Identification of key biomarkers related to fibrocartilage chondrocytes for osteoarthritis based on bulk, single-cell transcriptomic data DOI Creative Commons
Bailin Pan, Pingping Yao, Jinjin Ma

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 21, 2024

Osteoarthritis (OA) is a prevalent joint disease that severely impacts patients' quality of life. Due to its unclear pathogenesis and lack effective therapeutic targets, discovering new biomarkers for OA essential. Recently, the role chondrocyte subpopulations in progression has gained significant attention, offering potential insights into disease. This study aimed explore fibrocartilage chondrocytes (FC) identify key related FC. We analyzed single-cell ribonucleic acid sequencing (scRNA-seq) data from samples normal cartilage, focusing on Microarray were integrated differentially expressed genes (DEGs). conducted functional-enrichment analyses, including Kyoto Encyclopedia Genes Genomes (KEGG) Gene Ontology (GO), used weighted gene co-expression network analysis (WGCNA) least absolute shrinkage selection operator (LASSO) algorithm select biomarkers. A novel risk model was constructed using these then built transcription factor (TF)-gene interaction performed immunohistochemistry (IHC) validate protein expression levels cartilage samples. The identified 545 marker associated with FC OA. GO KEGG analyses revealed their biological functions; microarray 243 DEGs which conducted. Using WGCNA LASSO, we six hub genes, basis In addition, correlation close association between Forkhead Box (FoxO)-mediated IHC showed significantly lower ABCA5, ABCA6 SLC7A8 than multi-omics approach FC-related (BCL6, ABCA6, CITED2, NR1D1, SLC7A8) developed an exploratory model. Functional enrichment FoxO pathway may be linked markers, particularly implicating ABCA5 cholesterol homeostasis within chondrocytes. These findings highlight ABCA family members as contributors suggest targets.

Language: Английский

Progress in multi-omics studies of osteoarthritis DOI Creative Commons
Yuanyuan Wei, Qian He, Xiaoyu Zhang

et al.

Biomarker Research, Journal Year: 2025, Volume and Issue: 13(1)

Published: Feb. 11, 2025

Language: Английский

Citations

1
Identification and experimental validation of key genes in osteoarthritis based on machine learning algorithms and Single-cell sequencing analysis DOI Creative Commons
E. Yu,

Mingshu Zhang,

Chunyang Xi

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(17), P. e37047 - e37047

Published: Aug. 28, 2024

Osteoarthritis (OA) is a prevalent cause of disability in older adults. Identifying diagnostic markers for OA essential elucidating its mechanisms and facilitating early diagnosis.

Language: Английский

Citations

3
CCL4/CCR5 regulates chondrocyte biology and OA progression DOI Creative Commons

Hongjian Deng,

Pengfei Xue,

Xiaogang Zhou

et al.

Cytokine, Journal Year: 2024, Volume and Issue: 183, P. 156746 - 156746

Published: Sept. 5, 2024

Language: Английский

Citations

2
Identification of key biomarkers related to fibrocartilage chondrocytes for osteoarthritis based on bulk, single-cell transcriptomic data DOI Creative Commons
Bailin Pan, Pingping Yao, Jinjin Ma

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 21, 2024

Osteoarthritis (OA) is a prevalent joint disease that severely impacts patients' quality of life. Due to its unclear pathogenesis and lack effective therapeutic targets, discovering new biomarkers for OA essential. Recently, the role chondrocyte subpopulations in progression has gained significant attention, offering potential insights into disease. This study aimed explore fibrocartilage chondrocytes (FC) identify key related FC. We analyzed single-cell ribonucleic acid sequencing (scRNA-seq) data from samples normal cartilage, focusing on Microarray were integrated differentially expressed genes (DEGs). conducted functional-enrichment analyses, including Kyoto Encyclopedia Genes Genomes (KEGG) Gene Ontology (GO), used weighted gene co-expression network analysis (WGCNA) least absolute shrinkage selection operator (LASSO) algorithm select biomarkers. A novel risk model was constructed using these then built transcription factor (TF)-gene interaction performed immunohistochemistry (IHC) validate protein expression levels cartilage samples. The identified 545 marker associated with FC OA. GO KEGG analyses revealed their biological functions; microarray 243 DEGs which conducted. Using WGCNA LASSO, we six hub genes, basis In addition, correlation close association between Forkhead Box (FoxO)-mediated IHC showed significantly lower ABCA5, ABCA6 SLC7A8 than multi-omics approach FC-related (BCL6, ABCA6, CITED2, NR1D1, SLC7A8) developed an exploratory model. Functional enrichment FoxO pathway may be linked markers, particularly implicating ABCA5 cholesterol homeostasis within chondrocytes. These findings highlight ABCA family members as contributors suggest targets.

Language: Английский

Citations

0