Introduction
(Article introduction authored by Conquest Editorial Team)
Seropositive rheumatoid arthritis (RA) arises from a complex interplay of genetic and environmental factors, with most patients having no family history of RA. At diagnosis, patients typically exhibit joint inflammation and autoantibodies like ACPA and rheumatoid factor (RF). Retrospective studies show that anti-CCP and other inflammatory markers can precede RA symptoms by several years.
Prospective Risk-RA cohort studies confirm a risk phase marked by systemic autoimmunity, even without visible joint inflammation, with varying risk estimates for developing arthritis. At Karolinska Institutet, we investigated factors influencing RA risk to better identify individuals at high or low risk for developing arthritis.
Methods
Karolinska Risk-RA prospective research programme and cohort
The Karolinska Risk-RA is a prospective research program launched in 2014, enrolling individuals from three rheumatology clinics in Stockholm, Sweden. Participants must have musculoskeletal complaints with suspected rheumatic disease, be anti-CCP2 positive, and show no signs of arthritis on ultrasound. The program includes at least three annual follow-ups or until clinical arthritis develops, with additional support available if symptoms worsen.
The study, involving 267 individuals enrolled between 2014 and 2019, follows participants for a median of 49 months and adheres to ethical guidelines, with all participants providing informed consent.
Musculoskeletal Ultrasound Assessment
Hands, feet, and other symptomatic joints were assessed using musculoskeletal ultrasound (MSUS) based on EULAR-OMERACT criteria for synovitis. Participants with moderate synovial hypertrophy were excluded. Baseline data from those with minimal synovial hypertrophy, tenosynovitis, and bursitis were collected and analyzed.
Analysis of Autoantibodies, Genetic Risk Alleles, and Inflammation-Associated Proteins
Baseline serum samples were used to analyze nine ACPA reactivities and HLA-DRB1 shared epitope (SE) genotyping. A panel of 92 inflammation-associated serum proteins was also analyzed in both the Risk-RA cohort and a matched healthy control group. Data were normalized for analysis.
Statistical Analysis
Baseline data were normalized, and RF and anti-CCP2 levels were categorized. Survival time (arthritis-free) was analyzed using Kaplan-Meier analysis.
Significant predictors of arthritis progression were identified through Cox regression and selected for the final model, which was validated and tested for interaction effects. Statistical analyses were performed using SAS and R Studio, with significance set at 0.05. The TRIPOD checklist was followed in the report preparation.
Results
Baseline Characteristics of the Study Cohort
The study included 267 participants, mostly female (79%), with a mean age of 48 years. Median symptom duration before inclusion was 21 months. 58% had ever smoked, and 27% had a first-degree relative with RA. All participants were anti-CCP2 positive, with 33% also RF positive.
Clinical Characteristics at Baseline and Association with Arthritis Onset
Arthritis developed in 38% of participants after a median of 14 months. RF positivity and the presence of HLA-SE alleles were significantly associated with arthritis progression, while smoking showed no significant association. (Fig. 1)
Anti-Citrullinated Protein Antibodies at Baseline and Association with Arthritis Onset
Higher anti-CCP levels and increased ACPA reactivities were linked to arthritis progression.
The presence of one or more ACPA reactivities was a strong predictor, but combining it with RF positivity did not improve predictive accuracy. (Fig. 2)
Minimal Ultrasound Changes at Baseline and Association with Arthritis Onset
Ultrasound-detected tenosynovitis was significantly more common in individuals who developed arthritis. 84% of those with tenosynovitis progressed to arthritis, compared to 34% without it.
Inflammation-Associated Proteins at Baseline and Association with Arthritis Onset
Significantly different levels of 10 proteins (IL-6, TNF-R superfamily member 9, IL-17C, IL-10, CXCL9, IL-15 receptor α [IL-15Rα], CXCL6, leukaemia inhibitory factor receptor [LIF-R], delta and Notch-like epidermal growth factor-related receptor [DNER] and hepatocyte growth factor [HGF]) between those developing arthritis and individuals not developing arthritis.
Significant Independent Predictors in a Model for Arthritis Progression
Independent predictors of arthritis progression included ACPA reactivity, ultrasound-detected tenosynovitis, and levels of IL-6 and IL-15Rα. The prediction model had an AUC of 0.82, and most predictors remained significant after Bonferroni adjustment. (Fig. 3)
Discussion
The aim of this study was to identify factors linked to arthritis progression in anti-CCP-positive individuals with musculoskeletal complaints but no joint inflammation at the start.
Conducted within the Karolinska Risk-RA cohort, the study followed 267 individuals for at least three years, during which 38% developed arthritis.
Key findings include a higher presence of ACPA reactivities in those who progressed to arthritis (96% vs. 62%), with at least one ACPA reactivity being a strong predictor of arthritis.
Inflammation-associated proteins, particularly IL-6 and IL-15Rα, showed differences between progressors and non-progressors. Ultrasound-detected tenosynovitis strongly predicted arthritis development, with 89% of these individuals progressing to arthritis.
The study also found that HLA-SE alleles were associated with arthritis progression, while smoking showed a non-significant trend.
The predictive model identified factors like ACPA reactivity, tenosynovitis, IL-6, and IL-15Rα, though further validation is needed for clinical use. Limitations include the absence of bone erosion analyses and cell phenotyping.
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