Analysis of serum rheumatoid factors in patients with rheumatoid arthritis in Han, Tibetan and Hui nationalities in Qinghai

The potential role of serum amyloid A as biomarker of rheumatic diseases: a systematic review and meta-analysis

The identification of novel, robust biomarkers for the diagnosis of rheumatic diseases (RDs) and the presence of active disease might facilitate early treatment and the achievement of favourable long-term outcomes. We conducted a systematic review and meta-analysis of studies investigating the acute phase reactant, serum amyloid A (SAA), in RD patients and healthy controls to appraise its potential as diagnostic biomarker. We searched PubMed, Scopus, and Web of Science from inception to 10 April 2024 for relevant studies. We evaluated the risk of bias and the certainty of evidence using the JBI Critical Appraisal Checklist and GRADE, respectively (PROSPERO registration number: CRD42024537418). In 32 studies selected for analysis, SAA concentrations were significantly higher in RD patients compared to controls (SMD = 1.61, 95% CI 1.24-1.98, p < 0.001) and in RD patients with active disease compared to those in remission (SMD = 2.17, 95% CI 1.21-3.13, p < 0.001). Summary receiving characteristics curve analysis showed a good diagnostic accuracy of SAA for the presence of RDs (area under the curve = 0.81, 95% CI 0.78-0.84). The effect size of the differences in SAA concentrations between RD patients and controls was significantly associated with sex, body mass index, type of RD, and study country. Pending the conduct of prospective studies in different types of RDs, the results of this systematic review and meta-analysis suggest that SAA is a promising biomarker for the diagnosis of RDs and active disease.

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.

Analysis of rheumatoid factor and acute phase proteins using microarrays in patients with rheumatoid arthritis

One of the biomarkers of biggest clinical importance in rheumatoid arthritis (RA) is rheumatoid factor (IgM RF). The rheumatoid factor has insufficient sensitivity and specificity, therefore, to increase the diagnostic information of the test, acute phase proteins were used as concomitant biomarkers. Using biological microchips, we measured IgM RF, C-reactive protein (CRP) and Serum amyloid protein A (SAA) in patients with RA (n = 60), ankylosing spondylitis (AS) (n=55), systemic lupus erythematosus (SLE) (n=20) and healthy donors (HD) (n=9). It was shown that the medians of IgM RF concentrations are significantly higher (p<0.01) in patients with RA compared to patients suffering from other diseases and healthy donors. CRP and SAA were also significantly increased (p<0.05) in patients with RA and AS compared with SLE and HD. It has been shown that the complex determination of three biomarkers in differentiating RA patients with the comparison group had a higher diagnostic sensitivity than the isolated determination of IgM RF, while the addition of SAA makes the greatest contribution to improving the diagnostic characteristics of the biomarker panel: the use of a logistic regression model based on IgM RF and SAA allowed to increase the diagnostic sensitivity of the analysis from 58.3% to 65%. Thus, the developed microarray-based method can be used to detect and elucidate the diagnostic characteristics of RA biomarkers; however, further use requires validation of the obtained results on an expanded sampling.

Association between serum amyloid A and rheumatoid arthritis: A systematic review and meta-analysis

BACKGROUNDS

Consistent correlation of serum amyloid A (SAA) to rheumatoid arthritis (RA) is not completely established. The present study is to systematically summarize their relationship.

METHODS

Publications up to may 2021 were examined using key terms in the PubMed, Cochrane Library, Embase and China national knowledge infrastructure (CNKI) databases.

RESULTS

The total 33 studies, involving in 3524 RA cases and 3537 normal participants, were included. The pooled result indicated that the SAA level in the RA group was markedly higher than that in the control group [standardized mean difference (SMD) = 0.80, 95% CI (0.51, 1.08)]. By stratified analyses, the concentration of SAA was found to be gradually increased with the aggravation of RA. Additionally, the meta-analysis of correlation demonstrated that SAA levels were positively associated with the levels of disease activity score 28 (DAS28) [r = 0.55, 95% CI (0.15, 0.94)], erythrocyte sedimentation rate (ESR) [r = 0.65, 95% CI (0.53, 0.76)], C-reactive protein (CRP) [r = 0.92, 95% CI (0.57, 1.57)], rheumatoid factor (RF) [r = 0.24, 95% CI (0.09, 0.39)], interleukin 4 (IL-4) [r = 0.54, 95% CI (0.30, 0.78)], interleukin 6 (IL-6) [r = 0.46, 95% CI (0.27, 0.65)], interleukin 10 (IL-10) [r = 0.53, 95% CI (0.29, 0.77)], interleukin 17 (IL-17) [r = 0.52, 95% CI (0.27, 0.77)], and anti-cyclic citrullinated peptide antibody (A-CCP) [r = 0.32, 95% CI (0.15, 0.50)], but inversely linked with the levels of hemoglobin [r=-0.51, 95% CI (-0.84, -0.18)]. Furthermore, the allele of SAA 1.3 was actively related with increased risks of RA [OR=1.30, 95% CI (1.02, 1.65)] and of RA with amyloidosis [OR=2.06, 95% CI (1.63, 2.60)]. Besides, the genotype of SAA 1.3/1.3 was positively connected with the risks of RA [OR=1.56, 95% CI (1.00, 2.43)] and of RA with amyloidosis [OR=4.47, 95% CI (2.70, 7.41)].

CONCLUSIONS

High levels of SAA might be associated with elevated risk of RA, and the concentration of SAA might be gradually increased with the aggravation of RA. Moreover, high levels of SAA might play a vital role in RA by enhancing the levels of DAS28, ESR, CRP, RF, IL-4, IL-6, IL-10, IL-17 and A-CCP, or by attenuating hemoglobin levels. More importantly, the allele of SAA 1.3 and genotype of SAA 1.3/1.3 might be the risk factor of RA and of RA with amyloidosis.