Screening crucial lncRNAs and genes in osteoarthritis by integrated analysis
Advances in Rheumatology volume 63, Article number: 7 (2023)
Osteoarthritis (OA) is one of the most frequent chronic diseases with high morbidity worldwide, marked by degradation of the cartilage and bone, joint instability, stiffness, joint space stenosis and subchondral sclerosis. Due to the elusive mechanism of osteoarthritis (OA), we aimed to identify potential markers for OA and explore the molecular mechanisms underlying OA.
Expression profiles data of OA were collected from the Gene Expression Omnibus database to identify differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) in OA. Functional annotation and protein–protein interaction (PPI) networks were performed. Then, nearby DEmRNAs of DElncRNAs was obtained. Moreover, GO and KEGG pathway enrichment analysis of nearby DEmRNAs of DElncRNAs was performed. Finally, expression validation of selected mRNAs and lncRNAs was performed by quantitative reverse transcriptase-polymerase chain reaction.
In total, 2080 DEmRNAs and 664 DElncRNAs were determined in OA. PI3K-Akt signaling pathway, Endocytosis and Rap1 signaling pathway were significantly enriched KEGG pathways in OA. YWHAB, HSPA8, NEDD4L and SH3KBP1 were four hub proteins in PPI network. The AC093484.4/TRPV2 interact pair may be involved in the occurrence and development of OA.
Our study identified several DEmRNAs and DElncRNAs associated with OA. The molecular characters could provide more information for further study on OA.
Osteoarthritis (OA) is one of the most frequent chronic diseases with high morbidity worldwide, marked by degradation of the cartilage and bone, joint instability, stiffness, joint space stenosis and subchondral sclerosis . Patients with OA would suffer some symptoms, such as stiffness, pain, swelling, and loss of mobility with occasional variable degrees of local inflammation, which would severely reduce the quality of life and create a heavy socioeconomic burden . However, the pathogenesis of OA is not completely understood. Therefore, it is essential to gain novel insights into biological mechanisms of OA and explore potential biomarkers for OA.
With advancement of next-generation sequencing technology, numerous research has increasingly recognized the important role of lncRNAs in the occurrence and development of OA . LncRNAs are RNA molecules > 200 bp in length and participate in numerous biological processes, such as the proliferation, apoptosis, cell cycle, and chromatin remodeling . DILC is reduced in OA and over expression of DILC inhibits the expression of IL-6 in chondrocytes . Knockdown of MFI2-AS1 is found to increase cell viability but suppress apoptosis and inflammatory response to inhibit lipopolysaccharide-induced OA progression . MALAT1 is reported to participate in cell proliferation, apoptosis, and ECM degradation of OA . TUG1 performed as a ceRNA through sponging miR-195 to increase MMP-13 expression to regulate ECM degradation in OA . However, the results are not consistent and reliable due to the difference of samples and sequencing platform, which means we need more comprehensive approaches to identify the hub biomarkers.
Therefore, in this study, we analyzed the expression profiles of OA in the Gene Expression Omnibus database (GEO) database by bioinformatics tools to obtain differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs). This study aims to better understand the potential mechanisms in the occurrence and development of OA and may accelerate the improvement of the treatment level of OA.
Materials and methods
The mRNA/lncRNA expression profiles of OA were downloaded from GEO database. Three mRNA datasets, GSE113825, GSE117999 and GSE114007, and one lncRNA dataset, GSE113825, were included in this study (Additional file 1: Table S1).
Identification of DEmRNAs/DElncRNAs and functional analysis
With limma package and metaMA package, DEmRNAs and DElncRNAs in OA were obtained. The threshold for the significance was the false discovery rate (FDR) < 0.05. Metascape was employed to perform GO and KEGG pathway enrichment analysis to identify aberrantly regulated biological processes and signaling pathways in OA (p-value < 0.05).
Protein–protein interaction (PPI) network construction
In order to predict the function and explore the mechanism of mRNAs, top 200 up- and down-regulated DEmRNAs were searched with the BioGrid, and PPI network was constructed with Cytoscape software.
Identification of the nearby DEmRNAs of DElncRNAs
To explore the cis-regulated mechanism of lncRNAs, the nearby DEmRNAs were identified within a 100 kb window up- or down-stream of DElncRNAs in OA. GO and KEGG pathway enrichment analysis of nearby mRNAs of DElncRNAs was performed by Metascape (p-value < 0.05).
Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) validation
Eight blood samples were obtained from 4 patients with OA and 4 normal controls. Samples were collected after obtaining written informed consent from every participant. This study was approved by the ethical committee of Honghui Hospital, Xi'an Jiaotong University Health Science Center (202,112,002) and performed in accordance with the Declaration of Helsinki. Total RNA was isolated with the Trizol reagent (Invitrogen, USA) following manufacturer’s protocol. The qRT-PCR reactions were performed in ABI 7300 Real-time PCR Detection System with SuperReal PreMix Plus. GAPDH and ACTB were used as endogenous controls.
Expression validation in the GEO dataset and receiver operating characteristic (ROC) analysis
GSE82107 (involving synovial tissues), GSE55235 (involving synovial tissues), GSE63359 (involving peripheral blood leukocytes), GSE48556 (involving peripheral blood mononuclear cell) and GSE175960 (involving cartilage tissues) datasets were downloaded from the GEO database, which consisted of 175 patients with OA and 79 normal controls. The expression pattern of DEmRNAs and DElncRNAs was validated with these five datasets. Then, by using pROC package in R language, we performed the ROC analysis to assess the diagnostic value of DEmRNAs and DElncRNAs. The area under the curve (AUC) was further calculated.
DEmRNAs and DElncRNAs in OA
After processing the raw data, 2080 (1146 up- and 934 down-regulated) DEmRNAs and 664 (522 up- and 142 down-regulated) DElncRNAs were acquired in OA. The top 10 up- and down-regulated DEmRNAs and DElncRNAs are displayed in Table 1. Hierarchical clustering analysis of DEmRNAs and DElncRNAs is exhibited in Fig. 1A and B, respectively.
Functional analysis of DEmRNAs
GO analysis indicated that axon development (p-value = 1.00E-12), neuron projection morphogenesis (p-value = 1.00E-10) and plasma membrane bounded cell projection morphogenesis (p-value = 1.00E-10) were significantly enriched GO terms (Fig. 2A). KEGG pathway enrichment analysis showed that PI3K-Akt signaling pathway (p-value = 2.00E-06), endocytosis (p-value = 1.00E-05) and Rap1 signaling pathway (p-value = 5.01E-05) were several significantly enriched pathways (Fig. 2B).
PPI network of DEmRNAs
The PPI network of DEmRNAs contained 135 nodes and 135 edges (Fig. 3). MRNAs with higher degree were as follows: YWHAB (degree = 11), HSPA8 (degree = 8), NEDD4L (degree = 7) and SH3KBP1 (degree = 7).
Identification of the nearby DEmRNAs of DElncRNAs
A total of 46 DElncRNA-nearby DEmRNA pairs, involving 38 DElncRNAs and 45 DEmRNAs, were obtained in OA (Table 2). GO analysis indicated that these DEmRNAs were significantly enriched in protein-DNA complex assembly (p-value = 1.26E-03), protein-DNA complex subunit organization (p-value = 2.00E-03) and head development (p-value = 3.16E-03) (Additional file 2: Fig. S1). In KEGG analysis of nearby DEmRNAs of DElncRNAs, only 3 mRNAs were significantly enriched in the cAMP signaling pathway.
Seven DEmRNAs (TSPAN11, SULF1, YWHAB, AURKA, SH3KBP1, TRPV2 and ACP5) and two lncRNAs (CRNDE and LINC00152) were selected for qRT-PCR analysis. Based on our integrated analysis, TSPAN11, SULF1, YWHAB, AURKA, SH3KBP1, TRPV2, ACP5 and LINC00152 were up-regulated while CRNDE was down-regulated in OA. Except for CRNDE, the qRT-PCR results were basically in line with our integrated analysis results (Fig. 4).
Expression validation in the GEO dataset and ROC analysis
As shown in Fig. 5, the expression patterns of AURKA, PIK3IP1, SULF1 and TRPV2 in GSE48556, AURKA, B3GALT4, LIMK2, PIK3IP1, SULF1 and TRPV2 in GSE55235, AURKA, B3GALT4, LIMK2, PIK3IP1, SULF1 and TRPV2 in GSE63359, B3GALT4, LIMK2, SULF1, TRPV2, TSPAN11 and CRNDE in GSE82107, B3GALT4, LIMK2, SULF1, TSPAN11, CRNDE and LINC00152 in GSE175960 were displayed, which were consistent with our integrated analysis. We performed ROC curve analyses and calculated the AUC to assess the diagnostic value of these DEmRNAs and DElncRNAs. The results indicated that the AUC of SULF1 (1.000) and TRPV2 (0.900) in GSE55235, and LIMK2 (0.700), SULF1 (0.871) and TSPAN11 (0.829) in GSE82107, was more than 0.70, which indicated that these genes had a potential diagnostic value (Fig. 6).
OA is a destructive joint disease, and increases in prevalence with age, marked by disordered cartilage homeostasis with subsequent inflammation and degradation, and seriously threatens human health . Therefore, more attention has been paid on exploring potential pathogenesis mechanisms of OA to facilitate diagnosis and prognosis.
TSPAN11 (CD 151-like) is a member of the tetraspanins family that has been linked to OA. Elevated TSPAN11 is detected in articular cartilage collected from knees undergoing total knee arthroplasty due to end-stage OA . It has been suggested that the integrin clustering mediated by TSPAN11 determines the alignment of bone matrix architecture orthogonal to cell alignment . Human endo-O-sulfatases, including Sulf-1 and Sulf-2, regulate a multitude of cell-signaling events through heparan sulfate protein interactions and have been linked with the occurrence of OA . SULF1 is a regulator of numerous growth factors in skeletal embryonic development . Increased mRNA and protein levels of SULF1 in the cartilage of the elderly patients with OA may alter the sulfation patterns of heparan sulfate proteoglycans and growth factor activities, leading to abnormal chondrocyte activation and cartilage degradation in OA . Jiang et al. indicated that SULF1 was associated with bone loss and the pathology of osteoporosis and OA in aging . The increased expression of Sulf1 in differentiating osteoblasts was further confirmed by RT-PCR analysis of mRNA levels in rat calvarial osteoblast cultures . In this study, both TSPAN11 and SULF1 were significantly high expressed, which was in accordance with previous observations, indicating the importance of TSPAN11 and SULF1 in OA.
As a type of Aurora kinase, Aurora kinase A (AURKA) is crucial for the successful execution of mitosis . Highly expressed AURKA is detected in human osteoarthritic chondrocytes and knocking-down AURKA significantly reduced the OARSI score . AURKA ubiquitination affects mitochondrial dysfunction and inhibits the occurrence of OA by degradation of SOD2 . AURKA is identified as a hub gene in osteoarthritic degenerative meniscal lesions based on GSE52042 dataset . Similarly, we found that AURKA was identified not only as a significantly up-regulated DEmRNA, but also as a hub gene in this study, which added to evidence that AURKA is crucial for the development of OA.
CRNDE is closely associated with the proliferation of osteoclasts . CRNDE regulates bone marrow mesenchymal stem cells chondrogenic differentiation to promote cartilage repair in OA . CRNDE is a regulator of bone metabolism, and deletion of CRNDE in mice develops a low bone mass phenotype due to impaired bone formation . Overexpression of CRNDE alleviated cartilage damage and synovitis in OA rats . Wang et al. demonstrated that LINC00152 induced proliferation and suppressed apoptosis in rheumatoid arthritis fibroblast-like synoviocytes . Similarly, Zhang et al. suggested that LINC00152 was inflammation-related lncRNA and might be involved in the regulation of rheumatoid arthritis fibroblast-like synoviocytes inflammation . In addition, Hu et al. identified that CRNDE and LINC00152 were involved in age-related degeneration of articular cartilage . In agreement with previous studies, we also observed significantly down-regulated CRNDE and LINC00152 in this study.
LIM kinases (LIMKs), comprising LIMK1 and LIMK2, are common downstream effectors of several signalization pathways, and function as a signalling node that controls cytoskeleton dynamics through the phosphorylation of the cofilin family proteins . Li et al. suggested that LIMK2 is required for membrane cytoskeleton reorganization of contracting airway smooth muscle . LIMK2 plays an important role in the reorganization of actin cytoskeleton induced by fluid shear stress in murine osteoblast lines . LIMK2 silencing inhibits the fluid shear stress-induced reorganisation of the actin cytoskeleton of primary osteoblasts and demonstrates that the mechanosensitivity of osteoblasts in response to this stress is enhanced . PIK3IP1 is reported as a negative regulator of the PI3K pathway . PIK3IP1 has also been considered as a negative regulator of antitumor T cell response . PIK3IP1 is an important modulator for the tumor necrosis factor-driven inflammatory response in fibroblast-like synoviocytes . In addition, down-regulated PIK3IP1 is detected in rheumatoid arthritis . Both LIMK2 and PIK3IP1 interacted with LINC00152, which indicated that the LINC00152/LIMK2 and LINC00152/PIK3IP1 interacted pairs may exert a critical function in OA.
TRPV2 encodes an ion channel which is a Ca2+ permeable channel and performs a function in mediating intracellular Ca2+ current via mechanical stimuli . Bai et al. reported that TRPV2 modulated RANKL-dependent osteoclastic differentiation in multiple myeloma cells . Laragione et al. indicated that TRPV2 inhibited cell invasion, inflammatory cell infiltration, and angiogenesis, and reduced the severity of arthritis . TRPV2 is required for homeostasis of articular joints by induction of Prg4 and suppression of ectopic endochondral ossification in these joints . In the present study, significantly up-regulated TRPV2 was detected in OA, which may suggest that TRPV2 is of great importance in OA. In addition, AC093484.4, as the most significant DElncRNA, interacted with TRPV2. Hence, more evidence should be obtained to determine the function of AC093484.4/TRPV2 interact pair on OA.
The β-1,3-galactosyltransferase-4 (B3GALT4) gene belongs to the β-1,3-galactosyltransferase (β3GalT) gene family, which is essential in the O-glycosylation process . B3GALT4 has been linked to multiple tumors. For example, B3GALT4 is suggested to serve as a novel biomarker for the diagnosis of gynecological cancers . Zhang et al. revealed that B3GALT4 was a novel prognostic biomarker for colorectal cancer . Zhang et al. reported that higher expression levels of B3GALT4 predicted better overall survival rates, which might be potential predictors of recurrent osteosarcoma prognosis . In addition, Verma et al. indicated that decreased B3GALT4 could increase cell vulnerability to potentially toxic stressors, which may contribute to dopaminergic neurodegeneration in Parkinson's disease . Shi et al. indicated that HCG25 was significantly up-regulated in hepatocellular carcinoma and had great diagnostic value for hepatocellular carcinoma . To date, there is no study report on the association between OA and HCG25/B3GALT4. In this study, B3GALT4 was interacted with HCG25, which remind us to focus on the function of HCG25/B3GALT4 interact pair on OA.
Our study also has certain limitations. First, the data for this study was obtained from public databases with a small sample size. However, the external validation database confirmed the reliability of our analysis. Second, the sample size used for QRT-PCR validation was small. Third, molecular experiments as well as larger clinical samples are required to further validate the results.
In conclusion, we identified several DEmRNAs and DElncRNAs associated with OA. This study thus provides further insights into the underlying molecular mechanism of OA, which may facilitate the diagnosis and treatment of OA.
Availability of data and materials
All data generated or analysed during this study are included in this published article.
Gene expression omnibus database
Differentially expressed mRNAs
Differentially expressed lncRNAs
Quantitative reverse transcriptase-polymerase chain reaction
Receiver operating characteristic
Area under the curve
Aurora kinase A
False discovery rate
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Wang, J., Zhang, Y., Ma, T. et al. Screening crucial lncRNAs and genes in osteoarthritis by integrated analysis. Adv Rheumatol 63, 7 (2023). https://doi.org/10.1186/s42358-023-00288-1