Impending radiographic erosive progression over the following year in a cohort of consecutive patients with inflammatory polyarthritis: prediction by serum biomarkers

Differences in referral path, clinical and radiographic outcomes between seronegative and seropositive rheumatoid arthritis Mexican Mestizo patients: A cohort study

BACKGROUND

The study compared the referral path, the first two-year clinical outcomes, and the first five-year radiographic outcomes between seronegative patients (SNPs) from a recent-onset rheumatoid arthritis dynamic cohort initiated in 2004 and seropositive patients (SPPs). Predictors of incidental erosive disease were investigated.

PATIENTS AND METHODS

Up to March 2023, one independent observer reviewed the charts from 188 patients with at least two years of clinical assessments and up to five years of annual radiographic assessments. SNPs were defined when baseline RF and ACPA serum titers were within local normal ranges. The erosive disease was defined on hand and/or foot radiographs when at least one unequivocal cortical bone defect was detected. The incidental erosive disease was defined in baseline erosive disease-free patients who developed erosions at follow-ups. Multivariate Cox regression analyses identified hazard ratios (95% confidence interval) for factors to predict incidental erosive disease.

RESULTS

There were 17 (9%) SNPs, and they had a shorter time from symptoms onset to first physician evaluation, visited a lower number of physicians, and received less intensive treatment at referral and during the first years of follow-up than SPPs. Also, they had fewer 0-66 swollen joints and were less frequently persistent on therapy. The erosive disease was detected only in SPPs, and its frequency increased from 10.1% at baseline to 36.1% at the five-year radiographic assessment. There were 53 (31.4%) patients with incidental erosive disease, and differences between SPPs and SNPs were statistically significant at the feet location. Incidental erosive disease was predicted by baseline ACPA, ESR, substantial morning stiffness, and cumulative CRP.

CONCLUSIONS

SNPs showed mild differences in their referral path and clinical outcomes compared to SPPs. However, erosive disease was detected only in SPPs and was predicted by baseline and cumulative clinical and serologic variables.

Osteoclast microRNA Profiling in Rheumatoid Arthritis to Capture the Erosive Factor

In rheumatoid arthritis (RA), only a subset of patients develop irreversible bone destruction. Our aim was to identify a microRNA (miR)-based osteoclast-related signature predictive of erosiveness in RA. Seventy-six adults with erosive (E) or nonerosive (NE) seropositive RA and 43 sex- and age-matched healthy controls were recruited. Twenty-five miRs from peripheral blood mononuclear cell (PBMC)-derived osteoclasts selected from RNA-Seq (discovery cohort) were assessed by qPCR (replication cohort), as were 33 target genes (direct targets or associated with regulated pathways). The top five miRs found differentially expressed in RA osteoclasts were either decreased (hsa-miR-34a-3p, 365b-3p, 374a-3p, and 511-3p [E versus NE]) or increased (hsa-miR-193b-3p [E versus controls]). In vitro, inhibition of miR-34a-3p had an impact on osteoclast bone resorption. An integrative network analysis of miRs and their targets highlighted correlations between mRNA and miR expression, both negative (CD38, CD80, SIRT1) and positive (MITF), and differential gene expression between NE versus E (GXYLT1, MITF) or versus controls (CD38, KLF4). Machine-learning models were used to evaluate the value of miRs and target genes, in combination with clinical data, to predict erosion. One model, including a set of miRs (predominantly 365b-3p) combined with rheumatoid factor titer, provided 70% accuracy (area under the curve [AUC] 0.66). Adding genes directly targeted or belonging to related pathways improved the predictive power of the model for the erosive phenotype (78% accuracy, AUC 0.85). This proof-of-concept study indicates that identification of RA subjects at risk of erosions may be improved by studying miR expression in PBMC-derived osteoclasts, suggesting novel approaches toward personalized treatment. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Biomarkers for the diagnosis and treatment of rheumatoid arthritis - a systematic review

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease, symmetrically affecting the small joints. Biomarkers are tools that can be used in the diagnosis and monitoring of RA.

AIM

To systematically explore the role of the biomarkers: C-reactive protein (CRP), rheumatoid factor (RF), anti-cyclic citrullinated protein (Anti-CCP), 14-3-3η protein, and the multi-biomarker disease activity (MBDA) score for the diagnosis and treatment of RA.

METHODS

A systematic review of the English literature using four different databases was carried out.

RESULTS

CRP >7.1 mg/L predicted poor conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) outcome in RA. Anti-CCP, CRP ≥0.3 mg/dL, and RF predicted bone erosion and cartilage destruction. Combination of high 14-3-3η protein with RF and CRP improved the prediction of rapid erosion progression (REP). Anti-CCP was not associated with disease activity but was associated with increased radiographic damage (r = 0.46, p = 0.048). RF was not associated with joint damage but correlated with ultrasound-detected bone erosion. The 14-3-3η protein significantly correlated with inflammation, bone rremodeling, and osteoporosis in RA patients (p < 0.05). In addition, the 14-3-3η protein positively correlated with RA duration (p = 0.003), disease aactivity, and positive RF (p = 0.025) and it distinguished early from established RA. Early MBDA scores correlated with later response in disease activity after 6 and 12 weeks of treatment (p < 0.05). The MBDA score was able to differentiate between small differences in disease activity, predicted remission over 1-year pperiod, and was a strong predictor of radiographic progression of RA.

CONCLUSION

The investigated biomarkers are helpful tools in clinical practice for diagnosis, monitoring of treatment, and predicting prognosis in RA patients. However, further research is still required to investigate novel biomarkers for the pre-treatment selection of potentially responsive patients before starting therapy for a precision medicine in this area.

Serum 14-3-3η is a Marker that Complements Current Biomarkers for the Diagnosis of RA: Evidence from a Meta-analysis

OBJECTIVE

To systematically evaluate the diagnostic value of 14-3-3η protein for rheumatoid arthritis (RA).

METHOD

Searched PubMed, Web of Science, Embase and China Biology Medicine (CBM) databases comprehensively from inception to May 2020. The evaluation index were the pooled sensitivity, specificity, diagnosis odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), as well as the area under the summary receiver operating characteristic (SROC) curves. Meta-Disc 1.4 and RevMan 5.3 were used to analyze all statistics. QUADAS-2 tool was applied to evaluate the quality of eligible studies. Subgroup analysis and meta-regression were used to explore the sources of heterogeneity.

RESULTS

Nine articles containing eleven records were eligible for this meta-analysis. The pooled sensitivity of 14-3-3η was 0.63 (95% CI: 0.60 to 0.66), the pooled specificity was 0.90 (95% CI: 0.88 to 0.91). The pooled PLR and NLR was 6.10 (95% CI: 4.67 to 7.96) and 0.40 (95% CI: 0.33 to 0.48), respectively. The pooled DOR was 15.90 (95% CI: 11.15 to 22.68), and the area under the curve (AUC) was 0.8696. Compared with a single indicator (rheumatoid factor or anti-citrullinated protein antibodies), adding 14-3-3η can bring incremental benefits to the diagnosis of RA. The results of subgroup analysis and meta-regression suggested that the two factors (ethnicity, early vs established RA) we analyzed might not be the source of heterogeneity (P value were 0.0979 and 0.4298, respectively) and there was no publication bias among these articles (P = .42).

CONCLUSION

Serum 14-3-3η protein is a supplementary biomarker in the diagnosis of RA.