MiR-26a regulates the expression of serum IGF-1 in patients with osteoporosis and its effect on proliferation and apoptosis of mouse chondrocytes.

OBJECTIVES: To examine the effects of the regulation on IGF-1 by miR-26a on the serum of patients with osteoporosis (OP) and apoptosis and proliferation of chondrocytes of mice with OP. METHODS: Totally 47 patients with OP treated in our hospital between July 2018 and November 2019 were selected as the research group, and 42 healthy individuals in physical examination over this period were selected as the control group. Serum was sampled from each participant in both groups, and miR-26a in the sampled serum was quantified and compared. In addition, chondrocytes were sampled from mice with OP. The changes of proliferation and apoptosis of the chondrocytes were analyzed via MTT and flow cytometry, and the levels of Caspase3, Caspase9, Bax, and Bcl-2 were quantified by western blot (WB) assay. RESULTS: MiR-26a was expressed highly in the serum of patients with OP and chondrocytes of mice with OP, while IGF-1 was lowly expressed in them. According to the dual-luciferase reporter assay, there was a targeting correlation between miR-26a and IGF-1, and suppressing miR-26a significantly up-regulated the expression and protein level of IGF-1. CONCLUSIONS: MiR-26a can serve as a biological marker for the diagnosis of OP, and it can suppress the proliferation of chondrocytes and promote their apoptosis by regulating IGF-1.

miR-17-5p and miR-19b-3p prevent osteoarthritis progression by targeting EZH2.

Osteoarthritis (OA) is a joint disease caused by a variety of factors, including aging, obesity and trauma. MicroRNAs (miRNAs) have been reported to be crucial regulators during OA progression. The present study aimed to investigate the role of miR-17-5p and miR-19b-3p during OA development. Interleukin (IL)-1ß-treated chondrocytes were used to mimic OA in vitro. The expression levels of miR-17-5p and enhancer of zeste homolog 2 (EZH2) were measured in cartilage tissues and chondrocytes using reverse transcription-quantitative PCR or western blotting. Apoptosis was assessed by flow cytometry. The protein expression levels of extracellular matrix (ECM)-associated genes were detected by western blotting. The binding sites between miR-17-5p or miR-19b-3p and EZH2 were predicted using the MicroT-CDS online database and verified using dual-luciferase reporter and RIP assays. miR-17-5p expression was downregulated, whereas EZH2 expression was upregulated in OA cartilage tissues and IL-1ß-induced chondrocytes compared with that in the control tissues and cells. miR-17-5p mimics inhibited IL-1ß-induced apoptosis and ECM degradation in chondrocytes. EZH2 was the target of miR-17-5p and miR-19b-3p in chondrocytes, and enhanced apoptosis and ECM degradation in IL-1ß-stimulated chondrocytes. Rescue experiments revealed that miR-17-5p or miR-19b-3p mimic-induced inhibition of OA progression was reversed by EZH2 overexpression. In conclusion, miR-17-5p and miR-19b-3p inhibited OA progression by targeting EZH2, which may serve as a potential therapeutic target for OA.

Identification of differential modules in ankylosing spondylitis using systemic module inference and the attract method.

The objective of the present study was to identify differential modules in ankylosing spondylitis (AS) by integrating network analysis, module inference and the attract method. To achieve this objective, four steps were conducted. The first step was disease objective network (DON) for AS, and healthy objective network (HON) inference dependent on gene expression data, protein-protein interaction networks and Spearman's correlation coefficient. In the second step, module detection was performed by utilizing a clique-merging algorithm, which comprised of exploring maximal cliques by clique algorithm and refining or merging maximal cliques with a high overlap. The third part was seed module evaluation through module pair matches by Jaccard score and module correlation density (MCD) calculation. Finally, in the fourth step, differential modules between the AS and healthy groups were identified based on a gene set enrichment analysis-analysis of variance model in the attract method. There were 5,301 nodes and 28,176 interactions both in DON and HON. A total of 20 and 21 modules were detected for the AS and healthy group, respectively. Notably, six seed modules across two groups were identified with Jaccard score ≥0.5, and these were ranked in descending order of differential MCD (ΔC). Seed module 1 had the highest ΔC of 0.077 and Jaccard score of 1.000. By accessing the attract method, one differential module between the AS group and healthy group was identified. In conclusion, the present study successfully identified one differential module for AS that may be a potential marker for AS target therapy and provide insights for future research on this disease.

Pathway analysis based on Monte Carlo Cross-Validation in polyarticular juvenile idiopathic arthritis.

INTRODUCTION: Juvenile idiopathic arthritis (JIA) is a common chronic disease with onset before the 16 years old in a child. Polyarticular JIA has been reported as the main form of JIA in several locations. Until now, understanding of the genetic basis of JIA is incomplete. The purpose of this study was to identify pathway pairs of great potential functional relevance in the progression of polyarticular JIA. MATERIALS AND METHODS: Microarray data of 59 peripheral blood samples from healthy children and 61 samples from polyarticular JIA were transformed to gene expression data. Differential expressed genes (DEG) between patients and normal controls were identified using Linear Models for Microarray Analysis. After performed enrichment of DEG, differential pathways were identified with Fisher's test and false discovery rate. Differential pathway pairs were constructed with random two differential pathways, and were evaluated by Random Forest classification. Monte Carlo Cross-Validation was introduced to screen the best pathway pair. RESULTS: 42 DEG with P-values<0.01 were identified. 19 differential pathways with P-values<0.01 were identified. Area under the curve (AUC) of pathway pairs was generated with RF classification. After 50 bootstraps of Monte Carlo Cross-Validation, the best pathway pair with the highest AUC value was identified, and it was the pair of tumoricidal function of hepatic natural killer cells pathway and erythropoietin signaling pathway. CONCLUSION: These identified pathway pairs may play pivotal roles in the progress of polyarticular JIA and can be applied for diagnosis. Particular attention can be focused on them for further research.