Investigation of candidate genes for osteoarthritis based on gene expression profiles

Analysis of Molecular Changes and Features in Rat Knee Osteoarthritis Cartilage: Progress From Cellular Changes to Structural Damage

OBJECTIVE

Although knee osteoarthritis (KOA) is a common disease, there is a lack of specific prevention and early treatment methods. Hence, this study aimed to examine the molecular changes occurring at different stages of KOA to elucidate the dynamic nature of the disease.

DESIGN

Using a low-force compression model and analyzing RNA sequencing data, we identified molecular changes in the transcriptome of knee joint cartilage, including gene expression and molecular pathways, between the cellular changes and structural damage stages of KOA progression. In addition, we validated hub genes using an external dataset.

RESULTS

Gene set enrichment analysis (GSEA) identified the following pathways to be associated with KOA: "B-cell receptor signaling pathway," "cytokine-cytokine receptor interaction," and "hematopoietic cell lineage." Expression analysis revealed 585 differentially expressed genes, with 579 downregulated and 6 upregulated genes. Enrichment and clustering analyses revealed that the main molecular clusters were involved in cell cycle regulation and immune responses. Furthermore, the hub genes Csf1r, Cxcr4, Cxcl12, and Ptprc were related to immune responses.

CONCLUSIONS

Our study provides insights into the dynamic nature of early-stage KOA and offers valuable information to support the development of effective intervention strategies to prevent the irreversible damage associated with KOA, thereby addressing a major clinical challenge.

A molecular map of long non-coding RNA expression, isoform switching and alternative splicing in osteoarthritis

Osteoarthritis is a prevalent joint disease and a major cause of disability worldwide with no curative therapy. Development of disease-modifying therapies requires a better understanding of the molecular mechanisms underpinning disease. A hallmark of osteoarthritis is cartilage degradation. To define molecular events characterizing osteoarthritis at the whole transcriptome level, we performed deep RNA sequencing in paired samples of low- and high-osteoarthritis grade knee cartilage derived from 124 patients undergoing total joint replacement. We detected differential expression between low- and high-osteoarthritis grade articular cartilage for 365 genes and identified a 38-gene signature in osteoarthritis cartilage by replicating our findings in an independent dataset. We also found differential expression for 25 novel long non-coding RNA genes (lncRNAs) and identified potential lncRNA interactions with RNA-binding proteins in osteoarthritis. We assessed alterations in the relative usage of individual gene transcripts and identified differential transcript usage for 82 genes, including ABI3BP, coding for an extracellular matrix protein, AKT1S1, a negative regulator of the mTOR pathway and TPRM4, coding for a transient receptor potential channel. We further assessed genome-wide differential splicing, for the first time in osteoarthritis, and detected differential splicing for 209 genes, which were enriched for extracellular matrix, proteoglycans and integrin surface interactions terms. In the largest study of its kind in osteoarthritis, we find that isoform and splicing changes, in addition to extensive differences in both coding and non-coding sequence expression, are associated with disease and demonstrate a novel layer of genomic complexity to osteoarthritis pathogenesis.

Extensive cytokine analysis in synovial fluid of osteoarthritis patients

OBJECTIVE

Osteoarthritis (OA) is a joint disease characterized by articular cartilage loss and afflicts many people worldwide. However, diagnostic methods and treatment options remain limited and are often characterized by low sensitivity and low efficacy. The focus of the present study was to identify proteomic biomarkers in synovial fluid to improve diagnosis and therapy of OA patients.

METHODS

Antibody array technology was utilized for protein expression profiling of synovial fluid from 24 OA patients and 24 healthy persons.

RESULTS

Compared with healthy persons, twenty proteins showed lower expression levels in OA patients, while thirty proteins had higher levels. Among these differential proteins, GITRL, CEACAM-1, FSH, EG-VEGF, FGF-4, PIGF, Cystatin EM and NT-4 were found for the first time to be differentially expressed in OA. Bioinformatics analysis showed that most of these differential proteins were involved leukocytes events, and some differentially expressed proteins including IL-18, CXCL1, CTLA4, MIP-3b, CD40, MMP-1, THBS1, CCL11, PAI-1, BAFF, aggrecan, angiogenin and follistatin were located in central positions of the protein-protein interaction (PPI) network.

CONCLUSION

We speculate that leukocyte proliferation and migration to the joint may be an important pathogenesis of OA, which needs a further validation. The central proteins of the PPI network may play a more pivotal role in OA. The newly identified differentially expressed proteins may be novel biomarkers for OA diagnosis and targets for OA therapy.

Ingenuity pathway analysis of human facet joint tissues: Insight into facet joint osteoarthritis

Facet joint osteoarthritis (FJOA) is a common degenerative joint disorder with high prevalence in the elderly. FJOA causes lower back pain and lower extremity pain, and thus severely impacts the quality of life of affected patients. Emerging studies have focused on the histomorphological and histomorphometric changes in FJOA. However, the dynamic genetic changes in FJOA have remained to be clearly determined. In the present study, previously obtained RNA deep sequencing data were subjected to an ingenuity pathway analysis (IPA) and canonical signaling pathways of differentially expressed genes (DEGs) in FJOA were studied. The top 25 enriched canonical signaling pathways were identified and canonical signaling pathways with high absolute values of z-scores, specifically leukocyte extravasation signaling, Tec kinase signaling and osteoarthritis pathway, were investigated in detail. DEGs were further categorized by disease, biological function and toxicity (tox) function. The genetic networks between DEGs as well as hub genes in these functional networks were also investigated. It was demonstrated that C-X-C motif chemokine ligand 8, elastase, neutrophil expressed, growth factor independent 1 transcriptional repressor, Spi-1 proto-oncogene, CCAAT enhancer binding protein epsilon, GATA binding protein 1, TAL bHLH transcription factor 1, erythroid differentiation factor, minichromosome maintenance complex component 4, BTG anti-proliferation factor 2, BRCA1 DNA repair-associated, cyclin D1, chromatin assembly factor 1 subunit A, triggering receptor expressed on myeloid cells 1 and tumor protein p63 were hub genes in the top 5 IPA networks (with a score >30). The present study provides insight into the pathological processes of FJOA from a genetic perspective and may thus benefit the clinical treatment of FJOA.

Centrality and the shortest path approach in the human interactome

Many notions and concepts for network analysis, including the shortest path approach, came to systems biology from the theory of graphs - the field of mathematics that studies graphs. We studied the relationship between the shortest paths and a biologically meaningful molecular path between vertices in human molecular interaction networks. We analyzed the sets of the shortest paths in the human interactome derived from HPRD and HIPPIE databases between all possible combinations of start and end proteins in eight signaling pathways in the KEGG database - NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta, and the signaling part of the apoptotic process. We investigated whether the shortest paths match the canonical paths. We studied whether centrality of vertices and paths in the subnetworks induced by the shortest paths can highlight vertices and paths that are part of meaningful molecular paths. We found that the shortest paths match canonical counterparts only for canonical paths of length 2 or 3 interactions. The shortest paths match longer canonical counterparts with shortcuts or substitutions by protein complex members. We found that high centrality vertices are part of the canonical paths for up to 80% of the canonical paths depending on the database and the length.

RNA expression preoperatively and postoperatively following total knee replacement: a pilot study in patients with and without chronic postsurgical pain

BACKGROUND AND OBJECTIVE

Differences in gene expression may provide insight into the biological pathways involved in chronic postsurgical pain (CPSP). We compared blood RNA microarrays preoperatively and postoperatively following total knee arthroplasty (TKA) in patients with and without CPSP.

METHODS

Patients scheduled for primary TKA had whole blood samples obtained preoperatively and at 48 hours and 6 months postsurgery. RNA expression (54 613 transcripts) were assayed using the "Affymetrix HG-U133 plus 2.0" microarray. Genes that met the threshold criteria of ±1.5-fold differential change in expression (CPSP vs non-CPSP), with p<0.0125, were considered for pathway analysis. WikiPathways was used to identify biological pathways that were affected (p<0.01) by differentially regulated genes.

RESULTS

Four of 16 (25%) patients had CPSP at 6 months. Preoperatively, 325 (0.6%) genes met the criteria, with 292 (89.9%) having greater expression in the CPSP group. Twelve biological pathways were affected, with the mitogen-activated kinase, phosphatidylinositide 3-kinase-protein kinase B-mammalian target of rapamycin, and brain-derived neurotrophic factor signaling pathways having known association with pain. At 48 hours, 26 genes met the criteria; 7 pathways were affected, including transforming growth factor-β with known association with pain. At 6 months 55 genes met the criteria, with 49 increased in the CPSP group. Four biological pathways were affected, with only the chemokine signaling pathway having known association with pain.

CONCLUSIONS

Despite a lack of clinical differences, patients who develop CPSP have upregulated pain pathways preoperatively; however, only the chemokine pathway remained differentially upregulated at 6 months postsurgery.

What did we learn from 'omics' studies in osteoarthritis

PURPOSE OF REVIEW

'Omics' technologies developed for the massive analysis of the major biologically relevant molecules (genes, proteins, metabolites) have been applied to the study of osteoarthritis (OA) for more than a decade.

RECENT FINDINGS

'Omics' studies have undoubtedly contributed to increase the knowledge on pathogenic processes related with OA and have provided hundreds to thousands of molecules that might have a putative biomarker utility for this disease.

SUMMARY

This review describes the most recent 'omics' studies in OA research, their conclusions, and discuss those remaining challenges. Still many validation studies must be performed in large and well-characterized cohorts for the translation of the findings from 'omics' strategies to clinical applications. The development of tools for the intelligent integration of 'omics' data with clinical and imaging information is also mandatory to take full profit of the work that has been already performed.

Identification of gene expression profiles and key genes in subchondral bone of osteoarthritis using weighted gene coexpression network analysis

Osteoarthritis (OA) significantly influences the quality life of people around the world. It is urgent to find an effective way to understand the genetic etiology of OA. We used weighted gene coexpression network analysis (WGCNA) to explore the key genes involved in the subchondral bone pathological process of OA. Fifty gene expression profiles of GSE51588 were downloaded from the Gene Expression Omnibus database. The OA-associated genes and gene ontologies were acquired from JuniorDoc. Weighted gene coexpression network analysis was used to find disease-related networks based on 21756 gene expression correlation coefficients, hub-genes with the highest connectivity in each module were selected, and the correlation between module eigengene and clinical traits was calculated. The genes in the traits-related gene coexpression modules were subject to functional annotation and pathway enrichment analysis using ClusterProfiler. A total of 73 gene modules were identified, of which, 12 modules were found with high connectivity with clinical traits. Five modules were found with enriched OA-associated genes. Moreover, 310 OA-associated genes were found, and 34 of them were among hub-genes in each module. Consequently, enrichment results indicated some key metabolic pathways, such as extracellular matrix (ECM)-receptor interaction (hsa04512), focal adhesion (hsa04510), the phosphatidylinositol 3'-kinase (PI3K)-Akt signaling pathway (PI3K-AKT) (hsa04151), transforming growth factor beta pathway, and Wnt pathway. We intended to identify some core genes, collagen (COL)6A3, COL6A1, ITGA11, BAMBI, and HCK, which could influence downstream signaling pathways once they were activated. In this study, we identified important genes within key coexpression modules, which associate with a pathological process of subchondral bone in OA. Functional analysis results could provide important information to understand the mechanism of OA.

Protective Effects of Peucedanum japonicum Extract against Osteoarthritis in an Animal Model Using a Combined Systems Approach for Compound-Target Prediction

Peucedanum japonicum Thunberg is an herbal medicine used to treat neuralgia, rheumatoid arthritis, and inflammatory-related diseases. However, its effects on osteoarthritis (OA) and its regulatory mechanisms have not been investigated by network analysis. Here, we investigated the pharmacological effects of Peucedanum japonicum extract (PJE) on OA, by combining in vivo effective verification and network pharmacology prediction. Rats in which OA was induced by monosodium iodoacetate (MIA) were treated with PJE (200 mg/kg), and histopathological parameters, weight bearing distribution and inflammatory factors in serum and joint tissue were measured after 28 days of treatment. Additionally, in silico network analysis was used to predict holistic OA regulatory mechanisms of PJE. The results showed that PJE exerted potential protective effects by recovering hind paw weight bearing distribution, alleviating histopathological features of cartilage and inhibiting inflammatory mediator levels in the OA rat model. Furthermore, network analysis identified caspase-3 (CASP3), caspase-7 (CASP7), and cytochrome P450 2D6 (CYP2D6) as potential target genes; in addition, the TNF (Tumor necrosis factor) signaling pathway was linked to OA therapeutic action. Our combined animal OA model and network analysis confirmed the therapeutic effects of PJE against OA and identified intracellular signaling pathways, active compounds and target genes linked to its therapeutic action.