Integration of transcriptome-wide association study and messenger RNA expression profile to identify genes associated with osteoarthritis

Identification and Validation of Pivotal Genes in Osteoarthritis Combined with WGCNA Analysis

Introduction

The prevalence of osteoarthritis (OA), the most common chronic joint condition, is increasing due to the aging population and escalating obesity rates, leading to a significant impact on human health and well-being. Thus, analyzing the key targets of OA through bioinformatics can help discover new biomarkers to improve its diagnosis.

Methods

The microarray and RNA-seq results were screened from the Gene Expression Omnibus (GEO) database. Functional enrichment analyses, protein-protein interaction (PPI) analysis, and weighted gene co-expression network analysis (WGCNA) of the DEGs were performed. RT-qPCR and WB were further performed to verify the hub gene expression in OA rat.

Results

In this study, 35 key genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) using the GSE169077 and GSE114007 datasets. Enrichment analysis revealed that these key genes were predominantly enriched in the HIF-1 signaling pathway, ECM-receptor interaction, and FoxO signaling pathway. Through the integration of protein-protein interaction (PPI) analysis, validation in animal models and ROC curve analysis, four pivotal genes (GADD45B, CLDN5, HILPDA and CDKN1B) were finally identified.

Conclusion

In conclusion, these identified key genes could serve as novel targets for predicting and treating OA, offering fresh insights into its etiology and pathogenesis.

Integrative bioinformatics approach identifies novel drug targets for hyperaldosteronism, with a focus on SHMT1 as a promising therapeutic candidate

Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches. We employed a systematic approach combining: gene identification through transcriptome-wide association studies (TWAS); causal inference using summary data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) analyses; additional analyses included phenome-wide association analysis, enrichment analysis, protein-protein interaction (PPI) networks, drug repurposing, molecular docking and clinical validation through aldosterone-producing adenomas (APAs) tissue. Through systematic screening and prioritization, we identified 163 PA-associated genes, of which seven emerged as potential drug targets: CEP104, HIP1, TONSL, ZNF100, SHMT1, and two long non-coding RNAs (AC006369.2 and MRPL23-AS1). SHMT1 was identified as the most promising target, showing significantly elevated expression in APAs compared to adjacent non-tumorous tissues. Drug repurposing analysis identified four potential SHMT1-targeting compounds (Mimosine, Pemetrexed, Leucovorin, and Irinotecan), supported by molecular docking studies. The integration of multiple bioinformatics methods and experimental validation successfully identified novel drug targets for hyperaldosteronism. SHMT1, in particular, represents a promising candidate for future therapeutic development. These findings provide new opportunities for developing causative treatments for PA, though further clinical validation is warranted.

Advances in understanding effects of miRNAs on apoptosis, autophagy, and pyroptosis in knee osteoarthritis

MicroRNAs (miRNAs) are a class of endogenous small non-coding RNAs. MicroRNAs-mediated signaling pathways play a critical regulatory role in inducing apoptosis, autophagy, and pyroptosis in developing knee osteoarthritis (KOA). Given this, we searched databases, such as PubMed, using keywords including "miRNA," "knee osteoarthritis," "apoptosis," "autophagy," "pyroptosis", and their combinations. Through an extensive literature review, we conclude that miRNAs can be modulated through various signaling pathways, such as Wnt/β-catenin, TGF-β, PI3K/AKT/mTOR, and NLRP3/Caspase-1, to regulate apoptosis, autophagy, and pyroptosis in KOA. Furthermore, we note that P2X7R and HMGB1 may be crucial regulatory molecules involved in the interconnected regulation of apoptosis, autophagy, and pyroptosis in KOA. Additionally, we describe that miR-140-5p and miR-107 can modulate the advancement of KOA chondrocytes by targeting distinct molecules involved in apoptosis, autophagy, and pyroptosis, respectively. Therefore, we conclude that miRNAs may be potential biomarkers and therapeutic targets for the early prediction, diagnosis, and effective therapeutic approaches of KOA.

Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis

BACKGROUND

Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and environmental factors. We conducted a transcriptome-wide association study (TWAS) and chemical-related gene set enrichment analysis (CGSEA) to investigate the susceptibility genes and environmental factors.

METHODS

TWAS analysis was conducted to identify the susceptibility genes by integrating the summary-level genome-wide association study data of knee OA (KOA) and hip OA (HOA) with the precomputed expression weights from the Genotype-Tissue Expression Project (Version 8). The FUSION software was used for both single-tissue and cross-tissue TWAS, which were combined using an aggregate Cauchy association test. The biological function and pathways of the TWAS genes were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, and the human cartilage mRNA expression profiles were utilized to validate the TWAS genes. CGSEA analysis was performed to scan the OA-associated chemicals by integrating the TWAS results with the chemical-related gene sets.

RESULTS

There were 44 and 93 unique TWAS genes identified in 7 and 11 chromosomes for KOA and HOA, respectively, fourteen and four of which showed significantly differential expression in the mRNA profiles, such as CRHR1, LTBP1, WWP2, LMX1B, and PTHLH. OA-related pathways were found in the KEGG and GO analysis, such as TGF-beta signaling pathway, MAPK signaling pathway, hyaluronan metabolic process, and chondrocyte differentiation. Forty-five OA-associated chemicals were identified, including quercetin, bisphenol A, and cadmium chloride.

CONCLUSIONS

Several candidate OA-associated genes and chemicals were identified through TWAS and CGSEA analysis, which expanded our understanding of the relationship between genes, chemicals, and their impact on OA.

Transcriptome-wide association study reveals candidate causal genes for lumbar spinal stenosis

Aims

Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early diagnosis and treatment of the disease.

Methods

We conducted a transcriptome-wide association study (TWAS) of spinal canal stenosis by integrating genome-wide association study summary statistics (including 661 cases and 178,065 controls) derived from Biobank Japan, and pre-computed gene expression weights of skeletal muscle and whole blood implemented in FUSION software. To verify the TWAS results, the candidate genes were furthered compared with messenger RNA (mRNA) expression profiles of LSS to screen for common genes. Finally, Metascape software was used to perform enrichment analysis of the candidate genes and common genes.

Results

TWAS identified 295 genes with permutation p-values < 0.05 for skeletal muscle and 79 genes associated for the whole blood, such as RCHY1 (P_TWAS = 0.001). Those genes were enriched in 112 gene ontology (GO) terms and five Kyoto Encyclopedia of Genes and Genomes pathways, such as 'chemical carcinogenesis - reactive oxygen species' (LogP value = -2.139). Further comparing the TWAS significant genes with the differentially expressed genes identified by mRNA expression profiles of LSS found 18 overlapped genes, such as interleukin 15 receptor subunit alpha (IL15RA) (P_TWAS = 0.040, P_mRNA = 0.010). Moreover, 71 common GO terms were detected for the enrichment results of TWAS and mRNA expression profiles, such as negative regulation of cell differentiation (LogP value = -2.811).

Conclusion

This study revealed the genetic mechanism behind the pathological changes in LSS, and may provide novel insights for the early diagnosis and intervention of LSS.

Identifying Candidate Genes Associated with Sporadic Amyotrophic Lateral Sclerosis via Integrative Analysis of Transcriptome-Wide Association Study and Messenger RNA Expression Profile

Amyotrophic lateral sclerosis, a fatal neurodegeneration disease affecting motor neurons in the brain and spinal cord, is difficult to diagnose and treat. The objective of this study is to identify novel candidate genes related to ALS. Transcriptome-wide association study of ALS was conducted by integrating the genome-wide association study summary data (including 1234 ALS patients and 2850 controls) and pre-computed gene expression weights of different tissues. The ALS-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the mRNA expression profiles of the sporadic ALS. Functional enrichment and annotation analysis of identified genes were performed by an R package and the functional mapping and annotation software. TWAS identified 761 significant genes (P_TWAS < 0.05), 627 Gene ontology terms, and 8 Kyoto Encyclopedia of Genes and Genomes pathways for ALS, such as C9orf72, with three expression quantitative trait loci were found significantly: rs2453554 (P_{TWAS CBRS} = 4.68 × 10^-10, P_{TWAS CBRS} = 2.54 × 10^-9), rs10967976 (P_{TWAS CBRS} = 7.85 × 10^-10, P_{TWAS CBRS} = 8.91 × 10^-9, P_{TWAS CBRS} = 1.49 × 10^-7, P_{TWAS CBRS} = 5.59 × 10^-7), rs3849946 (P_{TWAS CBRS} = 7.69 × 10^-4, P_{TWAS YBL} = 4.02 × 10^-2), Mitochondrion (P_adj = 4.22 × 10^-16), and Cell cycle (P_adj = 2.04 × 10^-3). Moreover, 107 common genes, 4 KEGG pathways and 41 GO terms were detected by integrating mRNA expression profiles of sALS, such as CPVL (FC = 2.06, P_mRNA = 6.99 × 10^-6, P_{TWAS CBR} = 2.88 × 10^-2, P_{TWAS CBR} = 4.37 × 10^-2), Pyrimidine Metabolism (P_adj = 2.43 × 10^-2), and Cell Activation (P_adj = 5.54 × 10^-3). Multiple candidate genes and pathways were detected for ALS. Our findings may provide novel clues for understanding the genetic mechanism of ALS.

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

We have screened candidate marker genes for the diagnosis of osteoarthritis and predicted their regulatory mechanisms. Six expression chips of tissue samples and one expression chip of peripheral blood mononuclear cell (PMBC) samples were obtained from the GEO database. Differential analysis, GSEA, and WGCNA were performed on the integra-ted tissue sample data with batch correction. Can-didate genes were obtained from the intersection of the genes significantly related to osteoarthritis in the WGCNA and the differentially expressed genes. ROC analysis was performed on the candidate genes in the tissue and PMBC samples. Genes with AUC values greater than 0.6 were retained as final candidates, and their upstream regulatory miRNAs were predicted. A total of 106 genes with differential expression were found in osteoarthritis tissue samples, which were mainly enriched in cell cycle and p53 signalling pathways. WGCNA selected a gene module significantly correlated with the occurrence of osteoarthritis. Fourteen candidate genes were obtained from the intersection of the genes in the module and the differentially expressed genes. ROC analysis showed that among these 14 candidate genes, only ADM, CX3CR1 and GADD45A had AUC values greater than 0.6 in both tissue and PMBC samples. The AUC values of the gene set of these three genes were greater than 0.7. Multiple miRNAs were predicted to be regulators of these three genes. ADM, CX3CR1 and GADD45A have potential as diagnostic marker genes for osteoarthritis and may be regulated by multiple miRNAs.

Muscle transcriptomic circuits linked to periarticular physiology in end-stage osteoarthritis

The ability of individuals with end-stage osteoarthritis (OA) to functionally recover from total joint arthroplasty is highly inconsistent. The molecular mechanisms driving this heterogeneity have yet to be elucidated. Furthermore, OA disproportionately impacts females, suggesting a need for identifying female-specific therapeutic targets. We profiled the skeletal muscle transcriptome in females with end-stage OA (n = 20) undergoing total knee or hip arthroplasty using RNA-Seq. Single-gene differential expression (DE) analyses tested for DE genes between skeletal muscle overlaying the surgical (SX) joint and muscle from the contralateral (CTRL) leg. Network analyses were performed using Pathway-Level Information ExtractoR (PLIER) to summarize genes into latent variables (LVs), i.e., gene circuits, and link them to biological pathways. LV differences in SX versus CTRL muscle and across sources of muscle tissue (vastus medialis, vastus lateralis, or tensor fascia latae) were determined with ANOVA. Linear models tested for associations between LVs and muscle phenotype on the SX side (inflammation, function, and integrity). DE analysis revealed 360 DE genes (|Log2 fold-difference| ≥ 1, FDR ≤ 0.05) between the SX and CTRL limbs, many associated with inflammation and lipid metabolism. PLIER analyses revealed circuits associated with protein degradation and fibro-adipogenic cell gene expression. Muscle inflammation and function were linked to an LV associated with endothelial cell gene expression highlighting a potential regulatory role of endothelial cells within skeletal muscle. These findings may provide insight into potential therapeutic targets to improve OA rehabilitation before and/or following total joint replacement.

A transcriptome-wide association study provides new insights into the etiology of osteoarthritis

Background

Osteoarthritis (OA) is a common clinical disease caused by a variety of factors, including genetic variants. Although genome-wide association studies (GWAS) have been performed to elucidate the genetic basis of OA, some loci of risk located in noncoding regions of the genome have been neglected. Therefore, we integrated multiple data types to detect the genetic component of gene expression in OA patients through transcriptome-wide association studies (TWAS) and summary-data-based Mendelian randomization (SMR) analysis.

Methods

TWAS was performed by integrating the larger GWAS summary-data for OA (n=30,727 cases, n=297,191 controls) and 2 expression weight sets (muscle-skeletal tissue and whole blood). Colocalization analysis, conditional analysis, and fine-mapping analysis were also conducted. A broad description of the identified associations was obtained. In addition, a causal relationship between certain risk genes and OA was identified with SMR.

Results

New significant genome-wide associations were found, including on chromosome 1q36.12 (rs1555024, P=4.24E-07) near the ASAP3 and TCEA3 genes, on chromosome 17q24.2 (rs2521348, P=1.01E-06) near the ABCA9 gene, on chromosome 20q11.22 (rs224331, P=8.17E-09) near the UQCC1 and MYH7B genes, and on chromosome 21q21.3 (rs2832155, P=5.39E-08) near the RWDD2B gene. In addition, SMR results exhibited that upregulated UQCC1 and downregulated ASAP3 were associated with OA development and both had a significant causal relationship with OA.

Conclusions

We revealed some novel OA-associated genes and risk loci by integrating multiple data types and analysis methods, thus providing new clues for the study of genetic mechanisms of OA.

Exosomes from dysfunctional chondrocytes affect osteoarthritis in Sprague-Dawley rats through FTO-dependent regulation of PIK3R5 mRNA stability

Aims

Exosomes (exo) are involved in the progression of osteoarthritis (OA). This study aimed to investigate the function of dysfunctional chondrocyte-derived exo (DC-exo) on OA in rats and rat macrophages.

Methods

Rat-derived chondrocytes were isolated, and DCs induced with interleukin (IL)-1β were used for exo isolation. Rats with OA (n = 36) or macrophages were treated with DC-exo or phosphate-buffered saline (PBS). Macrophage polarization and autophagy, and degradation and chondrocyte activity of cartilage tissues, were examined. RNA sequencing was used to detect genes differentially expressed in DC-exo, followed by RNA pull-down and ribonucleoprotein immunoprecipitation (RIP). Long non-coding RNA osteoarthritis non-coding transcript (OANCT) and phosphoinositide-3-kinase regulatory subunit 5 (PIK3R5) were depleted in DC-exo-treated macrophages and OA rats, in order to observe macrophage polarization and cartilage degradation. The PI3K/AKT/mammalian target of rapamycin (mTOR) pathway activity in cells and tissues was measured using western blot.

Results

DC-exo inhibited macrophage autophagy (p = 0.002) and promoted M1 macrophage polarization (p = 0.002). DC-exo at 20 μg/ml induced collagen degradation (p < 0.001) and inflammatory cell infiltration (p = 0.023) in rats. OANCT was elevated in DC (p < 0.001) and in cartilage tissues of OA patients (p < 0.001), and positively correlated with patients’ Kellgren-Lawrence grade (p < 0.001). PIK3R5 was increased in DC-exo-treated cartilage tissues (p < 0.001), and OANCT bound to fat mass and obesity-associated protein (FTO) (p < 0.001). FTO bound to PIK3R5 (p < 0.001) to inhibit the stability of PIK3R5 messenger RNA (mRNA) (p < 0.001) and disrupt the PI3K/AKT/mTOR pathway (p < 0.001).

Conclusion

Exosomal OANCT from DC could bind to FTO protein, thereby maintaining the mRNA stability of PIK3R5, further activating the PI3K/AKT/mTOR pathway to exacerbate OA.

Cite this article: Bone Joint Res 2022;11(9):652–668.

A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Juvenile Idiopathic Arthritis in Asia and Europe

Background

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.

Methods

A cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.

Results

The TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (P_TWAS = 4.21E-03, P_DEG = 1.50E-04) and FRAT2 (P_TWAS = 2.82E-02, P_DEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.

Conclusion

By conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

Identification of mechanics-responsive osteocyte signature in osteoarthritis subchondral bone

Aims

Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA.

Methods

Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.

Results

A group of 77 persistent genes that are highly relevant to extracellular matrix (ECM) biology and bone remodelling signalling were identified in OA subchondral lesions. A loading responsive gene set, including 446 principal genes, was highly enriched in OA medial tibial plateaus compared to lateral tibial plateaus. Of this gene set, a total of 223 genes were identified as the main contributors that were strongly associated with osteocyte functions and signalling pathways, such as ECM modelling, axon guidance, Hippo, Wnt, and transforming growth factor beta (TGF-β) signalling pathways. We limited the loading-responsive genes obtained via the osteocyte transcriptome signature to identify a subgroup of genes that are highly relevant to osteocytes, as the mechanics-responsive osteocyte signature in OA. Based on WGCNA, we found that this signature was highly co-expressed and identified three clusters, including early, late, and persistently responsive genes.

Conclusion

In this study, we identified the mechanics-responsive osteocyte signature in OA-lesioned subchondral bone.

Cite this article: Bone Joint Res 2022;11(6):362–370.

Effect of a single intra-articular administration of stanozolol in a naturally occurring canine osteoarthritis model: a randomised trial

Osteoarthritis (OA) is a disease with a high negative impact on patient's quality of life and a high financial burden. It is a source of chronic pain and affects all mammals, including humans and dogs. As the dog is a common model for translation research of human OA, and exploring spontaneous dog OA can improve the health and well-being of both humans and dogs. To describe the effect of the intra-articular administration of stanozolol in a naturally occurring canine OA model, forty canine (N = 40) hip joints were randomly assigned to receive stanozolol or saline (control). On treatment day and at 8, 15, 30, 90, and 180 days post-treatment, several evaluations were conducted: weight distribution, joint range of motion, thigh girth, digital thermography, and radiographic signs. Also, synovial fluid C-reactive protein and interleukin-1 levels were evaluated. Results from four Clinical Metrology Instruments was also gathered. Results were compared with Repeated Measures ANOVA, with a Huynh-Feldt correction, paired-samples t-test, or Wilcoxon signed-rank test, with p < 0.05. OA was graded as mild (90%), moderate (5%), and severe (5%), including both sexes. They had a mean age of 6.5 ± 2.4 years and a bodyweight of 26.7 ± 5.2 kg. No differences were found between groups at treatment day in all considered evaluations. Weight distribution showed significant improvements with stanozolol from 15 days (p < 0.05) up to 180 days (p < 0.01). Lower values during thermographic evaluation in both views taken and improved joint extension at 90 (p = 0.02) and 180 days (p < 0.01) were observed. Pain and function scores improved up to 180 days. In the control group, radiographic signs progressed, in contrast with stanozolol. The use of stanozolol was safe and produced significant improvements in weight-bearing, pain score, and clinical evaluations in a naturally occurring canine OA model.

Shared genetic liability between major depressive disorder and osteoarthritis

Aims

Deciphering the genetic relationships between major depressive disorder (MDD) and osteoarthritis (OA) may facilitate an understanding of their biological mechanisms, as well as inform more effective treatment regimens. We aim to investigate the mechanisms underlying relationships between MDD and OA in the context of common genetic variations.

Methods

Linkage disequilibrium score regression was used to test the genetic correlation between MDD and OA. Polygenic analysis was performed to estimate shared genetic variations between the two diseases. Two-sample bidirectional Mendelian randomization analysis was used to investigate causal relationships between MDD and OA. Genomic loci shared between MDD and OA were identified using cross-trait meta-analysis. Fine-mapping of transcriptome-wide associations was used to prioritize putatively causal genes for the two diseases.

Results

MDD has a significant genetic correlation with OA (r_g = 0.29) and the two diseases share a considerable proportion of causal variants. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on OA (b_xy = 0.24) and genetic liability to OA conferred a causal effect on MDD (b_xy = 0.20). Cross-trait meta-analyses identified 29 shared genomic loci between MDD and OA. Together with fine-mapping of transcriptome-wide association signals, our results suggest that Estrogen Receptor 1 (ESR1), SRY-Box Transcription Factor 5 (SOX5), and Glutathione Peroxidase 1 (GPX1) may have therapeutic implications for both MDD and OA.

Conclusion

The study reveals substantial shared genetic liability between MDD and OA, which may confer risk for one another. Our findings provide a novel insight into phenotypic relationships between MDD and OA.

Cite this article: Bone Joint Res 2022;11(1):12–22.

Identification and development of a novel 5-gene diagnostic model based on immune infiltration analysis of osteoarthritis

Background

Osteoarthritis (OA), which is due to the progressive loss and degeneration of articular cartilage, is the leading cause of disability worldwide. Therefore, it is of great significance to explore OA biomarkers for the prevention, diagnosis, and treatment of OA.

Methods and materials

The GSE129147, GSE57218, GSE51588, GSE117999, and GSE98918 datasets with normal and OA samples were downloaded from the Gene Expression Omnibus (GEO) database. The GSE117999 and GSE98918 datasets were integrated, and immune infiltration was evaluated. The differentially expressed genes (DEGs) were analyzed using the limma package in R, and weighted gene co-expression network analysis (WGCNA) was used to explore the co-expression genes and co-expression modules. The co-expression module genes were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and hub genes were identified by the degree, MNC, closeness, and MCC algorithms. The hub genes were used to construct a diagnostic model based on support vector machines.

Results

The Immune Score in the OA samples was significantly higher than in the normal samples, and a total of 2313 DEGs were identified. Through WGCNA, we found that the yellow module was significantly positively correlated with the OA samples and Immune Score and negatively correlated with the normal samples. The 142 DEGs of the yellow module were related to biological processes such as regulation of inflammatory response, positive regulation of inflammatory response, blood vessel morphogenesis, endothelial cell migration, and humoral immune response. The intersections of the genes obtained by the 4 algorithms resulted in 5 final hub genes, and the diagnostic model constructed with these 5 genes showed good performance in the training and validation cohorts.

Conclusions

The 5-gene diagnostic model can be used to diagnose OA and guide clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03183-9.

Weighted gene co-expression network analysis reveals specific modules and hub genes related to immune infiltration of osteoarthritis

Background

The incidence of osteoarthritis (OA), a chronic degenerative disease, is increasing every year. There is no effective clinical treatment for OA and the pathological mechanism remains unclear. Early diagnosis is an effective strategy to control the progress of OA. In this study, we aimed to identify potential early diagnostic biomarkers.

Methods

We downloaded the gene expression profile dataset, GSE51588 and GSE55235, from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public database. The differentially expressed genes (DEGs) were screened out using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) was utilized to build the co-expression network between the normal and OA samples. A Venn diagram was constructed to detect the hub genes. Potential molecular mechanisms and signaling pathways were enriched by gene set variation analysis (GSVA). Single sample gene set enrichment analysis (ssGSEA) was used to identify the immune infiltration of OA.

Results

We screened out three hub genes based on WGCNA and DEGs in this study. GSVA results showed that nuclear factor interleukin-3 (NFIL3) was related to tumor necrosis factor alpha (TNF-α) signaling via nuclear factor kappa-B (NF-κB), the reactive oxygen species pathway, and myelocytomatosis (MYC) targets v2. Highly-expressed ADM (adrenomedullin) pathways included TNF-α signaling via NF-κB, the reactive oxygen species pathway, and ultraviolet (UV) response up. OGN (osteoglycin)-enriched pathways included epithelial mesenchymal transition, coagulation, and peroxisome.

Conclusions

We identified three hub genes (NFIL3, ADM, and OGN) that were correlated to the development and progression of OA, which may provide new biomarkers for early diagnosis.

Whole-Transcriptome Sequence of Degenerative Meniscus Cells Unveiling Diagnostic Markers and Therapeutic Targets for Osteoarthritis

Meniscus plays an important role in joint homeostasis. Tear or degeneration of meniscus might facilitate the process of knee osteoarthritis (OA). Hence, to investigate the transcriptome change during meniscus degeneration, we reveal the alterations of messenger RNA (mRNA), microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) in meniscus during OA by whole-transcriptome sequence. A total of 375 mRNAs, 15 miRNAs, 56 lncRNAs, and 90 circRNAs were significantly altered in the degenerative meniscus treated with interleukin-1β (IL-1β). More importantly, highly specific co-expression RNA (ceRNA) networks regulated by lncRNA LOC107986251-miR-212-5p-SESN3 and hsa_circ_0018069-miR-147b-3p-TJP2 were screened out during IL-induced meniscus degeneration, unveiling potential therapeutic targets for meniscus degeneration during the OA process. Furthermore, lipocalin-2 (LCN2) and RAB27B were identified as potential biomarkers in meniscus degeneration by overlapping three previously constructed databases of OA menisci. LCN2 and RAB27B were both upregulated in osteoarthritic menisci and IL-1β-treated menisci and were highly associated with the severity of OA. This could introduce potential novel molecules into the database of clinical diagnostic biomarkers and possible therapeutic targets for early-stage OA treatment.

Intra-articular low-dose parathyroid hormone (1-34) improves mobility and articular cartilage quality in a preclinical age-related knee osteoarthritis model

Aims

Osteoarthritis (OA) is prevalent among the elderly and incurable. Intra-articular parathyroid hormone (PTH) ameliorated OA in papain-induced and anterior cruciate ligament transection-induced OA models; therefore, we hypothesized that PTH improved OA in a preclinical age-related OA model.

Methods

Guinea pigs aged between six and seven months of age were randomized into control or treatment groups. Three- or four-month-old guinea pigs served as the young control group. The knees were administered 40 μl intra-articular injections of 10 nM PTH or vehicle once a week for three months. Their endurance as determined from time on the treadmill was evaluated before kill. Their tibial plateaus were analyzed using microcalculated tomography (μCT) and histological studies.

Results

PTH increased the endurance on the treadmill test, preserved glycosaminoglycans, and reduced Osteoarthritis Research Society International score and chondrocyte apoptosis rate. No difference was observed in the subchondral plate bone density or metaphyseal trabecular bone volume and bone morphogenetic 2 protein staining.

Conclusion

Subchondral bone is crucial in the initiation and progression of OA. Although previous studies have shown that subcutaneous PTH alleviates knee OA by improving subchondral and metaphyseal bone mass, we demonstrated that intra-articular PTH injections improved spontaneous OA by directly affecting the cartilage rather than the subchondral or metaphyseal bone in a preclinical age-related OA model.

Cite this article: Bone Joint Res 2021;10(8):514–525.

Small Noncoding RNAs in Knee Osteoarthritis: The Role of MicroRNAs and tRNA-Derived Fragments

Knee osteoarthritis (OA) is a degenerative knee joint disease that results from the breakdown of joint cartilage and underlying bone, affecting about 3.3% of the world's population. As OA is a multifactorial disease, the underlying pathological process is closely associated with genetic changes in articular cartilage and bone. Many studies have focused on the role of small noncoding RNAs in OA and identified numbers of microRNAs that play important roles in regulating bone and cartilage homeostasis. The connection between other types of small noncoding RNAs, especially tRNA-derived fragments and knee osteoarthritis is still elusive. The observation that there is limited information about small RNAs different than miRNAs in knee OA was very surprising to us, especially given the fact that tRNA fragments are known to participate in a plethora of human diseases and a portion of them are even more abundant than miRNAs. Inspired by these findings, in this review we have summarized the possible involvement of microRNAs and tRNA-derived fragments in the pathology of knee osteoarthritis.