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Fan Y, Bian X, Meng X, Li L, Fu L, Zhang Y, Wang L, Zhang Y, Gao D, Guo X, Lammi MJ, Peng G, Sun S. Unveiling inflammatory and prehypertrophic cell populations as key contributors to knee cartilage degeneration in osteoarthritis using multi-omics data integration. Ann Rheum Dis 2024; 83:926-944. [PMID: 38325908 PMCID: PMC11187367 DOI: 10.1136/ard-2023-224420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 01/23/2024] [Indexed: 02/09/2024]
Abstract
OBJECTIVES Single-cell and spatial transcriptomics analysis of human knee articular cartilage tissue to present a comprehensive transcriptome landscape and osteoarthritis (OA)-critical cell populations. METHODS Single-cell RNA sequencing and spatially resolved transcriptomic technology have been applied to characterise the cellular heterogeneity of human knee articular cartilage which were collected from 8 OA donors, and 3 non-OA control donors, and a total of 19 samples. The novel chondrocyte population and marker genes of interest were validated by immunohistochemistry staining, quantitative real-time PCR, etc. The OA-critical cell populations were validated through integrative analyses of publicly available bulk RNA sequencing data and large-scale genome-wide association studies. RESULTS We identified 33 cell population-specific marker genes that define 11 chondrocyte populations, including 9 known populations and 2 new populations, that is, pre-inflammatory chondrocyte population (preInfC) and inflammatory chondrocyte population (InfC). The novel findings that make this an important addition to the literature include: (1) the novel InfC activates the mediator MIF-CD74; (2) the prehypertrophic chondrocyte (preHTC) and hypertrophic chondrocyte (HTC) are potentially OA-critical cell populations; (3) most OA-associated differentially expressed genes reside in the articular surface and superficial zone; (4) the prefibrocartilage chondrocyte (preFC) population is a major contributor to the stratification of patients with OA, resulting in both an inflammatory-related subtype and a non-inflammatory-related subtype. CONCLUSIONS Our results highlight InfC, preHTC, preFC and HTC as potential cell populations to target for therapy. Also, we conclude that profiling of those cell populations in patients might be used to stratify patient populations for defining cohorts for clinical trials and precision medicine.
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Affiliation(s)
- Yue Fan
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Collaborative Innovation Center of Endemic Diseases and Health Promotion in Silk Road Region, Shaanxi Province; Key Laboratory of Trace Elements and Endemic Diseases, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xuzhao Bian
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Xiaogao Meng
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong, China
| | - Lei Li
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Laiyi Fu
- School of Automation Science and Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yanan Zhang
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Long Wang
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yan Zhang
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Department of Orthopaedics, Honghui Hospital, Xi'an, Shaanxi, China
| | - Dalong Gao
- Department of Orthopaedics, The Central Hospital of Xianyang, Xianyang, China
| | - Xiong Guo
- Collaborative Innovation Center of Endemic Diseases and Health Promotion in Silk Road Region, Shaanxi Province; Key Laboratory of Trace Elements and Endemic Diseases, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Mikko Juhani Lammi
- Department of Integrative Medical Biology, University of Umeå, Umeå, Sweden
| | - Guangdun Peng
- Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, Guangdong, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shiquan Sun
- Center for Single-Cell Omics and Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
- Collaborative Innovation Center of Endemic Diseases and Health Promotion in Silk Road Region, Shaanxi Province; Key Laboratory of Trace Elements and Endemic Diseases, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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Liao CS, He FZ, Li XY, Zhang Y, Han PF. Analysis of common differential gene expression in synovial cells of osteoarthritis and rheumatoid arthritis. PLoS One 2024; 19:e0303506. [PMID: 38771826 PMCID: PMC11108184 DOI: 10.1371/journal.pone.0303506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 04/25/2024] [Indexed: 05/23/2024] Open
Abstract
OBJECTIVE To elucidate potential molecular mechanisms differentiating osteoarthritis (OA) and rheumatoid arthritis (RA) through a bioinformatics analysis of differentially expressed genes (DEGs) in patient synovial cells, aiming to provide new insights for clinical treatment strategies. MATERIALS AND METHODS Gene expression datasets GSE1919, GSE82107, and GSE77298 were downloaded from the Gene Expression Omnibus (GEO) database to serve as the training groups, with GSE55235 being used as the validation dataset. The OA and RA data from the GSE1919 dataset were merged with the standardized data from GSE82107 and GSE77298, followed by batch effect removal to obtain the merged datasets of differential expressed genes (DEGs) for OA and RA. Intersection analysis was conducted on the DEGs between the two conditions to identify commonly upregulated and downregulated DEGs. Enrichment analysis was then performed on these common co-expressed DEGs, and a protein-protein interaction (PPI) network was constructed to identify hub genes. These hub genes were further analyzed using the GENEMANIA online platform and subjected to enrichment analysis. Subsequent validation analysis was conducted using the GSE55235 dataset. RESULTS The analysis of differentially expressed genes in the synovial cells from patients with Osteoarthritis (OA) and Rheumatoid Arthritis (RA), compared to a control group (individuals without OA or RA), revealed significant changes in gene expression patterns. Specifically, the genes APOD, FASN, and SCD were observed to have lower expression levels in the synovial cells of both OA and RA patients, indicating downregulation within the pathological context of these diseases. In contrast, the SDC1 gene was found to be upregulated, displaying higher expression levels in the synovial cells of OA and RA patients compared to normal controls.Additionally, a noteworthy observation was the downregulation of the transcription factor PPARG in the synovial cells of patients with OA and RA. The decrease in expression levels of PPARG further validates the alteration in lipid metabolism and inflammatory processes associated with the pathogenesis of OA and RA. These findings underscore the significance of these genes and the transcription factor not only as biomarkers for differential diagnosis between OA and RA but also as potential targets for therapeutic interventions aimed at modulating their expression to counteract disease progression. CONCLUSION The outcomes of this investigation reveal the existence of potentially shared molecular mechanisms within Osteoarthritis (OA) and Rheumatoid Arthritis (RA). The identification of APOD, FASN, SDC1, TNFSF11 as key target genes, along with their downstream transcription factor PPARG, highlights common potential factors implicated in both diseases. A deeper examination and exploration of these findings could pave the way for new candidate targets and directions in therapeutic research aimed at treating both OA and RA. This study underscores the significance of leveraging bioinformatics approaches to unravel complex disease mechanisms, offering a promising avenue for the development of more effective and targeted treatments.
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Affiliation(s)
- Chang-sheng Liao
- Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, P.R. China
- Department of Graduate School, Graduate Student Department of Changzhi Medical College, Changzhi, P.R. China
| | - Fang-zheng He
- Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, P.R. China
- Department of Graduate School, Graduate Student Department of Changzhi Medical College, Changzhi, P.R. China
| | - Xi-yong Li
- Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, P.R. China
- Department of Graduate School, Graduate Student Department of Changzhi Medical College, Changzhi, P.R. China
| | - Yan Zhang
- Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, P.R. China
- Department of Graduate School, Graduate Student Department of Changzhi Medical College, Changzhi, P.R. China
| | - Peng-fei Han
- Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, P.R. China
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