1. bookVolumen 16 (2022): Heft 4 (August 2022)
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1875-855X
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01 Jun 2007
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Long noncoding and micro-RNA expression in a model of articular chondrocyte degeneration induced by stromal cell-derived factor-1

Online veröffentlicht: 31 Aug 2022
Volumen & Heft: Volumen 16 (2022) - Heft 4 (August 2022)
Seitenbereich: 169 - 179
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
1875-855X
Erstveröffentlichung
01 Jun 2007
Erscheinungsweise
6 Hefte pro Jahr
Sprachen
Englisch

Osteoarthritis is a chronic and progressive multifactorial disease characterized by subchondral bone destruction, reduced numbers of chondrocytes, and degradation of the cartilaginous matrix [1,2,3]. Long noncoding ribonucleic acids (lncRNAs) and microRNAs (miRNAs) play important roles in mediating gene regulatory pathways in the pathogenesis of osteoarthritis and other diseases, including acute early phase spinal cord injury [4,5,6]. Aberrant expression of lncRNAs and miRNAs is associated with the development of osteoarthritis and may play regulatory roles in its pathogenesis [7,8,9]. About 4700 lncRNAs are expressed aberrantly in cartilage from patients with osteoarthritis compared with normal cartilage from control patients [10]. lncRNAs play an important regulatory role in the processes of joint synovial inflammation, cartilage matrix synthesis and metabolism, angiogenesis, chondrocyte autophagy, apoptosis, and other factors associated with osteoarthritis [11,12,13].

Stromal cell-derived factor-1 (SDF-1) is found at significantly higher levels in the synovial fluid of patients with osteoarthritis and has strong effects to induce cartilage matrix degradation. The SDF-1/chemokine (CXC motif) receptor 4 (CXCR4) signaling pathway plays a key role in the pathological process of cartilage degeneration in animal models and increases interleukin (IL)-6 production by human synovial fibroblasts [14,15,16,17]. Synovial tissue of the knee joints in patients with osteoarthritis can produce SDF-1 at a higher concentration than the synovial tissue of healthy knee joints. SDF-1 can interact with CXCR4-specific receptors on the surface of cartilage to activate the SDF-1/CXCR4 signaling pathway, which activates the extracellular signal-regulating enzyme (Erk) and related kinase (p38 mitogen-activated protein (MAP) kinase) signaling pathways, promoting the release of matrix metalloproteinases (MMP) from the cartilage matrix, which degrade the type II collagen and aggrecan substrates in the cartilage matrix, ultimately degenerating the articular cartilage and inducing osteoarthritis [18,19,20]. lncRNA-H19 stimulates osteogenic differentiation of bone marrow mesenchymal stem cells by regulating SDP-1 expression via miRNA-149 [21]. miRNA-126-silenced mice showed that miRNA-126 can regulate the expression of SDF-1 in endothelial cells [22]. miRNA-141-3p regulator of SDF-1 in bone marrow stromal cells may play an important role in the age-dependent pathophysiology of the murine and human bone marrow niche [23]. These studies indicate that the expression of SDP-1 in tissues and cells may be regulated by a multifaceted network of lncRNA and miRNA.

Here, we examined the expression of miRNAs and lncRNAs in an SDF-1-induced model of chondrocyte degeneration. Subsequently, we used microarrays to analyze the differential expression of the identified miRNAs and lncRNAs. We also analyzed the differential expression of lncRNAs in terms of transcript length distribution, classification, and exon number. Bioinformatics analysis was used to clarify the interaction between differentially expressed lncRNAs and miRNAs. A gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to identify the critical biological processes and pathways.

Methods
Materials and osteoarthritis cartilage modeling

All cartilage tissue was obtained from patients diagnosed with knee osteoarthritis who underwent total knee replacement at the First Affiliated Hospital of Kunming Medical University (March 2018 to March 2019). The cartilaginous tissue remaining on the surface of the tibial plateau and femoral condyle after osteotomy was collected during the surgery. The cartilage tissue specimen donors were informed of the research in writing and provided their documented consent before the specimens were collected. The present study was approved by the ethics committee of the First Affiliated Hospital of Kunming Medical University (2018 Lun Shen L No. 21), and the study protocols were in compliance with relevant national regulations and laws, including the ethical principles of the China Food and Drug Administration Good Clinical Practice for Medical Devices and People's Republic of China Regulations for the Management of Medical Institutions (promulgated by the Order No. 149 of the State Council on February 26, 1994; and revised in accordance with the Decision of the State Council on Amending Some Administrative Regulations on February 6, 2016), and international medical ethics documents, including the International Conference on Harmonisation Good Clinical Practice (ICH-GCP) and the Declaration of Helsinki and its contemporary (2013) revisions. After a diagnosis of osteoarthritis in accordance with the criteria described by Altman et al. [24], 10 patients (4 male and 6 female) underwent artificial knee arthroplasty due to osteoarthritis. The patients were aged from 55 to 75 years and had a gross visual grade of cartilage degeneration score of 0 or 1 point, where 0 points indicated a smooth articular surface and usual color, and 1 point indicated a rough articular surface, small cracks, and dark color [25]. Patients with liver or kidney disease, connective tissue disease, endocrine disease, serious cardiovascular disease, and tumors were excluded. The cartilage tissue was trimmed to dimensions 2 mm × 2 mm × 1 mm under aseptic conditions. Ten pieces (100 pieces in total from the 10 different patients) of cartilage tissue were placed separately into preprepared high-glucose Dulbecco's modified Eagle's medium (DMEM) for digestion and culture. Chondrocytes from the first-generation culture were divided equally without special selection into an experimental and control group (n = 3 each). The density of autologous chondrocytes in the carrier was about 1.6–2.0 × 105 cells/cm2. The cell culture medium in the 2 groups was high-glucose DMEM containing 10% fetal bovine serum and penicillin–streptomycin. In the experimental group, 100 ng/mL SDF-1 (R&D Systems) was added to the chondrocytes [17], and the control group was untreated. The chondrocytes in the 2 groups were cultured under the same conditions for 48 h using an improved method [19, 20], although a vehicle control was not used to conserve resources.

RNA extraction

Total RNA samples were extracted using an RNeasy Mini Kit (catalog No. 74106; Qiagen). The extraction was performed in accordance with the standard operating procedure handbook provided by the manufacturer. The extracted total RNA was examined qualitatively using a Bioanalyzer 2100 system (Agilent Technologies) and quantified using a Qubit 3.0 Fluorometer (Life Technologies) and NanoDrop One spectrophotometer (Thermo Fisher Scientific).

RNA amplification and labeling

Total RNA was amplified and labeled using a Low-Input QuickAmp WT Labeling Kit (catalog No. 5190-2943; Agilent Technologies) according to the kit instructions; the labeled complementary RNA was purified using an RNeasy Mini Kit (catalog No. 74106; Qiagen).

Hybridization

The NimbleGen SeqCap EZ Hybridization and Wash Kit (Roche) for permutation hybridization was used to enrich specific target regions according to protocols specified by the manufacturer.

Data collection

An Axon 4000B fluorescent scanner (Molecular Probes) was used to scan hybridized microarray slides and convert the scanning signal into a digital signal, and the low quality and weak signal data points were excluded. Fold change (FC) ≥2 was the cutoff criterion. A Student t test was performed to calculate the scanning signal values of the 2 groups and to obtain the log2 (ratio) and P value for each probe. When the ratio of the intensity of the hybridization signal between the experimental group and the control group was ≥2, the expression was defined as upregulated; otherwise, the expression was defined as downregulated. The miRNA screening conditions were FC ≥2 and P < 0.05 or log2 (ratio) ≥0.8.

Gene Ontology and KEGG analysis

Gene ontology (GO) analysis was performed to describe the functional properties of differentially expressed miRNAs. GO analysis included molecular function (MF), biological process (BP), and cellular component (CC). KEGG signaling pathway analysis was performed to describe the biological pathways of differentially expressed miRNAs.

Protein–protein interaction network analysis

To elucidate the interactions between differentially expressed miRNAs, a database of interacting genes was searched, and Cytoscape visualization was used to integrate biological models with biological graphics visualization tools for molecular interaction networks [26]. Differentially expressed miRNAs with FC >4 and P < 0.05 were identified, and the STRING online tool [27] was used to analyze differentially expressed miRNAs with a combined protein–protein interaction (PPI) score >0.4 as the cutoff value.

Statistical analysis

Data were analyzed using SPSS Statistics for Windows (version 17.0; SPSS). Differentially expressed (DE) levels of miRNAs and lncRNAs were compared using paired-sample t tests. Student t tests were to compare values between the groups. The differentially expressed lncRNAs and differentially expressed miRNAs with a FC threshold >2 and P < 0.05 were regarded as significant.

Results
Morphological changes in cell culture

Chondrocytes from the first-generation culture of osteoarthritis tissue were cultured with SDF-1 for 48 h. The chondrocytes in the experimental group were irregular and long spindle–shaped, with a low refractive index and fuzzy structure in living cells, while the chondrocytes in the control group were spindle-shaped or oval, with an intact nucleus, high refractive index, and clear structure in living cells (Figures 1A and B).

Figure 1

Morphology of chondrocytes in the 2 groups (×100). A. Chondrocytes in the experimental group were cultured with SDF-1 for 48 h. B. Morphology of chondrocytes in the control group. SDF-1, stromal cell-derived factor-1.

Difference visualization

lncRNA analysis revealed a total of 52,741 lncRNAs with changed expression. Further analysis showed that of these, the expression of 186 lncRNAs was changed significantly; 88 were upregulated, and 98 were downregulated. A total of 119,205 miRNAs had changed their level of expression, and the expression of 684 miRNAs had changed significantly. The heatmap, scatter plot, and volcano plot of the differentially expressed miRNAs and lncRNAs are shown in Figure 2 (miRNAs, A–C; lncRNAs, D–F).

Figure 2

Analysis of miRNAs and lncRNAs. A. Heatmap of the differentially expressed (DE) miRNAs. B. Scatter plot of the DE miRNAs. C. Volcano plot of the DE miRNAs. D. Heatmap of the DE lncRNAs. E. Scatter plot of the DE lncRNAs. F. Volcano plot of the DE lncRNAs. In the heatmap, red represents upregulated miRNAs or lncRNAs, and green represents downregulated miRNAs or lncRNAs. In the scatter plot, the X and Y values are the average normalized signal values, shown on a log2 scale. The red and green lines were set as FC lines with a default change of 2.0. Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. In the volcano plot, the X-axis is the FC (log2), and the Y-axis is P (−log10). Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. DE, differentially expressed; FC, fold change; FPKM, fragments per kilobase of transcript per million mapped fragments; lncRNAs, long noncoding ribonucleic acids; miRNAs, microRNAs; SDF1, stromal cell-derived factor-1 treated articular chondrocytes. Normal indicates articular chondrocytes untreated with SDF-1.

Differential expression analysis of lncRNAs

The top 10 most upregulated and most downregulated lncRNAs in the experimental group are shown in Table 1. Horizontal comparisons based on the transcript structure of the lncRNAs were performed, including the transcript length distribution, classification, and exon quantity differences. The length of lncRNAs was mainly concentrated at approximately 1000 bp, and lncRNAs constituted various RNA molecules (Figure 3A). The traditional classification method of lncRNAs is based on the location of the transcript in the genome and includes 5 major categories: (1) the sense group, (2) the antisense group, (3) the bidirectional group, (4) the intronic group, and (5) the intergenic group (Figure 3B).

Figure 3

Expression signatures of dysregulated lncRNAs in SDF-1-induced articular chondrocyte degeneration. A. Length distribution showed that dysregulated lncRNAs were mainly concentrated between 700 bp and 3000 bp. B. Differential lncRNAs were classified according to their genomic architecture.

Top 10 most upregulated and most downregulated lncRNAs in chondrocytes from the SDF-1-induced model of articular chondrocyte degeneration

Upregulated lncRNAsDownregulated lncRNAs

lncRNA IDPFClncRNA IDPFC
NONHSAT094312.25.51E–0510.27NONHSAT246243.14.01E–069.44
NONHSAT060379.23.42E–178.19NONHSAT217441.13.97E–078.57
NONHSAT207507.11.60E–168.12NONHSAT238505.16.22E–057.07
NONHSAT166467.15.44E–077.77NONHSAT258030.15.57E–056.86
NONHSAT198879.13.39E–067.75NONHSAT176410.14.59E–066.81
NONHSAT248596.11.21E–117.61NONHSAT022132.20.0001386.68
NONHSAT152279.12.89E–067.41NONHSAT119402.22.11E–066.59
NONHSAT000091.29.96E–057.21NONHSAT022138.20.0001696.58
ENST000005594584.66E–067.05NONHSAT229871.15.25E–056.53
NONHSAT038052.21.00E–066.87NONHSAT225394.14.07E–056.23

FC, fold change; SDF-1, stromal cell-derived factor-1.

Gene ontology and KEGG analyses

The GO analysis showed that the signaling pathways of miRNAs and their target genes are enriched in receptor regulation activities (MF), secondary lysosomes (cell components), lipopolysaccharide regulatory signaling pathways (biological processes), type I interferon signaling pathways, and ionic transmembrane transporter activity regulation (Figure 4). Pathway analysis indicated that miRNAs and their target genes are enriched in cytokine–cytokine receptor interactions, osteoclast differentiation, the nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) signaling pathway, the transforming growth factor (TGF-β) signaling pathway, and the ion signaling pathway, as shown in Figure 5.

Figure 4

GO analysis of differentially expressed genes. GO annotations of mRNAs with top 30 enrichment scores. The circles represent biological processes; the triangles represent cell components; and the squares represent MF. GO, gene ontogeny; MF, molecular functions.

Figure 5

KEGG signaling pathway analysis of differentially expressed genes. Top 30 for KEGG enrichment. KEGG, Kyoto Encyclopedia of Genes and Genomes.

PPI network construction

The PPI network identified genes for 10 proteins, interferon-γ (IFN-γ) inducible CXC 10 kDa chemokine chemotactic for monocytes and T-lymphocytes (CXCL10), interferon-α-stimulated gene 15-kDa protein (ISG15), v-myc myelocytomatosis viral oncogene homolog protein (MYC), interferon inducible myxovirus resistance protein MxA p78 (MX1), p59 2′,5′-oligoadenylate synthetase-like protein (OASL), interferon-induced with tetratricopeptide repeats 1 protein (IFIT1), radical S-adenosyl methionine domain containing 2 protein (RSAD2), second interferon-induced myxo-virus resistance 2 protein MxB p78 (MX2), interferon-induced protein 44 like protein (IFI44L), and bone marrow stromal tetherin antigen 2 (BST2), that have a higher possibility of being involved in the mechanism of chondrocyte degeneration (Table 2) and showed a network of upregulated and downregulated genes (Figure 6).

Figure 6

PPI network analysis of the top 10 differentially expressed genes. Nodes represent genes for the proteins indicated. Lines indicate interactions between genes. Red indicates upregulated genes, and green indicates downregulated genes. PPI, protein–protein interaction.

PPI network core (top 10) genes in the SDF-1-induced model of articular chondrocyte degeneration

ProteinDegreeEccentricityEdge count
CXCL1016416
ISG1512412
MYC11511
MX110510
OASL10510
IFIT110510
RSAD210510
MX210510
IFI44L10510
BST2858

BST2, bone marrow stromal tetherin antigen 2; CXCL10, interferon γ inducible CXC 10 kDa chemokine chemotactic for monocytes and T-lymphocytes; IFI44L, interferon-induced protein 44 like protein; IFIT1, interferon-induced with tetratricopeptide repeats 1 protein; ISG15, interferon-α-stimulated gene 15-kDa protein; MX1, interferon inducible myxovirus resistance protein MxA p78; MX2, second interferon-induced myxovirus resistance 2 protein MxB p78; MYC, v-myc myelocytomatosis viral oncogene homolog protein; OASL, p59 2′,5′-oligoadenylate synthetase-like protein; PPI, protein–protein interaction; RSAD2, radical S-adenosyl methionine domain containing 2 protein; SDF-1, stromal cell-derived factor-1.

Discussion

RNA expression data have been uploaded to the Sequence Read Archive database, and the BioProject ID is PRJNA638147. lncRNAs can compete with competing endogenous RNAs (ceRNA), as miRNA sponges, to play a regulatory role [7]. lncRNAs participate in gene regulation as guides, signals, baits, and scaffolds. The specific regulatory mechanism is mainly divided into 4 aspects, which regulate the degeneration of articular cartilage by regulating transcription factors and transcription processes and mediating post-transcriptional regulation of miRNA and mRNA, and regulation of nuclear structure [28]. Most research studies have focused on the function of lncRNAs as a “sponge,” in which lncRNA undergoes an endogenous competition interaction with miRNA that has a shared binding site to inhibit the regulatory effect of the miRNA on target mRNA, thereby affecting protein expression. The more binding sites there are, the stronger the “sponge effect” and the more obvious the inhibitory effect of lncRNA on miRNA. Under normal circumstances, various RNAs (such as lncRNA, miRNA, and mRNA) maintain a balanced state, and when an RNA is abnormally expressed, the balance is disrupted, and this results in disease [29]. Noncoding RNA with a common response element (miRNA response elements [MRE]) can compete with mRNA endogenously to bind miRNA and inhibit miRNA-mediated negative regulation of mRNA. Similarly, reducing ceRNA levels upregulate target gene expression, which may ultimately affect cellular biological processes [30].

Receptor regulatory factors such as Toll-like receptors (TLRs) are evolutionarily conserved molecules that promote immune responses by recognizing molecular patterns related to microorganisms. During infection, TLR signaling is necessary for the proper activation of the immune response [31]. TLRs produce large amounts of interleukin (IL)-1β and tumor necrosis factor (TNF)-α inflammatory factors by activating the NK-κB inflammatory signaling pathway. Liu et al. [32] found that the expression of TLR-2, NF-κB, MMP-13, and related inflammatory factors was significantly upregulated with the severity of osteoarthritis lesions, suggesting that the TLR-2/NF-κB signaling pathway may be involved in the occurrence of osteoarthritis.

When intra-articular hemorrhage occurs, lysosomes release degrading enzymes, and decreased proteoglycan concentration reduces chondrocyte synthesis activity and induces articular cartilage degeneration [33]. A high concentration of SDF-1 can increase its interaction with CXCR4 on the surface of chondrocytes and accelerate the degradation of type II collagen through the upregulation of MMPs, also leading to cartilage degeneration [34]. Chondrocytes are nonexcitable cells. However, the multiple ion channels present on the cell membrane are the basis for the cell to carry out various life activities, including transporting ions necessary for cell metabolism, regulating osmotic pressure inside and outside the cell, participating in the formation of electrical impulses, and mediating in signal transmission to adapt organisms to environmental conditions [35, 36].

Pathway analysis showed that miRNAs and their target genes were enriched in cytokine–cytokine receptor interaction, osteoclast differentiation, NF-κB signaling pathway, TGF-β signaling pathway, and Ca2+ signaling. Cytokines regulate the balance of anabolic and catabolic metabolism of cartilage matrix. They are divided into catabolic cytokines and anabolic cytokines according to their roles in the regulation of metabolism. The balance and imbalance between them are root causes of the degradation and destruction of the cartilage matrix in osteoarthritis. Cytokines, including TNF-α, IL-1, IL-6, IL-2, and IFN-γ, are involved in this pathway. These cytokines penetrate the synovium to induce an inflammatory response. In addition, they can activate synovial cells and stimulate the release of MMPs into the synovial fluid, leading to cartilage degradation [37, 38].

Currently, the most studied cytokines that promote chondrocyte catabolism are IL-1 and TNF-α. IL-1 not only inhibits the synthesis of the characteristic matrix components type II collagen and aggrecan by articular chondrocytes, but also stimulates articular chondrocytes to secrete protease that degrades cartilage matrix components, inhibits the expression of type I and type II collagen by articular chondrocytes, and promotes the degeneration of articular chondrocytes [39]. TNF-α also plays an important role in osteoarthritis cartilage degeneration. The mechanism of action of TNF-α is similar to that of IL-1 and includes promoting the generation of MMP and inhibiting the synthesis of cartilage matrix. TNF inhibits the expression of type II collagen and connexin genes through the MAP kinase/extracellular signal-regulated kinase (ERK) kinase (MEK) 1/2 and NF-κB pathways, which in turn interferes with the synthesis and reconstruction of articular cartilage [40]. The NF-κB transcription factor regulates gene expression, and the NF-κB signaling pathway is activated in articular cartilage and synovial cells in osteoarthritis [41]. NF-κB regulates the response to joint injury and inflammation by regulating cytokines, including IL-1β and TNF-α [39,40,41,42,43,44,45,46].

The PPI network revealed genes for 10 proteins that have a high possibility of being associated with the pathological process of chondrocyte degeneration: CXCL10, ISG15, MYC, MX1, OASL, IFIT1, RSAD2, MX2, IFI44L, and BST2. Chemokines, mainly CXC and CC, and their corresponding receptors are expressed in human chondrocytes, and their expression is increased in osteoarthritis articular cartilage [47]. Chemokines are involved in cartilage destruction by inducing the expression of related enzymes, mainly N-acetyl-β-d-glucosidase (NAG) and MMP. NAG is the main lysosomal glycosidase in osteoarthritis synovial fluid and catalyzes the hydrolysis of glucosamine polysaccharides, causing cartilage destruction [48].

In osteoarthritis, the cartilage surface is activated by a variety of chemokines, releasing enzymes that mediate the destruction of the cartilage matrix [48, 49]. Kostopoulou et al. [50] and Tardif et al. [51] found that an osteoarthritis-related miRNA can inhibit MMP-13.

MYC is not strongly expressed in normal chondrocyte nuclei, but is scattered in apoptotic chondrocyte nuclei. The degree of articular chondrocyte apoptosis in osteoarthritis is positively correlated with the degree of cartilage degeneration, and MYC participates in the process of chondrocyte apoptosis. The mechanism of MYC causing apoptosis may be due to an imbalance in the normal cell cycle, which inhibits cell growth [52].

In-depth studies of cytokine interactions, osteoarthritis signaling pathways, and miRNAs related to lncRNAs are required to investigate the relationship between lncRNAs and miRNAs, to elucidate the molecular mechanism of osteochondrocyte degeneration, and provide a new basis and targets for the effective diagnosis and treatment of osteoarthritis.

Figure 1

Morphology of chondrocytes in the 2 groups (×100). A. Chondrocytes in the experimental group were cultured with SDF-1 for 48 h. B. Morphology of chondrocytes in the control group. SDF-1, stromal cell-derived factor-1.
Morphology of chondrocytes in the 2 groups (×100). A. Chondrocytes in the experimental group were cultured with SDF-1 for 48 h. B. Morphology of chondrocytes in the control group. SDF-1, stromal cell-derived factor-1.

Figure 2

Analysis of miRNAs and lncRNAs. A. Heatmap of the differentially expressed (DE) miRNAs. B. Scatter plot of the DE miRNAs. C. Volcano plot of the DE miRNAs. D. Heatmap of the DE lncRNAs. E. Scatter plot of the DE lncRNAs. F. Volcano plot of the DE lncRNAs. In the heatmap, red represents upregulated miRNAs or lncRNAs, and green represents downregulated miRNAs or lncRNAs. In the scatter plot, the X and Y values are the average normalized signal values, shown on a log2 scale. The red and green lines were set as FC lines with a default change of 2.0. Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. In the volcano plot, the X-axis is the FC (log2), and the Y-axis is P (−log10). Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. DE, differentially expressed; FC, fold change; FPKM, fragments per kilobase of transcript per million mapped fragments; lncRNAs, long noncoding ribonucleic acids; miRNAs, microRNAs; SDF1, stromal cell-derived factor-1 treated articular chondrocytes. Normal indicates articular chondrocytes untreated with SDF-1.
Analysis of miRNAs and lncRNAs. A. Heatmap of the differentially expressed (DE) miRNAs. B. Scatter plot of the DE miRNAs. C. Volcano plot of the DE miRNAs. D. Heatmap of the DE lncRNAs. E. Scatter plot of the DE lncRNAs. F. Volcano plot of the DE lncRNAs. In the heatmap, red represents upregulated miRNAs or lncRNAs, and green represents downregulated miRNAs or lncRNAs. In the scatter plot, the X and Y values are the average normalized signal values, shown on a log2 scale. The red and green lines were set as FC lines with a default change of 2.0. Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. In the volcano plot, the X-axis is the FC (log2), and the Y-axis is P (−log10). Red points (FC >2) indicate upregulated miRNAs or lncRNAs, and blue points (FC ≤2) indicate downregulated miRNAs or lncRNAs. DE, differentially expressed; FC, fold change; FPKM, fragments per kilobase of transcript per million mapped fragments; lncRNAs, long noncoding ribonucleic acids; miRNAs, microRNAs; SDF1, stromal cell-derived factor-1 treated articular chondrocytes. Normal indicates articular chondrocytes untreated with SDF-1.

Figure 3

Expression signatures of dysregulated lncRNAs in SDF-1-induced articular chondrocyte degeneration. A. Length distribution showed that dysregulated lncRNAs were mainly concentrated between 700 bp and 3000 bp. B. Differential lncRNAs were classified according to their genomic architecture.
Expression signatures of dysregulated lncRNAs in SDF-1-induced articular chondrocyte degeneration. A. Length distribution showed that dysregulated lncRNAs were mainly concentrated between 700 bp and 3000 bp. B. Differential lncRNAs were classified according to their genomic architecture.

Figure 4

GO analysis of differentially expressed genes. GO annotations of mRNAs with top 30 enrichment scores. The circles represent biological processes; the triangles represent cell components; and the squares represent MF. GO, gene ontogeny; MF, molecular functions.
GO analysis of differentially expressed genes. GO annotations of mRNAs with top 30 enrichment scores. The circles represent biological processes; the triangles represent cell components; and the squares represent MF. GO, gene ontogeny; MF, molecular functions.

Figure 5

KEGG signaling pathway analysis of differentially expressed genes. Top 30 for KEGG enrichment. KEGG, Kyoto Encyclopedia of Genes and Genomes.
KEGG signaling pathway analysis of differentially expressed genes. Top 30 for KEGG enrichment. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure 6

PPI network analysis of the top 10 differentially expressed genes. Nodes represent genes for the proteins indicated. Lines indicate interactions between genes. Red indicates upregulated genes, and green indicates downregulated genes. PPI, protein–protein interaction.
PPI network analysis of the top 10 differentially expressed genes. Nodes represent genes for the proteins indicated. Lines indicate interactions between genes. Red indicates upregulated genes, and green indicates downregulated genes. PPI, protein–protein interaction.

Top 10 most upregulated and most downregulated lncRNAs in chondrocytes from the SDF-1-induced model of articular chondrocyte degeneration

Upregulated lncRNAs Downregulated lncRNAs

lncRNA ID P FC lncRNA ID P FC
NONHSAT094312.2 5.51E–05 10.27 NONHSAT246243.1 4.01E–06 9.44
NONHSAT060379.2 3.42E–17 8.19 NONHSAT217441.1 3.97E–07 8.57
NONHSAT207507.1 1.60E–16 8.12 NONHSAT238505.1 6.22E–05 7.07
NONHSAT166467.1 5.44E–07 7.77 NONHSAT258030.1 5.57E–05 6.86
NONHSAT198879.1 3.39E–06 7.75 NONHSAT176410.1 4.59E–06 6.81
NONHSAT248596.1 1.21E–11 7.61 NONHSAT022132.2 0.000138 6.68
NONHSAT152279.1 2.89E–06 7.41 NONHSAT119402.2 2.11E–06 6.59
NONHSAT000091.2 9.96E–05 7.21 NONHSAT022138.2 0.000169 6.58
ENST00000559458 4.66E–06 7.05 NONHSAT229871.1 5.25E–05 6.53
NONHSAT038052.2 1.00E–06 6.87 NONHSAT225394.1 4.07E–05 6.23

PPI network core (top 10) genes in the SDF-1-induced model of articular chondrocyte degeneration

Protein Degree Eccentricity Edge count
CXCL10 16 4 16
ISG15 12 4 12
MYC 11 5 11
MX1 10 5 10
OASL 10 5 10
IFIT1 10 5 10
RSAD2 10 5 10
MX2 10 5 10
IFI44L 10 5 10
BST2 8 5 8

Jamshidi A, Pelletier JP, Martel-Pelletier J. Machine-learning-based patient-specific prediction models for knee osteoarthritis. Nat Rev Rheumatol. 2019; 15:49–60. JamshidiA PelletierJP Martel-PelletierJ Machine-learning-based patient-specific prediction models for knee osteoarthritis Nat Rev Rheumatol 2019 15 49 60 10.1038/s41584-018-0130-530523334 Search in Google Scholar

Nguyen US, Zhang Y, Zhu Y, Niu J, Zhang B, Felson DT. Increasing prevalence of knee pain and symptomatic knee osteoarthritis: survey and cohort data. Ann Intern Med. 2011; 155:725–32. NguyenUS ZhangY ZhuY NiuJ ZhangB FelsonDT Increasing prevalence of knee pain and symptomatic knee osteoarthritis: survey and cohort data Ann Intern Med 2011 155 725 32 10.7326/0003-4819-155-11-201112060-00004340802722147711 Search in Google Scholar

Aguiar GC, Queiroz-Junior CM, Sitta GL, Amaral FA, Teixeira MM, Caliari MV, Ferreira AJ. Mefenamic acid decreases inflammation but not joint lesions in experimental osteoarthritis. Int J Exp Pathol. 2016; 97:438–46. AguiarGC Queiroz-JuniorCM SittaGL AmaralFA TeixeiraMM CaliariMV FerreiraAJ Mefenamic acid decreases inflammation but not joint lesions in experimental osteoarthritis Int J Exp Pathol 2016 97 438 46 10.1111/iep.12216537022728370591 Search in Google Scholar

Jones IA, Togashi R, Wilson ML, Heckmann N, Vangsness CT Jr. Intra-articular treatment options for knee osteoarthritis. Nat Rev Rheumatol. 2019; 15:77–90. JonesIA TogashiR WilsonML HeckmannN VangsnessCTJr Intra-articular treatment options for knee osteoarthritis Nat Rev Rheumatol 2019 15 77 90 10.1038/s41584-018-0123-4639084330498258 Search in Google Scholar

Stefani G, Slack FJ. Small non-coding RNAs in animal development. Nat Rev Mol Cell Biol. 2008; 9:219–30. StefaniG SlackFJ Small non-coding RNAs in animal development Nat Rev Mol Cell Biol 2008 9 219 30 10.1038/nrm234718270516 Search in Google Scholar

Shi Z, Ning G, Zhang B, Yuan S, Zhou H, Pan B, et al. Signatures of altered long noncoding RNAs and messenger RNAs expression in the early acute phase of spinal cord injury. J Cell Physiol. 2019; 234:8918–27. ShiZ NingG ZhangB YuanS ZhouH PanB Signatures of altered long noncoding RNAs and messenger RNAs expression in the early acute phase of spinal cord injury J Cell Physiol 2019 234 8918 27 10.1002/jcp.2756030341912 Search in Google Scholar

Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X, et al. LncRNA-Disease: a database for long-non-coding RNA-associated diseases. Nucleic Acids Res. 2013; 41(Database issue):D983–6. ChenG WangZ WangD QiuC LiuM ChenX LncRNA-Disease: a database for long-non-coding RNA-associated diseases Nucleic Acids Res 2013 41 Database issue D983 6 10.1093/nar/gks1099353117323175614 Search in Google Scholar

Bao Z, Yang Z, Huang Z, Zhou Y, Cui Q, Dong D. LncRNADisease 2.0: an updated database of long non-coding RNA-associated diseases. Nucleic Acids Res. 2019; 47(D1):D1034–7. BaoZ YangZ HuangZ ZhouY CuiQ DongD LncRNADisease 2.0: an updated database of long non-coding RNA-associated diseases Nucleic Acids Res 2019 47 D1 D1034 7 10.1093/nar/gky905632408630285109 Search in Google Scholar

Kopańska M, Szala D, Czech J, Gabło N, Gargasz K, Trzeciak M, et al. MiRNA expression in the cartilage of patients with osteoarthritis. J Orthop Surg Res. 2017; 12:51. doi: 10.1186/s13018-017-0542-y. Erratum in: J Orthop Surg Res. 2017; 12:90. KopańskaM SzalaD CzechJ GabłoN GargaszK TrzeciakM MiRNA expression in the cartilage of patients with osteoarthritis J Orthop Surg Res 2017 12 51 10.1186/s13018-017-0542-y Erratum in: J Orthop Surg Res. 2017; 12:90. 537126628351380 DOI öffnenSearch in Google Scholar

Fu M, Huang G, Zhang Z, Liu J, Zhang Z, Huang Z, et al. Expression profile of long noncoding RNAs in cartilage from knee osteoarthritis patients. Osteoarthritis Cartilage. 2015; 23:423–32. FuM HuangG ZhangZ LiuJ ZhangZ HuangZ Expression profile of long noncoding RNAs in cartilage from knee osteoarthritis patients Osteoarthritis Cartilage 2015 23 423 32 10.1016/j.joca.2014.12.00125524778 Search in Google Scholar

Sun H, Peng G, Ning X, Wang J, Yang H, Deng J. Emerging roles of long noncoding RNA in chondrogenesis, osteogenesis, and osteoarthritis. Am J Transl Res. 2019; 11:16–30. SunH PengG NingX WangJ YangH DengJ Emerging roles of long noncoding RNA in chondrogenesis, osteogenesis, and osteoarthritis Am J Transl Res 2019 11 16 30 Search in Google Scholar

Hu J, Wang Z, Shan Y, Pan Y, Ma J, Jia L. Long non-coding RNA HOTAIR promotes osteoarthritis progression via miR-17-5p/FUT2/b-catenin axis. Cell Death Dis. 2018; 9:711. doi: 10.1038/s41419-018-0746-z HuJ WangZ ShanY PanY MaJ JiaL Long non-coding RNA HOTAIR promotes osteoarthritis progression via miR-17-5p/FUT2/b-catenin axis Cell Death Dis 2018 9 711 10.1038/s41419-018-0746-z DOI öffnenSearch in Google Scholar

Cen X, Huang X-Q, Sun W-T, Liu Q, Liu J. Long noncoding RNAs: a new regulatory code in osteoarthritis. Am J Transl Res. 2017; 9:4747–55. CenX HuangX-Q SunW-T LiuQ LiuJ Long noncoding RNAs: a new regulatory code in osteoarthritis Am J Transl Res 2017 9 4747 55 Search in Google Scholar

He Z, Jia M, Yu Y, Yuan C, Wang J. Roles of SDF-1/CXCR4 axis in cartilage endplate stem cells mediated promotion of nucleus pulposus cells proliferation. Biochem Biophys Res Commun. 2018; 506:94–101. HeZ JiaM YuY YuanC WangJ Roles of SDF-1/CXCR4 axis in cartilage endplate stem cells mediated promotion of nucleus pulposus cells proliferation Biochem Biophys Res Commun 2018 506 94 101 10.1016/j.bbrc.2018.10.069 Search in Google Scholar

Chen H-T, Tsou H-K, Hsu C-J, Tsai C-H, Kao C-H, Fong Y-C, Tang C-H. Stromal cell-derived factor-1/CXCR4 promotes IL-6 production in human synovial fibroblasts. J Cell Biochem. 2011; 112:1219–27. ChenH-T TsouH-K HsuC-J TsaiC-H KaoC-H FongY-C TangC-H Stromal cell-derived factor-1/CXCR4 promotes IL-6 production in human synovial fibroblasts J Cell Biochem 2011 112 1219 27 10.1002/jcb.23043 Search in Google Scholar

Dong Y, Liu H, Zhang X, Xu F, Qin L, Cheng P, et al. Inhibition of SDF-1a/CXCR4 signalling in subchondral bone attenuates post-traumatic osteoarthritis. Int J Mol Sci. 2016; 17:943. doi: 10.3390/ijms17060943 DongY LiuH ZhangX XuF QinL ChengP Inhibition of SDF-1a/CXCR4 signalling in subchondral bone attenuates post-traumatic osteoarthritis Int J Mol Sci 2016 17 943 10.3390/ijms17060943 DOI öffnenSearch in Google Scholar

Wei L, Sun X, Kanbe K, Wang Z, Sun C, Terek R, Chen Q. Chondrocyte death induced by pathological concentration of chemokine stromal cell-derived factor-1. J Rheumatol. 2006; 33:1818–26. WeiL SunX KanbeK WangZ SunC TerekR ChenQ Chondrocyte death induced by pathological concentration of chemokine stromal cell-derived factor-1 J Rheumatol 2006 33 1818 26 Search in Google Scholar

Wang K, Li Y, Han R, Cai G, He C, Wang G, Jia D. T140 blocks the SDF-1/CXCR4 signaling pathway and prevents cartilage degeneration in an osteoarthritis disease model. PLoS One. 2017; 12:e0176048. doi: 10.1371/journal.pone.0176048 WangK LiY HanR CaiG HeC WangG JiaD T140 blocks the SDF-1/CXCR4 signaling pathway and prevents cartilage degeneration in an osteoarthritis disease model PLoS One 2017 12 e0176048 10.1371/journal.pone.0176048 DOI öffnenSearch in Google Scholar

Kanbe K, Takagishi K, Chen Q. Stimulation of matrix metalloprotease 3 release from human chondrocytes by the interaction of stromal cell-derived factor 1 and CXC chemokine receptor 4. Arthritis Rheum. 2002; 46:130–7. KanbeK TakagishiK ChenQ Stimulation of matrix metalloprotease 3 release from human chondrocytes by the interaction of stromal cell-derived factor 1 and CXC chemokine receptor 4 Arthritis Rheum 2002 46 130 7 10.1002/1529-0131(200201)46:1<130::AID-ART10020>3.0.CO;2-D Search in Google Scholar

Kanbe K, Takemura T, Takeuchi K, Chen Q, Takagishi K, Inoue K. Synovectomy reduces stromal-cell-derived factor-1 (SDF-1) which is involved in the destruction of cartilage in osteoarthritis and rheumatoid arthritis. J Bone Joint Surg Br. 2004; 86:296–300. KanbeK TakemuraT TakeuchiK ChenQ TakagishiK InoueK Synovectomy reduces stromal-cell-derived factor-1 (SDF-1) which is involved in the destruction of cartilage in osteoarthritis and rheumatoid arthritis J Bone Joint Surg Br 2004 86 296 300 10.1302/0301-620X.86B2.14474 Search in Google Scholar

Li G, Yun X, Ye K, Zhao H, An J, Zhang X, et al. Long non-coding RNA-H19 stimulates osteogenic differentiation of bone marrow mesenchymal stem cells via the microRNA-149/SDF-1 axis. J Cell Mol Med. 2020; 24:4944–55. LiG YunX YeK ZhaoH AnJ ZhangX Long non-coding RNA-H19 stimulates osteogenic differentiation of bone marrow mesenchymal stem cells via the microRNA-149/SDF-1 axis J Cell Mol Med 2020 24 4944 55 10.1111/jcmm.15040 Search in Google Scholar

van Solingen C, de Boer HC, Bijkerk R, Monge M, van Oeveren-Rietdijk AM, Seghers L, et al. MicroRNA-126 modulates endothelial SDF-1 expression and mobilization of Sca-1+/Lin progenitor cells in ischaemia. Cardiovasc Res. 2011; 92:449–55. van SolingenC de BoerHC BijkerkR MongeM van Oeveren-RietdijkAM SeghersL MicroRNA-126 modulates endothelial SDF-1 expression and mobilization of Sca-1+/Lin progenitor cells in ischaemia Cardiovasc Res 2011 92 449 55 10.1093/cvr/cvr227 Search in Google Scholar

Periyasamy-Thandavan S, Burke J, Mendhe B, Kondrikova G, Kolhe R, Hunter M, et al. MicroRNA-141-3p negatively modulates SDF-1 expression in age-dependent pathophysiology of human and murine bone marrow stromal cells. J Gerontol A Biol Sci Med Sci. 2019; 74:1368–74. Periyasamy-ThandavanS BurkeJ MendheB KondrikovaG KolheR HunterM MicroRNA-141-3p negatively modulates SDF-1 expression in age-dependent pathophysiology of human and murine bone marrow stromal cells J Gerontol A Biol Sci Med Sci 2019 74 1368 74 10.1093/gerona/gly186 Search in Google Scholar

Altman RD. The classification of osteoarthritis. J Rheumatol Suppl. 1995; 43:42–3. AltmanRD The classification of osteoarthritis J Rheumatol Suppl 1995 43 42 3 Search in Google Scholar

Charalambous CP. Biochemical and metabolic abnormalities in articular cartilage from osteoarthritic human hips. II: correlation of morphology with biochemical and metabolic data. In: Banaszkiewicz P, Kader D, editors. Classic papers in orthopaedics. London: Springer-Verlag; 2014, p. 385–7. CharalambousCP Biochemical and metabolic abnormalities in articular cartilage from osteoarthritic human hips. II: correlation of morphology with biochemical and metabolic data In: BanaszkiewiczP KaderD editors. Classic papers in orthopaedics London Springer-Verlag 2014 385 7 10.1007/978-1-4471-5451-8_97 Search in Google Scholar

Smoot ME, Ono K, Ruscheinski J, Wang P-L, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics. 2011; 27:431–2. SmootME OnoK RuscheinskiJ WangP-L IdekerT Cytoscape 2.8: new features for data integration and network visualization Bioinformatics 2011 27 431 2 10.1093/bioinformatics/btq675303104121149340 Search in Google Scholar

Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021; 49(D1):D605–12. SzklarczykD GableAL NastouKC LyonD KirschR PyysaloS The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets Nucleic Acids Res 2021 49 D1 D605 12 10.1093/nar/gkaa1074777900433237311 Search in Google Scholar

Pearson MJ, Philp AM, Heward JA, Roux BT, Walsh DA, Davis ET, et al. Long intergenic noncoding RNAs mediate the human chondrocyte inflammatory response and are differentially expressed in osteoarthritis cartilage. Arthritis Rheumatol. 2016; 68:845–56. PearsonMJ PhilpAM HewardJA RouxBT WalshDA DavisET Long intergenic noncoding RNAs mediate the human chondrocyte inflammatory response and are differentially expressed in osteoarthritis cartilage Arthritis Rheumatol 2016 68 845 56 10.1002/art.39520495000127023358 Search in Google Scholar

Li Y-F, Li S-H, Liu Y, Luo Y-T. Long noncoding RNA CIR promotes chondrocyte extracellular matrix degradation in osteoarthritis by acting as a sponge for Mir-27b. Cell Physiol Biochem. 2017; 43:602–10. LiY-F LiS-H LiuY LuoY-T Long noncoding RNA CIR promotes chondrocyte extracellular matrix degradation in osteoarthritis by acting as a sponge for Mir-27b Cell Physiol Biochem 2017 43 602 10 10.1159/00048053228934732 Search in Google Scholar

Zhang G, Wu Y, Xu D, Yan X. Long noncoding RNA UFC1 promotes proliferation of chondrocyte in osteoarthritis by acting as a sponge for miR-34a. DNA Cell Biol. 2016; 35:691–5. ZhangG WuY XuD YanX Long noncoding RNA UFC1 promotes proliferation of chondrocyte in osteoarthritis by acting as a sponge for miR-34a DNA Cell Biol 2016 35 691 5 10.1089/dna.2016.339727529373 Search in Google Scholar

Round JL, Lee SM, Li J, Tran G, Jabri B, Chatila TA, Mazmanian SK. The Toll-like receptor 2 pathway establishes colonization by a commensal of the human microbiota. Science. 2011; 332(6032):974–7. RoundJL LeeSM LiJ TranG JabriB ChatilaTA MazmanianSK The Toll-like receptor 2 pathway establishes colonization by a commensal of the human microbiota Science 2011 332 6032 974 7 10.1126/science.1206095316432521512004 Search in Google Scholar

Liu Y-X, Wang G-D, Wang X, Zhang Y-L, Zhang T-L. Effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis: an in vivo and in vitro study. Oncotarget. 2017; 8:38602–17. LiuY-X WangG-D WangX ZhangY-L ZhangT-L Effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis: an in vivo and in vitro study Oncotarget 2017 8 38602 17 10.18632/oncotarget.16199550355728418842 Search in Google Scholar

Parkinson-Lawrence EJ, Shandala T, Prodoehl M, Plew R, Borlace GN, Brooks DA. Lysosomal storage disease: revealing lysosomal function and physiology. Physiology (Bethesda). 2010; 25:102–15. Parkinson-LawrenceEJ ShandalaT ProdoehlM PlewR BorlaceGN BrooksDA Lysosomal storage disease: revealing lysosomal function and physiology Physiology (Bethesda) 2010 25 102 15 10.1152/physiol.00041.200920430954 Search in Google Scholar

Li P, Deng J, Wei X, Jayasuriya CT, Zhou J, Chen Q, et al. Blockade of hypoxia-induced CXCR4 with AMD3100 inhibits production of OA-associated catabolic mediators IL-1b and MMP-13. Mol Med Rep. 2016; 14:1475–82. LiP DengJ WeiX JayasuriyaCT ZhouJ ChenQ Blockade of hypoxia-induced CXCR4 with AMD3100 inhibits production of OA-associated catabolic mediators IL-1b and MMP-13 Mol Med Rep 2016 14 1475 82 10.3892/mmr.2016.5419494008327356492 Search in Google Scholar

Wilkins RJ, Browning JA, Ellory JC. Surviving in a matrix: membrane transport in articular chondrocytes. J Membr Biol. 2000; 177:95–108. WilkinsRJ BrowningJA ElloryJC Surviving in a matrix: membrane transport in articular chondrocytes J Membr Biol 2000 177 95 108 10.1007/s00232000110311003684 Search in Google Scholar

Mow VC, Guo XE. Mechano-electrochemical properties of articular cartilage: their inhomogeneities and anisotropies. Annu Rev Biomed Eng. 2002; 4:175–209. MowVC GuoXE Mechano-electrochemical properties of articular cartilage: their inhomogeneities and anisotropies Annu Rev Biomed Eng 2002 4 175 209 10.1146/annurev.bioeng.4.110701.12030912117756 Search in Google Scholar

Wojdasiewicz P, Poniatowski ŁA, Szukiewicz D. The role of inflammatory and anti-inflammatory cytokines in the pathogenesis of osteoarthritis. Mediators Inflamm. 2014; 2014:561459. doi: 10.1155/2014/561459 WojdasiewiczP PoniatowskiŁA SzukiewiczD The role of inflammatory and anti-inflammatory cytokines in the pathogenesis of osteoarthritis Mediators Inflamm 2014 2014 561459 10.1155/2014/561459 402167824876674 DOI öffnenSearch in Google Scholar

Choy E. Understanding the dynamics: pathways involved in the pathogenesis of rheumatoid arthritis. Rheumatology (Oxford). 2012; 51(Suppl 5):v3–11. ChoyE Understanding the dynamics: pathways involved in the pathogenesis of rheumatoid arthritis Rheumatology (Oxford) 2012 51 Suppl 5 v3 11 10.1093/rheumatology/kes11322718924 Search in Google Scholar

Kobayashi M, Squires GR, Mousa A, Tanzer M, Zukor DJ, Antoniou J, et al. Role of interleukin-1 and tumor necrosis factor α in matrix degradation of human osteoarthritic cartilage. Arthritis Rheum. 2005; 52:128–35. KobayashiM SquiresGR MousaA TanzerM ZukorDJ AntoniouJ Role of interleukin-1 and tumor necrosis factor α in matrix degradation of human osteoarthritic cartilage Arthritis Rheum 2005 52 128 35 10.1002/art.2077615641080 Search in Google Scholar

Séguin CA, Bernier SM. TNFα suppresses link protein and type II collagen expression in chondrocytes: role of MEK1/2 and NF-κB signaling pathways. J Cell Physiol. 2003; 197:356–69. SéguinCA BernierSM TNFα suppresses link protein and type II collagen expression in chondrocytes: role of MEK1/2 and NF-κB signaling pathways J Cell Physiol 2003 197 356 69 10.1002/jcp.1037114566965 Search in Google Scholar

Li M, Guan H. Noncoding RNAs regulating NF-κB signaling. In: Song E, editor. The long and short non-coding RNAs in cancer biology. Singapore: Springer; 2016, p. 317–36. (Cohen IR, Lajtha NSA, Lambris JD, Paoletti R, series editors. Adv Exp Med Biol., vol. 927). LiM GuanH Noncoding RNAs regulating NF-κB signaling In: SongE editor. The long and short non-coding RNAs in cancer biology Singapore Springer 2016 317 36 (Cohen IR, Lajtha NSA, Lambris JD, Paoletti R, series editors. Adv Exp Med Biol., vol. 927). 10.1007/978-981-10-1498-7_1227376741 Search in Google Scholar

Adli M. IKKα and IKKβ each function to regulate NF-κB activation in the TNF-induced/canonical pathway. PLoS One. 2010; 5:e9428. doi: 10.1371/journal.pone.0009428 AdliM IKKα and IKKβ each function to regulate NF-κB activation in the TNF-induced/canonical pathway PLoS One 2010 5 e9428 10.1371/journal.pone.0009428 282847520195534 DOI öffnenSearch in Google Scholar

Shi J, Zhang C, Yi Z, Lan C. Explore the variation of MMP3, JNK, p38 MAPKs, and autophagy at the early stage of osteoarthritis. IUBMB Life. 2016; 68:293–302. ShiJ ZhangC YiZ LanC Explore the variation of MMP3, JNK, p38 MAPKs, and autophagy at the early stage of osteoarthritis IUBMB Life 2016 68 293 302 10.1002/iub.148226873249 Search in Google Scholar

Jilani AA, Mackworth-Young CG. The role of citrullinated protein antibodies in predicting erosive disease in rheumatoid arthritis: a systematic literature review and meta-analysis. Int J Rheumatol. 2015; 2015:728610. doi: 10.1155/2015/728610 JilaniAA Mackworth-YoungCG The role of citrullinated protein antibodies in predicting erosive disease in rheumatoid arthritis: a systematic literature review and meta-analysis Int J Rheumatol 2015 2015 728610 10.1155/2015/728610 436437025821469 DOI öffnenSearch in Google Scholar

Liang Y, Chen S, Yang Y, Lan C, Zhang G, Ji Z, Lin H. Vasoactive intestinal peptide alleviates osteoarthritis effectively via inhibiting NF-κB signaling pathway. J Biomed Sci. 2018; 25:25. doi: 10.1186/s12929-018-0410-z LiangY ChenS YangY LanC ZhangG JiZ LinH Vasoactive intestinal peptide alleviates osteoarthritis effectively via inhibiting NF-κB signaling pathway J Biomed Sci 2018 25 25 10.1186/s12929-018-0410-z 585109829540226 DOI öffnenSearch in Google Scholar

Chang SH, Mori D, Kobayashi H, Mori Y, Nakamoto H, Okada K, et al. Excessive mechanical loading promotes osteoarthritis through the gremlin-1-NF-κB pathway. Nat Commun. 2019; 10:1442. doi: 10.1038/s41467-019-09491-5 ChangSH MoriD KobayashiH MoriY NakamotoH OkadaK Excessive mechanical loading promotes osteoarthritis through the gremlin-1-NF-κB pathway Nat Commun 2019 10 1442 10.1038/s41467-019-09491-5 644102030926814 DOI öffnenSearch in Google Scholar

Mazzetti I, Magagnoli G, Paoletti S, Uguccioni M, Olivotto E, Vitellozzi R, et al. A role for chemokines in the induction of chondrocyte phenotype modulation. Arthritis Rheum. 2004; 50:112–22. MazzettiI MagagnoliG PaolettiS UguccioniM OlivottoE VitellozziR A role for chemokines in the induction of chondrocyte phenotype modulation Arthritis Rheum 2004 50 112 22 10.1002/art.1147414730607 Search in Google Scholar

Mahon OR, Kelly DJ, McCarthy GM, Dunne A. Osteoarthritis-associated basic calcium phosphate crystals alter immune cell metabolism and promote M1 macrophage polarization. Osteoarthritis Cartilage. 2020; 28:603–12. MahonOR KellyDJ McCarthyGM DunneA Osteoarthritis-associated basic calcium phosphate crystals alter immune cell metabolism and promote M1 macrophage polarization Osteoarthritis Cartilage 2020 28 603 12 10.1016/j.joca.2019.10.01031730805 Search in Google Scholar

Grieshaber-Bouyer R, Kämmerer T, Rosshirt N, Nees TA, Koniezke P, Tripel E, et al. Divergent mononuclear cell participation and cytokine release profiles define hip and knee osteoarthritis. J Clin Med. 2019; 8:1631. doi: 10.3390/jcm8101631 Grieshaber-BouyerR KämmererT RosshirtN NeesTA KoniezkeP TripelE Divergent mononuclear cell participation and cytokine release profiles define hip and knee osteoarthritis J Clin Med 2019 8 1631 10.3390/jcm8101631 683273531590365 DOI öffnenSearch in Google Scholar

Kostopoulou F, Malizos KN, Papathanasiou I, Tsezou A. MicroRNA-33a regulates cholesterol synthesis and cholesterol efflux-related genes in osteoarthritic chondrocytes. Arthritis Res Ther. 2015; 17:42. doi: 10.1186/s13075-015-0556-y KostopoulouF MalizosKN PapathanasiouI TsezouA MicroRNA-33a regulates cholesterol synthesis and cholesterol efflux-related genes in osteoarthritic chondrocytes Arthritis Res Ther 2015 17 42 10.1186/s13075-015-0556-y 437584525880168 DOI öffnenSearch in Google Scholar

Tardif G, Hum D, Pelletier JP, Duval N, Martel-Pelletier J. Regulation of the IGFBP-5 and MMP-13 genes by the microRNAs miR-140 and miR-27a in human osteoarthritic chondrocytes. BMC Musculoskelet Disord. 2009; 10:148. doi: 10.1186/1471-2474-10-148 TardifG HumD PelletierJP DuvalN Martel-PelletierJ Regulation of the IGFBP-5 and MMP-13 genes by the microRNAs miR-140 and miR-27a in human osteoarthritic chondrocytes BMC Musculoskelet Disord 2009 10 148 10.1186/1471-2474-10-148 279222019948051 DOI öffnenSearch in Google Scholar

Yatsugi N, Tsukazaki T, Osaki M, Koji T, Yamashita S, Shindo H. Apoptosis of articular chondrocytes in rheumatoid arthritis and osteoarthritis: correlation of apoptosis with degree of cartilage destruction and expression of apoptosis-related proteins of p53 and c-myc. J Orthop Sci. 2000; 5:150–6. YatsugiN TsukazakiT OsakiM KojiT YamashitaS ShindoH Apoptosis of articular chondrocytes in rheumatoid arthritis and osteoarthritis: correlation of apoptosis with degree of cartilage destruction and expression of apoptosis-related proteins of p53 and c-myc J Orthop Sci 2000 5 150 6 10.1007/s00776005014210982649 Search in Google Scholar

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