Contribution of Multiplex Immunoassays to Rheumatoid Arthritis Management: From Biomarker Discovery to Personalized Medicine

IL-31 and IL-33 in rheumatoid arthritis patients

Objective – to investigate clinical and diagnostic significance of IL-31 and IL-33 determination in patients with rheumatoid arthritis (RA).

Material and methods. 154 patients with a reliable diagnosis of RA were examined. Serum levels of IL-31 and IL-33 were studied using multiplex xMAP technology on Bio-PlexTM 200 System analyzer (BIO-RAD, USA). The upper limit of the norm in the study of 20 healthy donor sera was (M+3σ): IL-31 – 15.08 pg/ml, IL-33 – 3.40 pg/ml.

Results. IL-31 (Me (25th; 75th percentile) – 13.75 (5.63; 308.52) and 6.10 (2.87; 8.62) pg/ml (p<0.001), IL-33 – 18.86 (7.45; 65.95) and 0.52 (0.17; 0.78) pg/ml (p><0.001) levels were observed in RA patients in comparison with the control group. An increase in IL-33 concentration (more than 3.40 pg/ml) was observed in 87.0% of patients, and IL-31 (more than 15.08 pg/ml) in 48.1% of patients with RA. An increase in IL-33 alone was observed in 42.2% (65 of 154 patients) with RA, while an isolated increase in IL-31 concentration was observed in only 2 (1.3%) patients. Simultaneous hyperproduction of IL-33 and IL-31 occurred in 69 (44.9%) patients. We revealed positive correlation of clinical and laboratory parameters of RA with cytokine concentration: SDAI correlated with IL-33 (r=0.36; p><0.05); CRP – with IL-31 (r=0.49; p><0,05) and IL-33 (r=0.40; p><0.05). Conclusion. Concentrations of IL-31 and IL-33 are elevated in RA patients and correlate with the indices of inflammatory activity of the disease.>< 0.001), IL-33 – 18.86 (7.45; 65.95) and 0.52 (0.17; 0.78) pg/ml (p<0.001) levels were observed in RA patients in comparison with the control group. An increase in IL-33 concentration (more than 3.40 pg/ml) was observed in 87.0% of patients, and IL-31 (more than 15.08 pg/ml) in 48.1% of patients with RA. An increase in IL-33 alone was observed in 42.2% (65 of 154 patients) with RA, while an isolated increase in IL-31 concentration was observed in only 2 (1.3%) patients. Simultaneous hyperproduction of IL-33 and IL-31 occurred in 69 (44.9%) patients. We revealed positive correlation of clinical and laboratory parameters of RA with cytokine concentration: SDAI correlated with IL-33 (r=0.36; p><0.05); CRP – with IL-31 (r=0.49; p><0,05) and IL-33 (r=0.40; p><0.05). Conclusion. Concentrations of IL-31 and IL-33 are elevated in RA patients and correlate with the indices of inflammatory activity of the disease.>< 0.001) levels were observed in RA patients in comparison with the control group. An increase in IL-33 concentration (more than 3.40 pg/ml) was observed in 87.0% of patients, and IL-31 (more than 15.08 pg/ml) in 48.1% of patients with RA. An increase in IL-33 alone was observed in 42.2% (65 of 154 patients) with RA, while an isolated increase in IL-31 concentration was observed in only 2 (1.3%) patients. Simultaneous hyperproduction of IL-33 and IL-31 occurred in 69 (44.9%) patients. We revealed positive correlation of clinical and laboratory parameters of RA with cytokine concentration: SDAI correlated with IL-33 (r=0.36; p<0.05); CRP – with IL-31 (r=0.49; p><0,05) and IL-33 (r=0.40; p><0.05). Conclusion. Concentrations of IL-31 and IL-33 are elevated in RA patients and correlate with the indices of inflammatory activity of the disease.>< 0.05); CRP – with IL-31 (r=0.49; p< ,05) and IL-33 (r=0.40; p<0.05)

Conclusion. Concentrations of IL-31 and IL-33 are elevated in RA patients and correlate with the indices of inflammatory activity of the disease.

Comparative Pharmacokinetics, Safety, and Immunogenicity Study of the Prefilled Syringe and Lyophilized Formulation of a Recombinant Human Tumor Necrosis Factor-α Receptor II:lgG Fc Fusion Protein in Healthy Chinese Male Subjects

This study aimed to compare the pharmacokinetics, safety, and immunogenicity of the prefilled syringe (PFS) with lyophilized (LYO) recombinant human tumor necrosis factor-α receptor II:lgG Fc fusion protein (rhTNFR:Fc) in healthy Chinese male subjects. A single-center, randomized, open-label, 2-period, crossover study was performed in healthy Chinese male subjects. Subjects were randomly assigned into 2 sequences and received a subcutaneous injection of 25 mg rhTNFR:Fc PFS or rhTNFR:Fc LYO (Anbainuo), with a 35-day washout between the 2 periods. Blood samples were collected at specified time intervals, and then serum concentrations of rhTNFR:Fc were analyzed by enzyme-linked immunosorbent assay. The maximum serum concentration, area under the concentration-time curve (AUC) from time 0 to the last quantifiable concentration, and AUC from time 0 to infinity were all calculated and evaluated. Meanwhile, safety and immunogenicity were also assessed. A total of 82 subjects completed the study, and six subjects withdrew for various reasons. The 90%CIs for geometric mean ratios of maximum serum concentration, AUC from time 0 to the last quantifiable concentration, and AUC from time 0 to infinity were all within the equivalence range of 80% to 125%. Safety was comparable between the 2 formulations with low immunogenicity. rhTNFR:Fc PFS exhibited similar pharmacokinetic and safety profiles of rhTNFR:Fc LYO (Anbainuo) in healthy Chinese male subjects.

Machine learning to identify immune-related biomarkers of rheumatoid arthritis based on WGCNA network

OBJECTIVES

This study was designed to identify the potential diagnostic biomarkers of rheumatoid arthritis (RA) and to explore the potential pathological relevance of immune cell infiltration in this disease.

METHODS

Three previously published datasets containing gene expression data from 35 RA patients and 29 controls (GSE55235, GSE55457, and GSE12021) were downloaded from the GEO database, after which a weighted correlation network analysis (WGCNA) approach was utilized to clarify differentially abundant genes. Candidate biomarkers of RA were then identified via the use of a LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analyses. Data were validated based upon the area under the receiver operating characteristic curve (AUC) values, with hub genes being identified as those with an AUC > 85% and a P value < 0.05. Lastly, the CIBERSORT algorithm was used to assess immune cell infiltration of RA tissues, and correlations between immune cell infiltration and disease-related diagnostic biomarkers were assessed.

RESULTS

The green-yellow module containing 87 genes was found to be highly correlated with RA positivity. FADD, CXCL2, and CXCL8 were identified as potential RA diagnostic biomarkers (AUC > 0.85), and these results were validated using the GSE77298 dataset. Immune cell infiltration analyses revealed the expression of hub genes to be correlated with mast cells, monocytes, activated NK cells, CD8 T cells, resting dendritic cells, and plasma cells.

CONCLUSION

These data indicate that FADD, CXCL2, and CXCL8 are valuable diagnostic biomarkers of RA, offering new insight that can guide future studies of RA incidence and progression.

Advances in the diagnosis of autoimmune diseases based on citrullinated peptides/proteins

Introduction: Autoimmune diseases are still one of the hard obstacles associated with humanity. There are many exogenous and endogenous etiological factors behind autoimmune diseases, which may be combined or dispersed to stimulate the autoimmune responses. Protein citrullination represents one of these factors. Harnessing specific citrullinated proteins/peptides could early predict and/or diagnose some of the autoimmune diseases. Many generations of diagnostic tools based on citrullinated peptides with comparable specificity/sensitivity are available worldwide.Areas covered: In this review, we discuss the deimination reaction behind the citrullination of most known autoantigens targeted, different generations of diagnostic tools based on citrullinated probes with specificity/sensitivity of each as well as newly developed assays. Furthermore, the most advanced molecular analytical tools to detect the citrullinated residues in the biological fluid and their performance are also evaluated, providing new avenues to early detect autoimmune diseases with high accuracy.Expert opinion: With the current specificity/sensitivity tools available for autoimmune disease detection, emphasis must be placed on developing more advance and effective, early, rapid, and simple diagnostic devices for autoimmune disease monitoring (similar to a portable device for sugar test at home). The molecular analytical devices with dual and/or multiplexe functions should be more simplified and invested in clinical laboratories.

Applications of Protein Microarrays in Biomarker Discovery for Autoimmune Diseases

Dysregulated autoantibodies and cytokines were deemed to provide important cues for potential illnesses, such as various carcinomas and autoimmune diseases. Increasing biotechnological approaches have been applied to screen and identify the specific alterations of these biomolecules as distinctive biomarkers in diseases, especially autoimmune diseases. As a versatile and robust platform, protein microarray technology allows researchers to easily profile dysregulated autoantibodies and cytokines associated with autoimmune diseases using various biological specimens, mainly serum samples. Here, we summarize the applications of protein microarrays in biomarker discovery for autoimmune diseases. In addition, the key issues in the process of using this approach are presented for improving future studies.

Identification of a Novel Serum Proteomic Signature for Primary Sjögren's Syndrome

Context

Primary Sjögren's syndrome (pSS) is a complex heterogeneous autoimmune disease (AID) which can mimic rheumatoid arthritis (RA) or systemic lupus erythematosus (SLE). Our exploratory study investigated serum biomarkers that may discriminate pSS from RA and SLE.

Methods

Serum concentrations of 63 biomarkers involved in immune cell trafficking, inflammatory response, cellular movement, and cell-to-cell signaling were measured in AID patients, included prospectively into the study at the Montpellier University Hospital. A multivariate analysis by multiple logistic regression was performed, and discriminative power assessed using logistic regression adjusted on significant demographic factors.

Results

Among the 95 patients enrolled, 42 suffered from pSS, 28 from RA, and 25 from SLE. Statistical analysis showed that concentrations of BDNF (OR = 0.493 with 95% CI [0.273-0.891]; p = 0.0193) and I-TAC/CXCL11 (OR = 1.344 with 95% CI [1.027-1.76]; p = 0.0314) can significantly discriminate pSS from RA. Similarly, greater concentrations of sCD163 (OR = 0.803 with 95% CI [0.649-0.994]; p = 0.0436), Fractalkine/CX3CL1 (OR = 0.534 with 95% CI [0.287-0. 991]; p = 0.0466), MCP-1/CCL2 (OR = 0.839 with 95% CI [0.732-0.962]; p = 0.0121), and TNFa (OR = 0.479 with 95% CI [0.247-0.928]; p = 0.0292) were associated with SLE diagnosis compared to pSS. In addition, the combination of low concentrations of BDNF and Fractalkine/CX3CL1 was highly specific for pSS (specificity 96.2%; positive predictive value 80%) compared to RA and SLE, as well as the combination of high concentrations of I-TAC/CXCL11 and low concentrations of sCD163 (specificity 98.1%; positive predictive value 75%).

Conclusion

Our study highlights biomarkers potentially involved in pSS, RA, and SLE pathophysiology that could be useful for developing a pSS-specific diagnostic tool.