Deciphering B Cell Heterogeneity and Pathogenic Mechanisms in Osteoporosis Through Single-Cell RNA Sequencing.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41404455", "kind": "science-record", "revision": 4, "content_hash": "sha256:7cba3fd03bccd3cef54ff4024f23a1ae77687cc0ad2444ef9f27a762e4194f42", "created_at": "2026-11-01T20:31:24Z", "updated_at": "2026-11-01T22:57:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Deciphering B Cell Heterogeneity and Pathogenic Mechanisms in Osteoporosis Through Single-Cell RNA Sequencing.", "doi": "10.1155/bmri/9979105", "pmid": "41404455", "authors": ["Taolve Zhou", "Jiayuan Zheng", "Yujun Sun", "Jionglin Wu", "Wenzhou Liu", "Zhenxiang Zheng", "Jiajie Li", "Guo Fu", "Fan Zhang", "Yanbo Chen", "Gang Zeng", "Weidong Song"], "journal": "BioMed research international", "year": 2025, "abstract": "Background: Osteoporosis is characterized by reduced bone mineral density and disrupted bone microstructure, leading to an increased risk of fractures. This study aimed to investigate the role of B cell subpopulations in osteoporosis and their effects on bone metabolism using single-cell RNA sequencing.\nMethods: Single-cell RNA sequencing data from primary human femoral head tissue cells of three osteoporosis patients and one non-osteoporosis patient were obtained from the GEO dataset (GSE169396). Data preprocessing, integration, dimensionality reduction, clustering, and annotation were conducted using the Seurat package in R. Enrichment analysis, cell trajectory analysis, and intercellular communication analysis were then applied to investigate the role of B cells and the signaling pathways within B cell subpopulations in osteoporosis.\nResults: We identified six distinct B cell subpopulations, and further analysis revealed a higher proportion of precursor B cells in osteoporosis patients compared to the normal group. Functional studies indicated that B cells contribute to the progression of osteoporosis through inflammatory activation and the unfolded protein response. Cell communication analysis among these B cell subpopulations demonstrated markedly enhanced intercellular signaling in osteoporosis patients relative to the normal group. Notably, two critical signaling pathways, MIF-(CD74+CXCR4) and LGALS9-CD45, were identified as potential key regulators driving the progression of osteoporosis.\nConclusion: This study underscores the heterogeneity and functions of B cells in osteoporosis, highlighting two signaling pathways implicated in disease progression. These findings offer novel insights into osteoporosis pathogenesis and suggest potential therapeutic targets for its treatment.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) were identified using Seurat’s “FindAllMarkers” function with thresholds of |log2FoldChange| > 2 and p < 0.05 [23]. The Student’s t test was performed for group comparisons when the data were normally distributed, while the Wilcoxon test was applied for non‐normally distributed data.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41404455", "locator": "sections[8] \"2.6. Identification of Differentially Expressed Genes and Marker Genes in B Cell Subpopulations\" paragraph 2", "quote": "Differentially expressed genes (DEGs) were identified using Seurat’s “FindAllMarkers” function with thresholds of |log2FoldChange| > 2 and p < 0.05 [23]."}, {"asset": "source:pmid:41404455", "locator": "sections[12] \"2.10. Statistical Analysis\" paragraph 2", "quote": "The Student’s t test was performed for group comparisons when the data were normally distributed, while the Wilcoxon test was applied for non‐normally distributed data."}], "state": "complete"}, {"id": "claim-data-access", "statement": "This study is based on the publicly available dataset GSE169396, which contains single‐cell RNA sequencing data related to osteoporosis. The dataset is accessible at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169396 (accessed on March 24, 2021).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41404455", "locator": "sections[32] \"Data Availability Statement\" paragraph 2", "quote": "This study is based on the publicly available dataset GSE169396, which contains single‐cell RNA sequencing data related to osteoporosis. The dataset is accessible at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169396 (accessed on March 24, 2021)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Compared with the control group, the OP group had higher proportions of precursor B cells (0.114 in the normal group vs. 0.147 in the OP group), while memory B cells (0.167 vs. 0.104), and B1 cells (0.031 vs. 0.015) were less abundant (Figure 3h).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41404455", "locator": "sections[15] \"3.2. Single‐Cell Transcriptome of B Cells\" paragraph 2", "quote": "Compared with the control group, the OP group had higher proportions of precursor B cells (0.114 in the normal group vs. 0.147 in the OP group), while memory B cells (0.167 vs. 0.104), and B1 cells (0.031 vs. 0.015) were less abundant (Figure 3h)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Compared with the control group, the OP group had higher proportions of precursor B cells (0.114 in the normal group vs. 0.147 in the OP group), while memory B cells (0.167 vs. 0.104), and B1 cells (0.031 vs. 0.015) were less abundant (Figure 3h).", "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:41404455"], "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:GSE169396"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:student_t", "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:GSE169396"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:student_t"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41404455", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/bmri/9979105", "sha256": "sha256:99db1e8678b77f5f348d43cf40dd46d453e534571120e264f934ba21c4be43b6", "bytes": 43047, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/bmri/9979105", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12703134", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE169396", "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=GSE169396", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE169396", "version": null, "note": "This study is based on the publicly available dataset GSE169396, which contains single‐cell RNA sequencing data related to osteoporosis. 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