Screening of Important Markers in Peripheral Blood Mononuclear Cells to Predict Female Osteoporosis Risk Using LASSO Regression Algorithm and SVM Method.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35110962", "kind": "science-record", "revision": 4, "content_hash": "sha256:c25ccc66df3d65476f2445c7fb585858cc2fcbdd617a9663dce146c6e5af9cb7", "created_at": "2026-11-01T17:36:50Z", "updated_at": "2026-11-01T22:05:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening of Important Markers in Peripheral Blood Mononuclear Cells to Predict Female Osteoporosis Risk Using LASSO Regression Algorithm and SVM Method.", "doi": "10.1177/11769343221075014", "pmid": "35110962", "authors": ["Hongwei Tang", "Qingtian Han", "Yong Yin"], "journal": "Evolutionary bioinformatics online", "year": 2022, "abstract": "BACKGROUND: Osteoporosis is a bone disease that increases the patient's risk of fracture. We aimed to identify robust marker genes related to osteoporosis based on different bioinformatic methods and multiple datasets.\nMETHODS: Three datasets from Gene Expression Omnibus (GEO) were utilized for analysis separately. Significantly differentially expressed genes (DEGs) from comparing high hip and low hip low bone mineral density (BMD) groups in the first dataset were identified for Gene Ontology (GO), Gene set enrichment analysis (GSEA) and Kyoto encyclopedia of genes and genomes (KEGG) to investigate the discrepantly enriched biological processes between high hip and low hip group. Last absolute shrinkage and selection operator (LASSO), SVM model and protein-protein interaction (PPI) regulatory network were performed and generated robust marker genes for downstream TF-target and miRNA-target prediction.\nRESULTS: Several DEGs between high hip BMD group and low hip BMD group were obtained. And the metabolism-related pathways such as metabolic pathways, carbon metabolism, glyoxylate and dicarboxylate metabolism shown enrichment in these DEGs. Integration with LASSO regression analysis, 8 differential expression genes (SH3BP1, NARF, ANKRD34B, RNF40, ZNF473, AKT1, SHMT1, and VASH1) in GSE62402 were identified as the optimal differential genes combination. Moreover, the SVM validation analysis in GSE56814 and GSE56815 datasets showed that the characteristic gene combinations presented high diagnostic effects, and the model AUC areas for GSE56814 was 0.899 and for GSE56815 was 0.921. Furthermore, the subcellular localization analysis of the 8 genes revealed that 4 proteins were located in the cytoplasm, 3 proteins were located in the nucleus, and 1 protein was located in the mitochondria. Additionally, the related TFs and miRNAs by performing TF-target and miRNA-target prediction for 5 genes (AKT1, SHMT1, ZNF473, RNF40 and VASH1) were investigated from PPI network.\nCONCLUSION: The optimal differential genes combination (SH3BP1, NARF, ANKRD34B, RNF40, ZNF473, AKT1, SHMT1, and VASH1) presented high diagnostic effect for osteoporosis risk.", "claims": [{"id": "claim-method", "statement": "Based on the expression levels of the differential genes in GSE62402, the LASSO regression algorithm was used for the screening of the optimal differential genes combination, and the parameter plot of the algorithm is shown in Figure 2A.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35110962", "locator": "sections[14] \"Screening and validation of marker genes\" paragraph 2", "quote": "Based on the expression levels of the differential genes in GSE62402, the LASSO regression algorithm was used for the screening of the optimal differential genes combination, and the parameter plot of the algorithm is shown in Figure 2A."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Briefly, 10 PBM samples (including 5 high hip BMD subjects and 5 low hip BMD subjects) from GSE62402, and 73 PBM samples (including 42 high hip BMD subjects and 31 low hip BMD subjects) from GSE56814 were detected using the GPL5175 [HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [transcript (gene) version].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35110962", "locator": "sections[3] \"The collection of transcriptome data\" paragraph 3", "quote": "Briefly, 10 PBM samples (including 5 high hip BMD subjects and 5 low hip BMD subjects) from GSE62402, and 73 PBM samples (including 42 high hip BMD subjects and 31 low hip BMD subjects) from GSE56814 were detected using the GPL5175 [HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [transcript (gene) version]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The optimal differential genes combination (SH3BP1, NARF, ANKRD34B, RNF40, ZNF473, AKT1, SHMT1, and VASH1) presented high diagnostic effect for osteoporosis risk.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35110962", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The optimal differential genes combination (SH3BP1, NARF, ANKRD34B, RNF40, ZNF473, AKT1, SHMT1, and VASH1) presented high diagnostic effect for osteoporosis risk."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The optimal differential genes combination (SH3BP1, NARF, ANKRD34B, RNF40, ZNF473, AKT1, SHMT1, and VASH1) presented high diagnostic effect for osteoporosis risk.", "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:35110962"], "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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