Dataset Information

Identifying Novel Osteoarthritis-Associated Genes in Human Cartilage Using a Systematic Meta-Analysis and a Multi-Source Integrated Network.

ABSTRACT: Osteoarthritis, the most common joint disorder, is characterised by deterioration of the articular cartilage. Many studies have identified potential therapeutic targets, yet no effective treatment has been determined. The aim of this study was to identify and rank osteoarthritis-associated genes and micro-RNAs to prioritise those most integral to the disease. A systematic meta-analysis of differentially expressed mRNA and micro-RNAs in human osteoarthritic cartilage was conducted. Ingenuity pathway analysis identified cellular senescence as an enriched pathway, confirmed by a significant overlap (p < 0.01) with cellular senescence drivers (CellAge Database). A co-expression network was built using genes from the meta-analysis as seed nodes and combined with micro-RNA targets and SNP datasets to construct a multi-source information network. This accumulated and connected 1689 genes which were ranked based on node and edge aggregated scores. These bioinformatic analyses were confirmed at the protein level by mass spectrometry of the different zones of human osteoarthritic cartilage (superficial, middle, and deep) compared to normal controls. This analysis, and subsequent experimental confirmation, revealed five novel osteoarthritis-associated proteins (PPIB, ASS1, LHDB, TPI1, and ARPC4-TTLL3). Focusing future studies on these novel targets may lead to new therapies for osteoarthritis.

SUBMITTER: Shorter E

PROVIDER: S-EPMC9030814 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Identifying Novel Osteoarthritis-Associated Genes in Human Cartilage Using a Systematic Meta-Analysis and a Multi-Source Integrated Network.

Shorter Emily E Avelar Roberto R Zachariou Margarita M Spyrou George M GM Raina Priyanka P Smagul Aibek A Ashraf Kharaz Yalda Y Peffers Mandy M Goljanek-Whysall Kasia K de Magalhães João Pedro JP Poulet Blandine B

International journal of molecular sciences 20220415 8

Osteoarthritis, the most common joint disorder, is characterised by deterioration of the articular cartilage. Many studies have identified potential therapeutic targets, yet no effective treatment has been determined. The aim of this study was to identify and rank osteoarthritis-associated genes and micro-RNAs to prioritise those most integral to the disease. A systematic meta-analysis of differentially expressed mRNA and micro-RNAs in human osteoarthritic cartilage was conducted. Ingenuity path ...[more]

PMID: 35457215

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Project description:BackgroundExercise is an effective nonpharmaceutical therapy for knee osteoarthritis (KOA).PurposeTo identify the most effective type of exercise therapy for KOA with regard to pain, stiffness, joint function, and quality of life.Study designSystematic review; Level of evidence, 3.MethodsThe PubMed, Web of Science, Embase, and Cochrane Library databases were searched, from inception to April 4, 2022. Included were randomized controlled trials that assessed the efficacy on KOA among 5 different exercise therapy groups (aquatic exercise [AE], stationary cycling [CY], resistance training [RT], traditional exercise [TC], and yoga [YG]) and compared with the control group. Outcomes among the groups were assessed with the Western Ontario and McMaster University Osteoarthritis Index (WOMAC), 6-minute walk test (6-MWT), visual analog scale (VAS) for pain, and Knee injury and Osteoarthritis Outcome Score (KOOS); weighted mean differences (WMDs) and 95% confidence intervals were calculated. Network meta-analyses comparing outcomes between all groups and with controls were performed, and group rankings were calculated using the surface under the cumulative ranking curve (SUCRA).ResultsA total of 39 studies (N = 2646 participants) were included. Most of the studies failed to blind participants and researchers, resulting in a high risk of performance bias. Significantly worse WOMAC-Pain scores were seen in controls compared with all exercise interventions except AE (WMD [95% CI]: CY, -4.45 [-5.69 to -3.20]; RT, -4.28 [-5.48 to -3.07]; TC, -4.20 [-5.37 to -3.04]; and YG, -0.57 [-1.04 to -1.04]), and worse scores were seen in controls compared with YG regarding WOMAC-Stiffness (WMD, -1.40 [95% CI, -2.45 to -0.34]) and WOMAC-Function (WMD, -0.49 [95% CI, -0.95 to -0.02]). According to the SUCRA, CY was the most effective for improving WOMAC-Pain (80.8%) and 6-MWT (76.1%); YG was most effective for improving WOMAC-Stiffness (90.6%), WOMAC-Function (77.4%), KOOS-Activities of Daily Living (72.0%), and KOOS-Quality of Life (79.1%); AE was the most effective regarding VAS pain (77.2%) and KOOS-Pain (64.0%); and RT was the most effective regarding KOOS-Symptoms (84.5%).ConclusionAll 5 types of exercise were able to ameliorate KOA. AE (for pain relief) and YG (for joint stiffness, limited knee function, and quality of life) were the most effective approaches, followed by RT, CY, and TC.

Project description:BackgroundReverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) remains one of the best-established techniques to assess gene expression patterns. However, appropriate reference gene(s) selection remains a critical and challenging subject in which inappropriate reference gene selction can distort results leading to false interpretations. To date, mixed opinions still exist in how to choose the most optimal reference gene sets in accodrance to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guideline. Therefore, the purpose of this study was to investigate which schemes were the most feasible for the identification of reference genes in a bone and cartilage bioengineering experimental setting. In this study, rat bone mesenchymal stem cells (rBMSCs), skeletal muscle tissue and adipose tissue were utilized, undergoing either chondrogenic or osteogenic induction, to investigate the optimal reference gene set identification scheme that would subsequently ensure stable and accurate interpretation of gene expression in bone and cartilage bioengineering.ResultsThe stability and pairwise variance of eight candidate reference genes were analyzed using geNorm. The V0.15- vs. Vmin-based normalization scheme in rBMSCs had no significant effect on the eventual normalization of target genes. In terms of the muscle tissue, the results of the correlation of NF values between the V0.15 and Vmin schemes and the variance of target genes expression levels generated by these two schemes showed that different schemes do indeed have a significant effect on the eventual normalization of target genes. Three selection schemes were adopted in terms of the adipose tissue, including the three optimal reference genes (Opt3), V0.20 and Vmin schemes, and the analysis of NF values with eventual normalization of target genes showed that the different selection schemes also have a significant effect on the eventual normalization of target genes.ConclusionsBased on these results, the proposed cut-off value of Vn/n + 1 under 0.15, according to the geNorm algorithm, should be considered with caution. For cell only experiments, at least rBMSCs, a Vn/n + 1 under 0.15 is sufficient in RT-qPCR studies. However, when using certain tissue types such as skeletal muscle and adipose tissue the minimum Vn/n + 1 should be used instead as this provides a far superior mode of generating accurate gene expression results. We thus recommended that when the stability and variation of a candidate reference genes in a specific study is unclear the minimum Vn/n + 1 should always be used as this ensures the best and most accurate gene expression value is achieved during RT-qPCR assays.

Dataset Information

Identifying Novel Osteoarthritis-Associated Genes in Human Cartilage Using a Systematic Meta-Analysis and a Multi-Source Integrated Network.

Publications

Identifying Novel Osteoarthritis-Associated Genes in Human Cartilage Using a Systematic Meta-Analysis and a Multi-Source Integrated Network.

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