Potential candidate biomarkers associated with osteoarthritis: Evidence from a comprehensive network and pathway analysis

Identification of diagnostic biomarkers for osteoarthritis through bioinformatics and machine learning

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage degradation, inflammatory arthritis, and joint dysfunction. Currently, there is a lack of effective early diagnostic methods and treatment strategies for OA. Bioinformatics and biomarker research provide new possibilities for early detection and personalized therapy of OA. In this study, we investigated the molecular mechanisms of OA and important signaling pathways involved in disease progression through bioinformatics analysis. Firstly, using the limma package, we analyzed the differentially expressed genes (DEGs) between normal healthy samples and OA cartilage tissue samples. These DEGs were found to be primarily involved in biological processes such as extracellular matrix (ECM) binding, immune receptor activity, and cytokine activity, as well as signaling pathways including cytokine receptors, ECM-receptor interaction, and PI3K-Akt. Gene set enrichment analysis revealed that in the OA group, signaling pathways such as AMPK, B cell receptor, IL-17, and PPAR were downregulated, while calcium signaling pathway, cell adhesion molecules, ECM-receptor interaction, TGF-β signaling pathway, and Wnt signaling pathway were upregulated. Additionally, we constructed a co-expression module network using WGCNA and identified key modules associated with OA, from which we selected 7 most predictive OA characteristic genes. Among them, ANTXR1, KCNS3, SGCD, and LIN7A were correlated with the level of immune cell infiltration. This study elucidates the mechanisms underlying the development of OA and identifies potential diagnostic markers and therapeutic targets, providing important insights for early diagnosis and treatment of OA.

Integrated Analysis of DNA Methylation and Gene Expression Profiles in a Rat Model of Osteoarthritis

Osteoarthritis (OA) is common and affected by several factors, such as age, weight, sex, and genetics. The pathogenesis of OA remains unclear. Therefore, using a rat model of monosodium iodoacetate (MIA)-induced OA, we examined genomic-wide DNA methylation using methyl-seq and characterized the transcriptome using RNA-seq in the articular cartilage tissue from a negative control (NC) and MIA-induced rats. We identified 170 genes (100 hypomethylated and upregulated genes and 70 hypermethylated and downregulated genes) regulated by DNA methylation in OA. DNA methylation-regulated genes were enriched in functions related to focal adhesion, extracellular matrix (ECM)-receptor interaction and the PI3K-Akt and Hippo signaling pathways. Functions related to extracellular matrix organization, extracellular matrix proteoglycans, and collagen formation were involved in OA. A molecular and protein-protein network was constructed using methylated expression-correlated genes. Erk1/2 was a downstream target of OA-induced changes in DNA methylation and RNA expression. We found that the integrin subunit alpha 2 (ITGA2) gene is important in focal adhesion, alpha6-beta4 integrin signaling, and the inflammatory response pathway in OA. Overall, gene expression changes because DNA methylation influences OA pathogenesis. ITGA2, whose gene expression changes are regulated by DNA methylation during OA onset, is a candidate gene. Our findings provide insights into the epigenetic targets of OA processes in rats.

ITGB1 alleviates osteoarthritis by inhibiting cartilage inflammation and apoptosis via activating cAMP pathway

OBJECTIVE

We aimed to screen novel biomarkers for osteoarthritis (OA) using bioinformatic methods and explore its regulatory mechanism in OA development.

METHODS

Differentially expressed genes were screened out from GSE98918 and GSE82107 datasets. Protein-protein interaction network and enrichment analysis were employed to search for hub gene and regulatory pathway. Hematoxylin-eosin, Safranin O-Fast green staining, and immunohistochemistry were performed to assess pathological damage. TNF-α, IL-1β, and IL-6 concentrations were determined by enzyme-linked immunosorbent assay. Real-time quantitative PCR was applied to verify expression of hub genes in OA model. The expression of key protein and pathway proteins was determined by western blot. Furthermore, Cell Counting Kit-8 and flow cytometry were conducted to explore the role of hub gene in chondrocytes.

RESULTS

We identified 6 hub genes of OA, including ITGB1, COL5A1, COL1A1, THBS2, LAMA1, and COL12A1, with high prediction value. ITGB1 was screened as a pivotal regulator of OA and cAMP pathway was selected as the key regulatory pathway. ITGB1 was down-regulated in OA model. ITGB1 overexpression attenuated pathological damage and apoptosis in OA rats with the reduced levels of TNF-α, IL-1β and IL-6. ITGB1 overexpression activated cAMP pathway in vivo and vitro models. In vitro model, ITGB1 overexpression promoted cell viability, while inhibited apoptosis. ITGB1 overexpression also caused a decrease of TNF-α, IL-1β, and IL-6 concentrations. cAMP pathway inhibitor reversed the positive effect of ITGB1 on OA cell model.

CONCLUSION

ITGB1 is a novel biomarker for OA, which inhibits OA development by activating the cAMP pathway.

Disruption of Col9a2 expression leads to defects in osteochondral homeostasis and osteoarthritis-like phenotype in mice

Background/Objective

As one of the branched chains of Type IX collagen (Col9), Collagen IX alpha2 (Col9a2) has been reported to be associated with several orthopedic conditions. However, the relationship between Col9a2 and knee osteoarthritis (KOA) remains to be elucidated.

Methods

To probe the relationship between Col9a2 and KOA, we performed a systematic analysis of Col9a2-deficient (Col9a2-/-) mice using whole-mount skeletal staining, Micro-CT (μCT), biomechanics, histomorphometry, immunohistochemistry (IHC), immunofluorescence (IF) and Elisa.

Results

We found that the subchondral bone (SCB) in the knee joint of Col9a2-/- mice became sparse and deformed in the early stage, with altered bone morphometric parameters, reduced load-bearing capacity, dysfunctional bone homeostasis (decreased osteogenesis capacity and elevated bone resorption capacity), diminished cartilage proteoglycans and disrupted cartilage extracellular matrix (ECM) anabolism and catabolism compared with the Col9a2+/+ mice. In the late stage, the cartilage degeneration in Col9a2-/- mice were particularly pronounced compared to Col9a2+/+ mice, as evidenced by severe cartilage destruction and a marked reduction in cartilage thickness and area.

Conclusion

Overall, Col9a2 is essential for maintaining osteochondral homeostasis in the knee joint of mice, and the absence of this gene is accompanied by distinct sclerosis of the SCB and a reduction in load-bearing capacity; in the late stage, in the lack of SCB stress inhibition, excessive load is consistently exerted on the cartilage, ultimately leading to osteoarthritic-like articular cartilage damage.

Identifying Drug-Induced Liver Injury Associated With Inflammation-Drug and Drug-Drug Interactions in Pharmacologic Treatments for COVID-19 by Bioinformatics and System Biology Analyses: The Role of Pregnane X Receptor

Of the patients infected with coronavirus disease 2019 (COVID-19), approximately 14–53% developed liver injury resulting in poor outcomes. Drug-induced liver injury (DILI) is the primary cause of liver injury in COVID-19 patients. In this study, we elucidated liver injury mechanism induced by drugs of pharmacologic treatments against SARS-CoV-2 (DPTS) using bioinformatics and systems biology. Totally, 1209 genes directly related to 216 DPTS (DPTSGs) were genes encoding pharmacokinetics and therapeutic targets of DPTS and enriched in the pathways related to drug metabolism of CYP450s, pregnane X receptor (PXR), and COVID-19 adverse outcome. A network, constructed by 110 candidate targets which were the shared part of DPTSGs and 445 DILI targets, identified 49 key targets and four Molecular Complex Detection clusters. Enrichment results revealed that the 4 clusters were related to inflammatory responses, CYP450s regulated by PXR, NRF2-regualted oxidative stress, and HLA-related adaptive immunity respectively. In cluster 1, IL6, IL1B, TNF, and CCL2 of the top ten key targets were enriched in COVID-19 adverse outcomes pathway, indicating the exacerbation of COVID-19 inflammation on DILI. PXR-CYP3A4 expression of cluster 2 caused DILI through inflammation-drug interaction and drug-drug interactions among pharmaco-immunomodulatory agents, including tocilizumab, glucocorticoids (dexamethasone, methylprednisolone, and hydrocortisone), and ritonavir. NRF2 of cluster 3 and HLA targets of cluster four promoted DILI, being related to ritonavir/glucocorticoids and clavulanate/vancomycin. This study showed the pivotal role of PXR associated with inflammation-drug and drug-drug interactions on DILI and highlighted the cautious clinical decision-making for pharmacotherapy to avoid DILI in the treatment of COVID-19 patients.

Integrated Analysis of miRNAs and Gene Expression Profiles Reveals Potential Biomarkers for Osteoarthritis

Purpose: Currently, the early diagnosis and treatment of osteoarthritis (OA) remain a challenge. In the present study, we attempted to explore potential biomarkers for the diagnosis and treatment of OA.

Methods: The differentially expressed genes (DEGs) were identified based on three mRNA datasets of synovial tissues for OA patients and normal controls downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used for evaluating gene function related categories. Then, miRNA sequencing was performed for differentially expressed miRNAs’ identification. Finally, weighted gene co-expression network analysis (WGCNA) was performed for genes detected by the three mRNA datasets and a competing endogenous RNA (ceRNA) network with DEGs and differentially expressed microRNAs (miRNAs) was constructed for central genes identification. In addition, the relationship between central gene expression and immune infiltration was analyzed, and the candidate agents for OA were predicted based on the Connectivity Map database. Quantitative RT-PCR (qRT-PCR), Western blotting analysis, and immunofluorescent staining were performed to validate the expression levels of differentially expressed miRNAs and differentially expressed target genes in normal and OA tissues and chondrocytes. MiRNA–mRNA network was also validated in chondrocytes in vitro.

Results: A total of 259 DEGs and 26 differentially expressed miRNAs were identified, among which 94 miRNA–mRNA interactions were predicted. The brown module in WGCNA was most closely correlated with the clinical traits of OA. After overlapping the brown module genes with miRNA–mRNA pairs, 27 miRNA–mRNA pairs were obtained. A ceRNA network was constructed with 5505 lncRNA–miRNA–mRNA interactions. B-cell translocation gene 2(BTG2), Abelson-related gene (ABL2), and vascular endothelial growth factor A (VEGFA) were identified to be the central genes with good predictive performance, which were significantly correlated with immune cell infiltration in OA, reflected by declined activated dendritic cells (aDCs), and elevated contents of B cells, macrophages, neutrophils, and T helper cells. Anisomycin, MG-132, thapsigargin, and lycorine were predicted to be the potential candidate agents for OA intervention. In vitro, the expression levels of differentially expressed miRNAs and biomarkers identified in the present study were consistent with the results obtained in normal or OA knee cartilage tissues and chondrocytes. Furthermore, BTG2 was identified to be negatively regulated by miR-125a-5p.

Conclusion: BTG2, ABL2, and VEGFA can be regarded as potential predictive and treatment biomarkers for OA, which might guide the clinical therapy of OA.

Mechanisms Underlying the Action of Ziziphi Spinosae Semen in the Treatment of Insomnia: A Study Involving Network Pharmacology and Experimental Validation

Purpose: This study aimed to investigate the potential mechanisms and related bioactive components of ZSS for the treatment of insomnia. Method: The insomnia model of rat induced by PCPA was established. After oral administration of ZSS extract, the general morphological observation, pentobarbital sodium-induced sleep test and histopathological evaluation were carried out. Network pharmacology, assisted by UHPLC-Q-Exactive-MS/MS analysis, was developed to identify the targets of ZSS in the treatment of insomnia, as well as the corresponding signaling pathways. In addition, we validated the identified targets and pathways by RT-qPCR and immunohistochemical analysis. Results: The pentobarbital sodium-induced sleep test, determination of 5-HT and GABA levles in hypothalamic tissues and HE staining showed that ZSS extract was an effective treatment for insomnia. Network pharmacology analysis identified a total of 19 candidate bioactive ingredients in ZSS extract, along with 433 potentially related targets. Next, we performed protein-protein interaction (PPI), MCODE clustering analysis, GO functional enrichment analysis, KEGG pathway enrichment analysis, and ingredient-target-pathway (I-T-P) sub-networks analysis. These methods allowed us to investigate the synergistic therapeutic effects of crucial pathways, including the serotonergic and GABAergic synapse pathways. Our analyses revealed that palmitic acid, coclaurine, jujuboside A, N-nornuciferine, caaverine, magnoflorine, jujuboside B, and betulinic acid, all played key roles in the regulation of these crucial pathways. Finally, we used the PCPA-induced insomnia in rats to validate the data generated by network pharmacology; these in vivo experiments clearly showed that pathways associated with the serotonergic and GABAergic system were activated in the rats model. Furthermore, ZSS treatment significantly suppressed high levels of HTR1A, GABRA1, and GABRG2 expression in the hypothalamus and reduced the expression levels of HTR2A. Conclusion: Based on the combination of comprehensive network pharmacology and in vivo experiments, we successfully identified the potential pharmacological mechanisms underlying the action of ZSS in the treatment of insomnia. The results provide a theoretical basis for further development and utilization of ZSS, and also provide support for the development of innovative drugs for the treatment of insomnia.

3D spheroids of human placenta-derived mesenchymal stem cells attenuate spinal cord injury in mice

Mesenchymal stem cell (MSC) is an absorbing candidate for cell therapy in treating spinal cord injury (SCI) due to its great potential for multiple cell differentiation, mighty paracrine secretion as well as vigorous immunomodulatory effect, of which are beneficial to the improvement of functional recovery post SCI. However, the therapeutic effects of MSC on SCI have been limited because of the gradual loss of MSC stemness in the process of expanding culture. Therefore, in this study, we aimed to maintain those beneficial properties of MSC via three-dimensional spheroid cell culture and then compared them with conventionally-cultured MSCs in the treatment of SCI both in vitro and in vivo with the aid of two-photon microscope. We found that 3D human placenta-derived MSCs (3D-HPMSCs) demonstrated a significant increase in secretion of anti-inflammatory factors and trophic factors like VEGF, PDGF, FGF via QPCR and Bio-Plex assays, and showed great potentials on angiogenesis and neurite morphogenesis when co-cultured with HUVECs or DRGs in vitro. After transplantation into the injured spinal cord, 3D-HPMSCs managed to survive for the entire experiment and retained their advantageous properties in secretion, and exhibited remarkable effects on neuroprotection by minimizing the lesion cavity, inhibiting the inflammation and astrogliosis, and promoting angiogenesis. Further investigation of axonal dieback via two-photon microscope indicated that 3D-HPMSCs could effectively alleviate axonal dieback post injury. Further, mice only treated with 3D-HPMSCs obtained substantial improvement of functional recovery on electrophysiology, BMS score, and Catwalk analysis. RNA sequencing suggested that the 3D-HPMSCs structure organization-related gene was significantly changed, which was likely to potentiate the angiogenesis and inflammation regulation after SCI. These results suggest that 3D-HPMSCs may hold great potential for the treatment of SCI.

Decellularized Porcine Cartilage Scaffold; Validation of Decellularization and Evaluation of Biomarkers of Chondrogenesis

Osteoarthritis is a major concern in the United States and worldwide. Current non-surgical and surgical approaches alleviate pain but show little evidence of cartilage restoration. Cell-based treatments may hold promise for the regeneration of hyaline cartilage-like tissue at the site of injury or wear. Cell-cell and cell-matrix interactions have been shown to drive cell differentiation pathways. Biomaterials for clinically relevant applications can be generated from decellularized porcine auricular cartilage. This material may represent a suitable scaffold on which to seed and grow chondrocytes to create new cartilage. In this study, we used decellularization techniques to create an extracellular matrix scaffold that supports chondrocyte cell attachment and growth in tissue culture conditions. Results presented here evaluate the decellularization process histologically and molecularly. We identified new and novel biomarker profiles that may aid future cartilage decellularization efforts. Additionally, the resulting scaffold was characterized using scanning electron microscopy, fluorescence microscopy, and proteomics. Cellular response to the decellularized scaffold was evaluated by quantitative real-time PCR for gene expression analysis.

Osteoarthritis: Novel Molecular Mechanisms Increase Our Understanding of the Disease Pathology

Although osteoarthritis (OA) is the most common musculoskeletal condition that causes significant health and social problems worldwide, its exact etiology is still unclear. With an aging and increasingly obese population, OA is becoming even more prevalent than in previous decades. Up to 35% of the world’s population over 60 years of age suffers from symptomatic (painful, disabling) OA. The disease poses a tremendous economic burden on the health-care system and society for diagnosis, treatment, sick leave, rehabilitation, and early retirement. Most patients also experience sleep disturbances, reduced capability for exercising, lifting, and walking and are less capable of working, and maintaining an independent lifestyle. For patients, the major problem is disability, resulting from joint tissue destruction and pain. So far, there is no therapy available that effectively arrests structural deterioration of cartilage and bone or is able to successfully reverse any of the existing structural defects. Here, we elucidate novel concepts and hypotheses regarding disease progression and pathology, which are relevant for understanding underlying the molecular mechanisms as a prerequisite for future therapeutic approaches. Emphasis is placed on topographical modeling of the disease, the role of proteases and cytokines in OA, and the impact of the peripheral nervous system and its neuropeptides.

Comprehensive analysis of lncRNA and mRNA based on expression microarray profiling reveals different characteristics of osteoarthritis between Tibetan and Han patients

Background

Osteoarthritis (OA) is thought to be the most prevalent chronic joint disease, especially in Tibet of China. Here, we aimed to explore the integrative lncRNA and mRNA landscape between the OA patients of Tibet and Han.

Methods

The lncRNA and mRNA expression microarray profiling was performed by SurePrint G3 Human Gene Expression 8x60K v2 Microarray in articular cartilage samples from OA patients of Han nationality and Tibetans, followed by GO, KEGG, and trans-regulation and cis-regulation analysis of lncRNA and mRNA.

Results

We found a total of 117 lncRNAs and 297 mRNAs differently expressed in the cartilage tissues of Tibetans (n = 5) comparing with those of Chinese Han (n = 3), in which 49 lncRNAs and 158 mRNAs were upregulated, and 68 lncRNAs and 139 mRNAs were downregulated. GO and KEGG analysis showed that several unreported biological processes and signaling pathways were particularly identified. LncRNA-mRNA co-expression analysis revealed a remarkable lncRNA-mRNA relationship, in which OTOA may play a critical role in the different mechanisms of the OA progression between Tibetans and Chinese Han.

Conclusion

This study identified different lncRNA/mRNA expression profiling between OA patients of Tibetans and Han, which were involved in many characteristic biological processes and signaling pathways.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02213-y.

An integrated analysis of the competing endogenous RNA network and co-expression network revealed seven hub long non-coding RNAs in osteoarthritis

Aims

This study aimed to uncover the hub long non-coding RNAs (lncRNAs) differentially expressed in osteoarthritis (OA) cartilage using an integrated analysis of the competing endogenous RNA (ceRNA) network and co-expression network.

Methods

Expression profiles data of ten OA and ten normal tissues of human knee cartilage were obtained from the Gene Expression Omnibus (GEO) database (GSE114007). The differentially expressed messenger RNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the edgeR package. We integrated human microRNA (miRNA)-lncRNA/mRNA interactions with DElncRNA/DEmRNA expression profiles to construct a ceRNA network. Likewise, lncRNA and mRNA expression profiles were used to build a co-expression network with the WGCNA package. Potential hub lncRNAs were identified based on an integrated analysis of the ceRNA network and co-expression network. StarBase and Multi Experiment Matrix databases were used to verify the lncRNAs.

Results

We detected 1,212 DEmRNAs and 49 DElncRNAs in OA and normal knee cartilage. A total of 75 dysregulated lncRNA-miRNA interactions and 711 dysregulated miRNA-mRNA interactions were obtained in the ceRNA network, including ten DElncRNAs, 69 miRNAs, and 72 DEmRNAs. Similarly, 1,330 dysregulated lncRNA-mRNA interactions were used to construct the co-expression network, which included ten lncRNAs and 407 mRNAs. We finally identified seven hub lncRNAs, named MIR210HG, HCP5, LINC00313, LINC00654, LINC00839, TBC1D3P1-DHX40P1, and ISM1-AS1. Subsequent enrichment analysis elucidated that these lncRNAs regulated extracellular matrix organization and enriched in osteoclast differentiation, the FoxO signalling pathway, and the tumour necrosis factor (TNF) signalling pathway in the development of OA.

Conclusion

The integrated analysis of the ceRNA network and co-expression network identified seven hub lncRNAs associated with OA. These lncRNAs may regulate extracellular matrix changes and chondrocyte homeostasis in OA progress.

Cite this article:Bone Joint Res. 2020;9(3):90–98.