Combined bioinformatics analysis reveals gene expression and DNA methylation patterns in osteoarthritis

Association of integrin-β2 polymorphism and expression with the risk of rheumatoid arthritis and osteoarthritis in Egyptian patients

BACKGROUND

The genetic architecture of rheumatoid arthritis (RA) and osteoarthritis (OA) are still unclear. Although RA and OA have quite different causes, they share synovial inflammation, risk factors, and some disease-associated genes, including the integrin subunit β2 (ITGB2)/CD18 gene involved in extracellular matrix interactions and immune cell signaling. However, the functional role of ITGB2 genetic variants, its circulating expression pattern, and their clinical usefulness in RA and OA remain unexplored. Our study appraised the association of ITGB2 rs2070946 single nucleotide polymorphism with the vulnerability to RA and OA and its influence on ITGB2 mRNA expression, along with the potential of serum ITGB2 expression in RA and OA diagnosis.

METHODS

This study included 70 RA patients, 70 primary OA patients, and 60 healthy volunteers. Genotyping and gene expression analysis were performed using qPCR. Bioinformatics analysis was employed to construct the protein-protein interaction (PPI) network of ITGB2.

RESULTS

Serum ITGB2 mRNA expression was upregulated in both RA and OA compared to healthy controls. ITGB2 rs2070946 was associated with escalating risk of both diseases. RA patients harboring the rs2070946 CC or TC + CC genotypes had higher serum ITGB2 expression than the TT genotype carriers. Likewise, OA patients having the minor homozygote CC genotype had higher serum ITGB2 expression than those carrying the TT, TC or TT + TC genotypes. Serum ITGB2 expression showed profound diagnostic potential for RA and OA in receiver-operating characteristic analysis. In RA, serum ITGB2 expression positively correlated with rheumatoid factor and disease activity score 28 (DAS28). The ITGB2-PPI network enriched in cell-cell adhesion, ICAM-3 receptor activity, T-cell activation, leukocyte adhesion, complement binding, and NF-κB, tumor necrosis factor, and interleukin signaling pathways.

CONCLUSION

These findings embrace the impact of ITGB2 rs2070946 as a novel genetic biomarker of both RA and OA, which could alter the ITGB2 expression. Serum ITGB2 expression could aid in timely diagnosis of RA and OA.

Characterizing OPRM1 DNA methylation in prescription opioid users with chronic musculoskeletal pain

Introduction

Many patients with chronic pain use prescription opioids. Epigenetic modification of the μ-opioid receptor 1 (OPRM1) gene, which codes for the target protein of opioids, may influence vulnerability to opioid abuse and response to opioid pharmacotherapy, potentially affecting pain outcomes.

Objective

Our objective was to investigate associations of clinical and sociodemographic factors with OPRM1 DNA methylation in patients with chronic musculoskeletal pain on long-term prescription opioids.

Methods

Sociodemographic variables, survey data (Rapid Estimate of Adult Health Literacy in Medicine-Short Form, Functional Comorbidity Index [FCI], PROMIS 43v2.1 Profile, Opioid Risk Tool, and PROMIS Prescription Pain Medication Misuse), and saliva samples were collected. The genomic DNA extracted from saliva samples were bisulfite converted, amplified by polymerase chain reaction, and processed for OPRM1-targeted DNA methylation analysis on a Pyrosequencing instrument (Qiagen Inc, Valencia, CA). General linear models were used to examine the relationships between the predictors and OPRM1 DNA methylation.

Results

Data from 112 patients were analyzed. The best-fitted multivariable model indicated, compared with their counterparts, patients with > eighth grade reading level, degenerative disk disease, substance abuse comorbidity, and opioid use < 1 year (compared with >5 years), had average methylation levels that were 7.7% (95% confidence interval [CI] 0.95%, 14.4%), 11.7% (95% CI 2.7%, 21.1%), 21.7% (95% CI 10.7%, 32.5%), and 16.1% (95% CI 3.3%, 28.8%) higher than the reference groups, respectively. Methylation levels were 2.2% (95% CI 0.64%, 3.7%) lower for every 1 unit increase in FCI and greater by 0.45% (95% CI 0.08%, 0.82%) for every fatigue T score unit increase.

Conclusions

OPRM1 methylation levels varied by several patient factors. Further studies are warranted to replicate these findings and determine potential clinical utility.