Integrated Analysis of Transcriptome Changes in Osteoarthritis: Gene Expression, Pathways and Alternative Splicing

Abstract

Objective Osteoarthritis (OA) is the most prevalent joint disease characterized by the degeneration of articular cartilage and the remodeling of its underlying bones, resulting in pain and loss of function in the knees and hips. As far as we know, no curative treatments are available except for the joint replacement. The precise molecular mechanisms which are involved in the degradation of cartilage matrix and development of osteoarthritis are still unclear. Design By analyzing RNA-seq data, we found the molecular changes at the transcriptome level such as alternative splicing, gene expression, and molecular pathways in OA knees cartilage. Results Expression analysis have identified 457 differential expressed genes including 266 up-regulated genes such as TNFSF15, ST6GALNAC5, TGFBI, ASPM, and TYM, and 191 down-regulated genes such as ADM, JUN, IRE2, PIGA, and MAFF. Gene set enrichment analysis (GSEA) analysis identified down-regulated pathways related to translation, transcription, immunity, PI3K/AKT, and circadian as well as disturbed pathways related to extracellular matrix and collagen. Splicing analysis identified 442 differential alternative splicing events within 284 genes in osteoarthritis, including genes involved in extracellular matrix (ECM) and alternative splicing, and TIA1 was identified as a key regulator of these splicing events. Conclusions These findings provide insights into disease etiology, and offer favorable information to support the development of more effective interventions in response to the global clinical challenge of osteoarthritis.

DDX5 inhibits hyaline cartilage fibrosis and degradation in osteoarthritis via alternative splicing and G-quadruplex unwinding

“…The difference between our study and the study by Katsoula et al is that we analyzed genome-wide differential splicing between healthy and OA cartilage. Furthermore, the study by Li et al 12 and our study indicated that there are many DASEs related to ECM-related pathways between healthy controls and individuals with OA. Li et al identified TIA1 as a key regulator of these DASEs.…”

“…2). With the exception of HK2 and ANGPTL4, most of the differentially expressed genes were also identified in the analysis by Li et al 12 . Then, to identify dysregulated splicing regulators related to hyaline cartilage fibrosis, we aggregated a comprehensive list of 452 splicing regulators from different sources, including previous publications [13][14][15][16][17] and the SpliceAid2 database 18 .…”

Natural and artificial selection of multiple alleles revealed through genomic analyses

“…Although no identity was observed between this gene and the previously proposed candidates ( Song et al, 2004 ; Lemay et al, 2023 ), it is annotated as an isopropylmalate synthase, a homolog to L1 , the eucomic acid synthase ( Lyu et al, 2023 ). It recently came to our attention that the same gene that we identified as L2 was also identified for L2 in a non-peer-reviewed preprint ( Li et al, 2023 ). This work is in accordance with our identification and multiple CM prediction and might be a valuable confirmation of our analyses.…”

“…Based on the highest average accuracy, we identified Glyma.03G005700 as the candidate gene for L2 , annotated as isopropylmalate synthase (IPMS; similar to the eucomic acid synthase GLYMA.19G120400). This gene has been identified as an L2 candidate in a preprint ( Li et al, 2023 ); it is a homolog to the cloned L1 Glyma.19G120400 ( Lyu et al, 2023 ).…”

Candidate Marker Genes for Diagnosis of Osteoarthritis and Prediction of Their Regulatory Mechanisms

“…69 the diagnosis of osteoarthritis. The analysis of Li et al (2023) has uncovered that ADM is evidently down-regulated in osteoarthritis. Additionally, existing studies have shown that ADM is regulated by tumour necrosis factor α and changes in ADM expression can affect adipogenesis and osteogenesis, providing new strategies for the treatment of bone and joints (Uzan et al, 2006;Hopwood et al, 2009;Qi et al, 2020;Cao et al, 2021a).…”