Protein Changes Mark Rheumatoid Arthritis Years Before Symptoms

Researchers have identified specific inflammatory proteins in the blood that change years before the clinical symptoms of rheumatoid arthritis appear. The study, published in Arthritis Research & Therapy, analyzed plasma samples from individuals who later developed the disease, comparing them with healthy controls and patients with early-stage rheumatoid arthritis. The findings suggest that biological differences between seropositive and seronegative forms of the disease are detectable during the pre-symptomatic phase, long before joint pain or swelling becomes evident.

The investigation focused on the temporal dynamics of inflammation-related proteins in relation to seroconversion, the process by which individuals develop autoantibodies such as rheumatoid factor or anti-citrullinated protein antibodies. Autoimmune processes in rheumatoid arthritis are known to begin years before clinical onset, but the specific protein changes that accompany the development of these antibodies have not been fully characterized. By examining these changes, the study aimed to clarify how immune dysregulation progresses in the years leading up to symptom onset.

The study utilized a case-control design with plasma samples from the Medical Biobank of Northern Sweden. The cohort included 419 individuals who were pre-symptomatic at the time of sampling but later developed rheumatoid arthritis. These samples were compared with 49 healthy population controls and 68 patients with early rheumatoid arthritis at the time of diagnosis. The median time from sample collection to symptom onset in the pre-symptomatic group was 4.35 years, providing a window into the biological changes occurring in the years preceding clinical disease.

Researchers analyzed the samples using a proximity extension assay to measure 92 inflammation-related proteins. After quality control procedures, 77 proteins were retained for downstream analysis. The study also measured levels of anti-CCP2 antibodies and rheumatoid factor to determine autoantibody status. Statistical analyses included logistic regression, generalized additive models, and network enrichment analysis to identify differentially expressed proteins and enriched biological pathways.

Four proteins—MMP10, IL6, CCL19, and IL10RB—showed higher concentrations in pre-symptomatic individuals compared to healthy controls. However, these differences did not survive correction for multiple testing, a limitation the authors noted due to the modest size of the control group. In contrast, twelve proteins were significantly associated with seropositivity in the pre-symptomatic phase. Network enrichment analysis of these proteins revealed associations with pathways related to the complement system and cytokine activity, suggesting a role for innate immune mechanisms in the early stages of the disease.

The study further stratified pre-symptomatic individuals into subgroups based on their autoantibody status over time. These groups included early seroconverters, who were seronegative in the earliest samples but seropositive closer to symptom onset; late seroconverters, who were seronegative in pre-symptomatic samples but seropositive at diagnosis; and stable seronegative individuals, who remained seronegative throughout. This stratification allowed researchers to examine how protein levels changed over time in relation to the timing of autoantibody development.

Three proteins—CXCL10, CCL7, and CDCP1—were consistently associated with seroconversion across multiple statistical models. In individuals who seroconverted, these proteins showed increasing trends as symptom onset approached, a pattern not observed in individuals who remained seronegative. CXCL10 was lower at early pre-symptomatic time points and rose progressively, while CCL7 rose mainly from around two years before symptom onset in late seroconverters. CDCP1 has been linked to IL6 production and T-cell adhesion in previous studies.

The proteins associated with early seroconversion were linked to T-cell activity, consistent with a T-cell-driven process in this phase. In contrast, many proteins associated with late seroconversion were related to bone remodelling, mineral metabolism, and collagen degradation. This distinction suggests that the biological pathways involved in seroconversion may differ depending on the timing of autoantibody development. The authors noted that these findings are hypothesis-generating and require validation in independent cohorts.

Generalized additive models indicated that seropositive and seronegative trajectories began to diverge approximately five years before symptom onset. The quartile analysis similarly showed the most pronounced differences from controls in the final five years before onset. This timing is consistent with the hypothesis that autoimmune escalation intensifies in the window leading up to clinical disease. The study highlights the importance of the pre-symptomatic phase in understanding the pathophysiological mechanisms driving rheumatoid arthritis.

The authors acknowledged several limitations, including the self-reported nature of symptom onset, which may introduce recall bias. The subgroups with repeated pre-symptomatic sampling and the control group were relatively small, limiting statistical power. Additionally, the study was restricted to a predefined antibody-dependent protein panel available on the Olink platform, and results were not validated using an orthogonal method. Despite these limitations, the cohort is among the largest available with sample collection predating symptom onset, providing valuable insights into the early stages of rheumatoid arthritis.

The findings support the notion that seropositive and seronegative rheumatoid arthritis represent biologically distinct entities from the earliest stages of pathogenesis. Proteomic alterations are detectable years before onset and are linked to autoantibody development, with immune dysregulation evident from approximately five years before symptoms appear.

The study drew on plasma samples from the Medical Biobank of Northern Sweden, a resource that has enabled researchers to examine biological markers in individuals before they develop clinical disease. The biobank’s collection strategy, which included samples gathered opportunistically during mammography screening and other population-based studies, allowed for a large cohort of pre-symptomatic individuals to be analyzed. The median time from sample collection to symptom onset was 4.35 years, meaning that many of the biological changes observed were occurring well before any clinical signs of joint inflammation were present.

To ensure that the observed differences in protein levels were not simply due to the timing of sample collection, the researchers compared the time from first reported symptoms to the sampling date between early and late seroconverters. The mean time to symptom onset did not differ significantly between these two groups, with early seroconverters sampled approximately 6.25 years before onset and late seroconverters sampled approximately 5.9 years before onset. This comparison suggests that the distinct protein profiles observed in these subgroups reflect true biological differences in the timing of autoantibody development, rather than an artifact of when the samples were taken.

The statistical analysis employed in the study was designed to handle the complexity of repeated measurements and the potential for multiple comparisons. Generalized linear mixed models were used to account for the non-independence of repeated samples from the same individual, treating each person as a random effect while adjusting for time to symptom onset. This approach allowed the researchers to identify proteins that were consistently associated with autoantibody positivity across multiple sampling occasions. Additionally, the Benjamini-Hochberg procedure was used to correct for multiple comparisons, controlling the false discovery rate to ensure that the identified associations were robust. Two-sided p-values of 0.05 or less were considered statistically significant, while adjusted p-values below 0.05 were used to control the false discovery rate.

Network enrichment analysis provided further insight into the biological pathways involved in seroconversion. By integrating protein-protein interaction data from the STRING and Pathway Commons databases with functional gene sets from Reactome and BioCarta, the researchers were able to identify pathways that were significantly enriched among the proteins associated with seropositivity. This analysis revealed that the complement system and chemokine receptor activity were particularly prominent. The involvement of the complement system in the pre-symptomatic phase is consistent with previous reports of systemic complement activation in rheumatoid arthritis, suggesting that innate immune mechanisms may play a role in the earliest stages of the disease. The enrichment of chemokine receptor pathways further supports the idea that immune cell trafficking and recruitment are key processes in the development of seropositive rheumatoid arthritis.

The study also examined the relationship between protein levels and specific clinical and genetic factors. No significant differences were observed between early and late seroconverters regarding history of smoking or HLA-DRB1 shared epitope carrier status. This finding suggests that the distinct protein profiles observed in these subgroups are not simply driven by differences in these well-known risk factors for rheumatoid arthritis. However, the study did note that the subgroups with repeated pre-symptomatic sampling were predominantly women, which may influence the interpretation of the results. The authors acknowledged that the modest size of the control group and the subgroups with repeated sampling limited the statistical power of the study, particularly for detecting smaller differences in protein levels.

The use of the Olink proximity extension assay allowed for the simultaneous measurement of 92 inflammation-related proteins in a small volume of plasma. However, the authors noted that the study was restricted to a predefined panel of proteins, and that results were not validated using an orthogonal method.

The findings of this study contribute to a growing body of evidence that seropositive and seronegative rheumatoid arthritis are biologically distinct entities from the earliest stages of pathogenesis. The identification of specific proteins that are associated with seroconversion and that show progressive changes over time provides new insights into the mechanisms driving the development of the disease.

Subject of Research: Pre-symptomatic inflammatory protein dynamics and seroconversion in rheumatoid arthritis

Article Title: Temporal dynamics of inflammatory proteins in the pre-symptomatic phase of rheumatoid arthritis related to seroconversion

Article References: Ahlsved, A., Lundquist, A., Lejon, K., Rantapää-Dahlqvist, S., & Brink, M. (2026). Temporal dynamics of inflammatory proteins in the pre-symptomatic phase of rheumatoid arthritis related to seroconversion. Arthritis Research & Therapy, 28(1), Article 178. https://doi.org/10.1186/s13075-026-03917-4

Image Credits: AI Generated

DOI: 10.1186/s13075-026-03917-4

Keywords: rheumatoid arthritis, pre-symptomatic phase, seroconversion, inflammatory proteins, autoantibodies, biomarkers, immune dysregulation, complement system, T-cell activity, proximity extension assay, Temporal, dynamics