How to investigate: Pre-clinical rheumatoid arthritis

Association of Four VEGFA Gene Variants with Rheumatoid Arthritis Risk: A Meta-analysis and Trial Sequential Analysis

The association between rheumatoid arthritis (RA) risk and specific variants of the Vascular Endothelial Growth Factor A (VEGFA) gene remains contentious. This study sought to elucidate the correlations between RA risk and several VEGFA gene variants, including VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), VEGFA-2578 (rs699947), VEGFA-1154 (rs1570360), through a comprehensive meta-analysis. We systematically reviewed literature from the Cochrane Library database, Embase, PubMed, Web of Science, China National Knowledge Infrastructure, and the Wanfang Data Information Service platform to gather relevant case-control studies. Using odds ratio (OR) and 95% confidence interval (95% CI), we analyzed the data to assess potential correlations. Sensitivity analysis and the Egger's test were employed to ensure the results stability and to evaluate potential publication bias. Additionally, trial sequential analysis (TSA) was conducted to validate the findings. Our meta-analysis incorporated ten studies involving 2817 patients and 2855 controls. Results indicated that the AA genotype of VEGFA-1154 (rs1570360) is associated with a reduced risk of RA in the overall population (AG + GG vs AA: P = 0.032 OR = 1.932 95% CI 1.059-3.523). However, no significant association is found for VEGFA-634 (rs2010963), VEGFA-C936 (rs3025039), and VEGFA-2578 (rs699947) variants with RA risk. Subgroup analysis revealed a significant association between the VEGF rs3025039(C936) variant and RA risk in the PCR-RFLP group under the TC vs. CC model. TSA confirmed the sufficiency of the sample size for robust conclusions. These findings suggest that the G allele of VEGFA-1154 (rs1570360) may increase RA risk, whereas the A allele appears to confer a protective effect. This study enhances our understanding of the genetic predispositions to RA and underscores the potential role of VEGFA gene variants in its pathogenesis.

Subclinical bowel inflammation increases healthcare resources utilization and steroid use before diagnosis of inflammatory bowel disease

BACKGROUND

Previous data support that the inflammatory process underlying ulcerative colitis (UC) and Crohn's disease (CD) can start years before the diagnosis. The aim of this study was to determine if patients with an incidental diagnosis of UC or CD demonstrate an increase in healthcare utilization in the years preceding the symptomatic onset of the disease.

METHODS

We performed a multicenter, retrospective, hospital-based, case-control study. Patients with an incidental diagnosis of UC or CD during the colorectal cancer screening program at 9 hospitals were included. Cases were matched 1:3 and compared separately with two control populations: one including healthy non-IBD subjects adjusted by gender, age, and date, excluding those with visits to Gastroenterology; and a second control cohort of UC/CD patients with symptomatic onset.

RESULTS

A total of 124 patients with preclinical inflammatory bowel disease (IBD) were included (87 UC, 30 CD, 7 IBD unclassified; median age 56 years). Patients with preclinical IBD showed an increase in the number of visits to Primary Care up to 3 and 5 years before diagnosis (aIRR 1.59, 95% CI [1.37-1.86], p = 0.001; aIRR 1.43, 95% CI [1.24-1.67], p = 0.01) and more frequent use of steroids (aOR 2.84, 95% CI [1.21-6.69], p = 0.03; aOR 2.25, 95% CI [1.06-4.79], p = 0.04) compared to matched non-IBD healthy controls, respectively. In contrast, patients with a symptomatic onset visited Primary Care less frequently, but they had an increase in the number of visits to Emergency Department, specialist care, sick-leaves, CT/ultrasound examinations, and use of antibiotics or systemic steroids.

CONCLUSIONS

There is an increased need for medical assistance and use of systemic steroids during the presymptomatic phase of IBD. These results will help in establishing new tools for early identification of IBD in the future.

Diagnosing rheumatoid arthritis disease using fuzzy expert system and machine learning techniques

Rheumatoid Arthritis (RA) is a very common autoimmune disease that causes significant morbidity and mortality, and therefore early diagnosis and treatment are important. Early diagnosis of RA and knowing the severity of the disease are very important for the treatment to be applied. The diagnosis of RA usually requires a physical examination, laboratory tests, and a review of the patient’s medical history. In this study, the diagnosis of RA was made with two different methods using a fuzzy expert system (FES) and machine learning (ML) techniques, which were designed and implemented with the help of a specialist in the field, and the results were compared. For this purpose, blood counts were taken from 286 people, including 91 men and 195 women from various age groups. In the first method, an FES structure that determines the severity of RA disease has been established from blood count using the laboratory test results of CRP, ESR, RF, and ANA. The FES result that determines RA disease severity, the Anti-CCP level that is used to distinguish RA disease, and the patient’s medical history were used to design the Decision Support System (DSS) that diagnoses RA disease. The DSS is web-based and publicly accessible. In the second method, RA disease was diagnosed using kNN, SVM, LR, DT, NB, and MLP algorithms, which are widely used in machine learning. To examine the effect of the patient’s history on RA disease diagnosis, two different models were used in machine learning techniques, one with and one without the patient’s history. The results of the fuzzy-based DSS were also compared with the diagnoses made by the specialist and the diagnoses made according to the 2010 ACR / EULAR RA classification criteria. The performed DSS has achieved a diagnostic success rate of 94.05% on 286 patients. In the study of machine learning techniques, the highest success rate was achieved with the LR model. While the success rate of the model was 91.25 % with only blood count data, the success rate was 97.90% with the addition of the patient’s history. In addition to the high success rate, the results show that the patient’s history is important in diagnosing RA disease.

Immune hallmarks of rheumatoid arthritis management: A brief review

The purpose of this review was to examine current evidence on immunomodulation mediated by conventional drugs and the use of novel biological agents for the treatment of rheumatoid arthritis (RA). Currently, treatment is focused on maximizing quality of life through sustained clinical remission and/or attenuating disease activity. To do so, disease-modifying antirheumatic drugs, especially methotrexate, are used alone or in combination with other drugs, including leflunomide, biological disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs). The most recent strategies modulate the immune response of the individual RA patient using tsDMARDs such as JAK inhibitors and bDMARDs such as ig-CTLA-4, anti- IL6R, anti-TNF-α and anti-CD20. To better understand current immunopharmacological interventions, we also looked at documented mechanisms of RA-mediated immunomodulation, highlighting perspectives potentially boosting RA treatment.

Increased frequency of TIGIT+ CD4 T Cell subset in autoantibody-positive first-degree relatives of patients with rheumatoid arthritis

Background

Despite immune cell dysregulation being an important event preceding the onset of rheumatoid arthritis (RA), the phenotype of T and B cells in preclinical RA is less understood. The aim of this study was to characterize T and B cell populations in RA patients and their autoantibody (aAb) negative and positive first-degree relatives (FDR).

Methods

Cryopreserved peripheral blood mononuclear cells (PBMCs) collected at scheduled visits from aAb-(n=25), and aAb+ FDR (n=10) and RA patients (n=13) were thawed and stained using optimized antibody cocktails as per a specific 13-color T or B cell panel. Immunophenotyping was performed using a Cytoflex LX (Beckman-Coulter) flow cytometer and FlowJo software was used for analyzing the frequency of immune cell populations.

Results

Multicolor flow cytometry experiments identified an increased TIGIT expression in circulating lymphocytes of aAb+ FDR and RA patients, relative to aAb- FDR (P<0.01). These TIGIT⁺ T cells exhibited a memory phenotype and expressed high levels of PD-1, ICOS, HLA-DR, CXCR3 and CXCR5. Moreover, increased TIGIT⁺ CD4 T cell frequency correlated with the frequency of PD-1⁺ CD4 T cells (r = 0.4705: P = 0.0043) and circulating levels of ACPA and RF. We also identified a decreased frequency of CD27+IgD- switched memory B cells in RA patients (P < 0.01), while increased frequency of TIGIT+ CD4 T cells in FDR correlated with the frequency of PD1⁺PTEN⁺ B cells (r = 0.6838, P = 0.0004) and autoantibody positivity (P = 0.01).

Conclusion

We demonstrate TIGIT as a distinct CD4 T cell marker for differentiating aAb- FDR from aAb+FDR and might play a critical role in regulating T and B cell crosstalk in preclinical RA.

Pros and cons of causative association between periodontitis and rheumatoid arthritis

Research in recent decades has brought significant advancements in understanding of the molecular basis of the etiology of autoimmune diseases, including rheumatoid arthritis, a common systemic disease in which an inappropriate or inadequate immune response to environmental challenges leads to joint destruction. Recent studies have indicated that the classical viewpoint of the immunological processes underpinning the pathobiology of rheumatoid arthritis is restricted and needs to be expanded to include a more holistic and interdisciplinary approach incorporating bacteria-induced inflammatory reactions as an important pathway in rheumatoid arthritis etiology. Here, we discuss in detail data showing the clinical and molecular association of rheumatoid arthritis development with periodontal diseases. We also describe the unique role of periopathogens, which have been proposed to be crucial in the initiation and progression of this autoimmune pathological disorder.

Marine-Derived Biologically Active Compounds for the Potential Treatment of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease with a prevalence rate of up to 1% and is significantly considered a common worldwide public health concern. Commercially, several traditional formulations are available to treat RA to some extent. However, these synthetic compounds exert toxicity and considerable side effects even at lower therapeutic concentrations. Considering the above-mentioned critiques, research is underway around the world in finding and exploiting potential alternatives. For instance, marine-derived biologically active compounds have gained much interest and are thus being extensively utilized to confront the confines of in practice counterparts, which have become ineffective for 21st-century medical settings. The utilization of naturally available bioactive compounds and their derivatives can minimize these synthetic compounds' problems to treat RA. Several marine-derived compounds exhibit anti-inflammatory and antioxidant properties and can be effectively used for therapeutic purposes against RA. The results of several studies ensured that the extraction of biologically active compounds from marine sources could provide a new and safe source for drug development against RA. Finally, current challenges, gaps, and future perspectives have been included in this review.

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

Rheumatoid arthritis (RA) is a multifactorial, inflammatory and progressive autoimmune disease that affects approximately 1% of the population worldwide. RA primarily involves the joints and causes local inflammation and cartilage destruction. Immediate and effective therapies are crucial to control inflammation and prevent deterioration, functional disability and unfavourable progression in RA patients. Thus, early diagnosis is critical to prevent joint damage and physical disability, increasing the chance of achieving remission. A large number of biomarkers have been investigated in RA, although only a few have made it through the discovery and validation phases and reached the clinic. The single biomarker approach mostly used in clinical laboratories is not sufficiently accurate due to its low sensitivity and specificity. Multiplex immunoassays could provide a more complete picture of the disease and the pathways involved. In this review, we discuss the latest proposed protein biomarkers and the advantages of using protein panels for the clinical management of RA. Simultaneous analysis of multiple proteins could yield biomarker signatures of RA subtypes to enable patients to benefit from personalized medicine.

Prevention and adherence in Rheumatic and Musculoskeletal disease

Rheumatic and Musculoskeletal Diseases (RMDs) are chronic conditions that affect a substantial number of people. RMDs are significantly related to co-morbidity. Therefore, focusing on prevention in RMDs is of importance to promote and maintain health. Prevention includes primary-, secondary-, tertiary-, and clinical prevention. Primary prevention aims to prevent the onset of disease before the disease process begins, secondary prevention includes detecting and reducing disease and risk factors at the earliest possible point, and tertiary prevention aims to limit the influence of a recognized or verified disease and to address or reduce further development or worsening of the disease, including physical and psychosocial disability. Clinical prevention attempts to integrate prevention into the disease management to limit disease progression and prevent complications and relapse. This chapter will focus on the evidence for prevention and highlight how innovations and trends can contribute by using digital technologies as an example.

Immunometabolism in the development of rheumatoid arthritis

In rheumatoid arthritis (RA), breakdown of self-tolerance and onset of clinical disease are separated in time and space, supporting a multi-hit model in which emergence of autoreactive T cells is a pinnacle pathogenic event. Determining factors in T cell differentiation and survival include antigen recognition, but also the metabolic machinery that provides energy and biosynthetic molecules for cell building. Studies in patients with RA have yielded a disease-specific metabolic signature, which enables naive CD4 T cells to differentiate into pro-inflammatory helper T cells that are prone to invade into tissue and elicit inflammation through immunogenic cell death. A typifying property of RA CD4 T cells is the shunting of glucose away from glycolytic breakdown and mitochondrial processing toward the pentose phosphate pathway, favoring anabolic over catabolic reactions. Key defects have been localized to the mitochondria and the lysosome; including instability of mitochondrial DNA due to the lack of the DNA repair nuclease MRE11A and inefficient lysosomal tethering of AMPK due to deficiency of N-myristoyltransferase 1 (NMT1). The molecular taxonomy of the metabolically reprogrammed RA T cells includes glycolytic enzymes (glucose-6-phosphate dehydrogenase, phosphofructokinase), DNA repair molecules (MRE11A, ATM), regulators of protein trafficking (NMT1), and the membrane adapter protein TSK5. As the mechanisms determining abnormal T cell behavior in RA are unraveled, opportunities will emerge to interject autoimmune T cells by targeting their metabolic checkpoints.