International journal of biological macromolecules · 2026
Integrated single-cell and bulk RNA sequencing analysis reveals peroxisome-related biomarkers in osteoarthritis lipid metabolism.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lu Peizhi, Li Ya, Yang Shuo, Yao Haoyu, Ning Rende
Аннотация
BACKGROUND: Osteoarthritis (OA) is a disabling joint disease that has garnered increasing attention with the global trend of population aging. Dysregulated lipid metabolism is considered one of the key contributors to the development of OA, though its precise mechanisms remain unclear. Peroxisomes are well-known for their role in cellular lipid metabolism, but the impact of peroxisome-related hub genes involved in lipid metabolism on OA is still unknown. This study explores the potential application value of peroxisome-related hub genes (PRGs) involved in lipid metabolism in OA.
METHODS: Four OA microarray datasets were downloaded from the GEO database, and hub genes were screened. The peroxisome lipid metabolism gene set was then downloaded from the Reactome database, and the intersection of these datasets yielded the Peroxisome-Related Genes (PRGs). Random forest, SVM-RFE algorithm, and multivariate logistic regression analysis were used to further screen and validate the hub genes. A diagnostic model for predicting OA occurrence was constructed based on these identified hub genes. Furthermore, the relationship between hub gene expression and immune infiltration of the synovial tissue was analyzed using CIBERSORT and MCP-counter algorithms. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed, followed by GO/KEGG enrichment analysis to further evaluate the key modules. The single-cell dataset GSE216651 was employed to further investigate the associations between the five hub genes and the various cell populations within the synovium. Hub gene expression was validated through WB, HE and qPCR.
RESULTS: We have identified five hub genes (SCP2, HAO2, ACOX2, CROT, AMACR) in the synovium of OA patients that can serve as diagnostic biomarkers for OA with an AUC value of 0.955. The expression levels of peroxisomal lipid metabolism-related hub genes were correlated to the immune disorders in OA synovium. Clustering and enrichment analysis showed that cluster 1 was significantly associated with "cell cycle", and cluster 2 was associated with "regulation of blood pressure". WB, qPCR and HE confirmed that SCP2 can serve as predictors.
CONCLUSION: Our findings suggest that PRGs play a significant role in the development of synovitis associated with OA. Furthermore, we identified peroxisomal lipid metabolism-related hub genes with potential diagnostic value for distinguishing OA.
METHODS: Four OA microarray datasets were downloaded from the GEO database, and hub genes were screened. The peroxisome lipid metabolism gene set was then downloaded from the Reactome database, and the intersection of these datasets yielded the Peroxisome-Related Genes (PRGs). Random forest, SVM-RFE algorithm, and multivariate logistic regression analysis were used to further screen and validate the hub genes. A diagnostic model for predicting OA occurrence was constructed based on these identified hub genes. Furthermore, the relationship between hub gene expression and immune infiltration of the synovial tissue was analyzed using CIBERSORT and MCP-counter algorithms. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed, followed by GO/KEGG enrichment analysis to further evaluate the key modules. The single-cell dataset GSE216651 was employed to further investigate the associations between the five hub genes and the various cell populations within the synovium. Hub gene expression was validated through WB, HE and qPCR.
RESULTS: We have identified five hub genes (SCP2, HAO2, ACOX2, CROT, AMACR) in the synovium of OA patients that can serve as diagnostic biomarkers for OA with an AUC value of 0.955. The expression levels of peroxisomal lipid metabolism-related hub genes were correlated to the immune disorders in OA synovium. Clustering and enrichment analysis showed that cluster 1 was significantly associated with "cell cycle", and cluster 2 was associated with "regulation of blood pressure". WB, qPCR and HE confirmed that SCP2 can serve as predictors.
CONCLUSION: Our findings suggest that PRGs play a significant role in the development of synovitis associated with OA. Furthermore, we identified peroxisomal lipid metabolism-related hub genes with potential diagnostic value for distinguishing OA.