Insights into osteoarthritis development from single-cell RNA sequencing of subchondral bone

The causal impact of bioavailable testosterone levels on osteoarthritis: a bidirectional Mendelian randomized study

BACKGROUND

It has been shown that low testosterone levels are associated with the development of osteoarthritis (OA). In our study, we aimed to investigate a bidirectional causal relationship between bioavailable testosterone levels and OA using Mendelian randomization (MR) analysis.

METHODS

In our study, the datasets from publicly available genome-wide association study (GWAS) were adopted, including the OA-related dataset (ukb-b-14486) and the bioavailable testosterone levels-related dataset (ebi-a-GCST90012104). The UKB-B-14,486 dataset contains 462,933 samples in total, including 38,472 OA samples, 424,461 control samples, and 9,851,867 SNPs, all collected from the European population in 2018. Additionally, the EBI-A-GCST90012104 dataset includes 382,988 samples and 16,137,327 SNPs, which reflect data from the European population in 2020. In total, five methods were utilized, namely MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode. Among them, IVW was the main analytical method. Additionally, the sensitivity analysis was carried out through the heterogeneity test, the horizontal pleiotropy test, and the Leave-One-Out (LOO) method.

RESULTS

The result of forward MR analysis demonstrated that bioavailable testosterone levels were considerably relevant to OA, and were a risk factor for OA (OR = 1.01, 95% CI: [1.00, 1.02], P = 0.02). However, through reverse MR analysis, we did not find a causal relationship between OA and bioavailable testosterone levels. Moreover, the results of the sensitivity analysis suggested that our results were reliable.

CONCLUSION

The results of our study supported a causal relationship between bioavailable testosterone levels and OA.

Neural and immune roles in osteoarthritis pain: Mechanisms and intervention strategies

Pain is the leading symptom for most individuals with osteoarthritis (OA), a complex condition marked by joint discomfort. Recently, the dynamic interplay between the nervous and immune systems has become a focal point for understanding pain regulation. Despite this, there is still a substantial gap in our comprehensive understanding of the neuroimmune interactions and their effects on pain in OA. This review examines the bidirectional influences between immune cells and nerves in OA progression. It explores current approaches that target neuroimmune pathways, including promoting M2 macrophage polarization and specific neuronal receptor targeting, for effective pain reduction.

Translational potential statement

This review provides a comprehensive overview of the mechanisms underlying the interplay between the immune system and nervous system during the progression of OA, as well as their contributions to pain. Additionally, it compiles existing intervention strategies targeting neuroimmunity for the treatment of OA pain. This information offers valuable insights for researchers seeking to address the challenge of OA pain.

The causal effect of cytokine cycling levels on osteoarthritis: a bidirectional Mendelian randomized study

Objective

Osteoarthritis (OA) is the most prevalent joint disease globally, serving as a primary cause of pain and disability. However, the pathological processes underlying OA remain incompletely understood. Several studies have noted an association between cytokines and OA, yet the causal link between them remains ambiguous. This study aims to identify cytokines potentially causally related to OA using Mendelian randomization (MR) analysis, informing early clinical diagnosis and treatment decisions.

Methods

We conducted a genome-wide association study (GWAS) on 12 OA traits involving 177,517 cases and 649,173 controls from 9 international cohorts. For discovery MR analysis, we used 103 cytokines from two European populations as instrumental variables (IVs). Concurrently, another European population OA GWAS database (36,185 cases and 135,185 controls) was used to replicate MR analysis, employing the inverse variance weighted (IVW) method as the primary analytic approach. Additional methods tested included MR Egger, Weighted median, and Weighted mode. We merged the MR findings through meta-analysis. Heterogeneity testing, level pleiotropy testing (MR Egger intercept test and MRPRESSO), and sensitivity analysis via Leave One Out (LOO) were conducted to verify result robustness. Lastly, reverse MR analysis was performed.

Results

The meta-analysis merger revealed a correlation between CX3CL1 cycle levels and increased OA risk (OR=1.070, 95% CI: 1.040-1.110; P<0.010). We also observed associations between MCP4 (OR=0.930, 95% CI: 0.890-0.970; P<0.010) and CCL25 (OR=0.930, 95% CI: 0.890-0.970; P<0.010) with reduced OA risk. The sensitivity analysis results corroborate the robustness of these findings.

Conclusion

Our MR analysis indicates a potential causal relationship between CX3CL1, MCP4, CCL25, and OA risk changes. Further research is warranted to explore the influence of cytokines on OA development.

Profiling joint tissues at single-cell resolution: advances and insights

Advances in the profiling of human joint tissues at single-cell resolution have provided unique insights into the organization and function of these tissues in health and disease. Data generated by various single-cell technologies, including single-cell RNA sequencing and cytometry by time-of-flight, have identified the distinct subpopulations that constitute these tissues. These timely studies have provided the building blocks for the construction of single-cell atlases of joint tissues including cartilage, bone and synovium, leading to the identification of developmental trajectories, deciphering of crosstalk between cells and discovery of rare populations such as stem and progenitor cells. In addition, these studies have revealed unique pathogenetic populations that are potential therapeutic targets. The use of these approaches in synovial tissues has helped to identify how distinct cell subpopulations can orchestrate disease initiation and progression and be responsible for distinct pathological outcomes. Additionally, repair of tissues such as cartilage and meniscus remains an unmet medical need, and single-cell methodologies can be invaluable in providing a blueprint for both effective tissue-engineering strategies and therapeutic interventions for chronic joint diseases such as osteoarthritis and rheumatoid arthritis.