Evidence map›Paper›PMID 39438957›Full record

ArticleJournal of orthopaedic surgery and research2024

Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus.

Yanzhu Shen, Ruichen Jiang, Yanjun Huang, Yuming Wang, Sizheng Zhan, Xiangsheng Tang, Ping Yi

Abstract read
In one paragraph

Article in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Yanzhu ShenChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730 , China.
Ruichen JiangGraduate School, Beijing University of Chinese Medicine, Beijing, 100029, China.
Yanjun HuangChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730 , China.
Yuming WangDepartment of Orthopaedics, China-Japan Friendship Hospital, Beijing, 100029, China.
Sizheng ZhanDepartment of Orthopaedics, China-Japan Friendship Hospital, Beijing, 100029, China.
Xiangsheng TangChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730 , China.
Ping YiChina-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730 , China. CJFH_YPSpine@163.com.

Funding

the National High Level Hospital Clinical Research Funding 2022-NHLHCRF-LX-02-0104
6 · The paper itself

Abstract

backgroundOsteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.

methodWe analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.

resultAfter quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.

conclusionThis research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

Indexed as

Gene Expression ProfilingOsteoarthritisSingle-Cell AnalysisGene Regulatory NetworksHumansMeniscusMicroarray AnalysisMicroRNAsOsteoarthritis, KneeProtein Interaction MapsTranscription FactorsTranscriptomeMicroRNAsTranscription FactorsBiological techniquesGeneticsMeniscusOsteoarthritisSingle-cell sequencing

Identifiers

PMID39438957
PMCPMC11515729

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