Pro-Inflammatory Biomarkers Combined with Body Composition Display a Strong Association with Knee Osteoarthritis in a Community-Based Study

METTL3 mediated ferroptosis in chondrocytes and promoted pain in KOA via HMGB1 m6A modification

Methyltransferase-like 3 (METTL3) plays a role in the development of knee osteoarthritis (KOA). However, the mechanism underlying the role of METTL3 in KOA is unclear. This work investigated the effects of MELLT3 on ferroptosis and pain relief in in vitro and in vivo KOA models. Chondrocytes were treated with 10 ng/mL interleukin-1β (IL-1β) or 5 μM Erastin (ferroptosis inducer). IL-1β or Erastin treatment inhibited cell viability and glutathione levels; increased Fe2+, lipid reactive oxygen species and malondialdehyde production; and decreased glutathione peroxidase 4, ferritin light chain and solute carrier family 7 member 11 levels. The overexpression of METTL3 facilitated the N6-methyladenosine methylation of high mobility group box 1 (HMGB1). HMGB1 overexpression reversed the effect of sh-METTL3 on IL-1β-treated chondrocytes. A KOA rat model was established by the injection of monosodium iodoacetate into the joints and successful model establishment was confirmed by haematoxylin and eosin staining and Safranin O/Fast Green staining. METTL3 depletion alleviated cartilage damage, the inflammatory response, ferroptosis and knee pain in KOA model rats, and these effects were reversed by the addition of HMGB1. In conclusion, METTL3 depletion inhibited ferroptosis and the inflammatory response, and ameliorated cartilage damage and knee pain during KOA progression by regulating HMGB1.

Osteoarthritis Year in Review 2024: Molecular biomarkers of osteoarthritis

OBJECTIVE

To provide a comprehensive and insightful summary of studies on molecular biomarkers at the gene, protein, and metabolite levels across different sample types and joints affected by osteoarthritis (OA).

METHODS

A literature search using the PubMed database for publications on OA biomarkers published between April 1, 2023 and April 30, 2024 was performed. Publications were then screened, examined at length, and summarized in a narrative review.

RESULTS

Out of the 364 papers initially identified, 44 publications met inclusion criteria, were relevant to OA, and were further examined for data extraction and discussion. These studies included 1 genomic analysis, 22 on protein markers, 6 on metabolite markers, 9 on inflammatory mediators, and 6 integrating multiple molecular levels.

CONCLUSIONS

Significant advancements have been made in identifying molecular biomarkers for OA, encompassing various joints, sample types, and molecular levels. Despite this progress, gaps remain, particularly in the need for validation, larger sample sizes, the integration of more clinical data, and consideration of covariates. For early detection and improved treatment of OA, continued efforts in biomarker identification are needed. This effort should seek to identify effective biomarkers that advance early detection, support prevention, evaluate interventions, and improve patient outcomes.

Systemic inflammatory biomarkers are novel predictors of all-cause and cardiovascular mortality in individuals with osteoarthritis: a prospective cohort study using data from the NHANES

BACKGROUND

Chronic inflammation may contribute to increased mortality risk in individuals with osteoarthritis (OA), but research on the prognostic value of inflammatory biomarkers is limited. We aimed to evaluate the associations of the systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) with all-cause and cardiovascular mortality among US adults with OA.

METHODS

This cohort study included 3545 adults with OA aged ≥ 20 years from the National Health and Nutrition Examination Survey 1999-2020. The SII and SIRI were calculated using complete blood cell count data. Participants were categorized as having a higher or lower SII and SIRI using cutoff points derived by the maximally selected rank statistics method. Cox proportional hazards models, Fine-Gray competing risk regression models and time-dependent receiver operating characteristic (ROC) analysis were used to evaluate the associations between the SII/SIRI and mortality in OA patients.

RESULTS

Over a median follow-up of 5.08 (3.42-9.92) years, 636 (17.94%) deaths occurred, including 149 (4.20%) cardiovascular deaths. According to multivariable-adjusted models involving demographic, socioeconomic, and health factors, OA patients with a higher SII had a twofold greater risk of all-cause mortality than patients with a lower SII (HR 2.01; 95% CI: 1.50-2.68). Similarly, a higher SIRI was associated with an 86% increased risk of all-cause mortality relative to a lower SIRI (HR 1.86; 95% CI: 1.46-2.38). Similar to the trend found with all-cause mortality, patients with an elevated SII and SIRI had a 88% and 67% increased risk of cardiovascular mortality, respectively, compared to patients with a lower SII (HR 1.88; 95% CI: 1.16-3.03) and SIRI (HR 1.67; 95% CI: 1.14-2.44). Time-dependent ROC curves showed that both the SII and SIRI have moderate and valid performance in predicting short- and long-term mortality in patients with OA.

CONCLUSIONS

Higher SII and SIRI values were associated with greater all-cause and cardiovascular mortality among US adults with OA.

The diagnostic role of the systemic inflammation index in patients with immunological diseases: a systematic review and meta-analysis

The identification of novel, easily measurable biomarkers of inflammation might enhance the diagnosis and management of immunological diseases (IDs). We conducted a systematic review and meta-analysis to investigate an emerging biomarker derived from the full blood count, the systemic inflammation index (SII), in patients with IDs and healthy controls. We searched Scopus, PubMed, and Web of Science from inception to 12 December 2023 for relevant articles and evaluated the risk of bias and the certainty of evidence using the Joanna Briggs Checklist and the Grades of Recommendation, Assessment, Development, and Evaluation Working Group system, respectively. In 16 eligible studies, patients with IDs had a significantly higher SII when compared to controls (standard mean difference, SMD = 1.08, 95% CI 0.75 to 1.41, p < 0.001; I2 = 96.2%, p < 0.001; moderate certainty of evidence). The pooled area under the curve (AUC) for diagnostic accuracy was 0.85 (95% CI 0.82-0.88). In subgroup analysis, the effect size was significant across different types of ID, barring systemic lupus erythematosus (p = 0.20). In further analyses, the SII was significantly higher in ID patients with active disease vs. those in remission (SMD = 0.81, 95% CI 0.34-1.27, p < 0.001; I2 = 93.6%, p < 0.001; moderate certainty of evidence). The pooled AUC was 0.74 (95% CI 0.70-0.78). Our study suggests that the SII can effectively discriminate between subjects with and without IDs and between ID patients with and without active disease. Prospective studies are warranted to determine whether the SII can enhance the diagnosis of IDs in routine practice. (PROSPERO registration number: CRD42023493142).