucial gene markers and related important pathways that acted as essential components in the etiology of leprosy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 10 candidate gene biomarkers and six related immune-system pathways for leprosy.", "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:38739634"], "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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