Supporting findings in prior studies, in this cohort of military patients with RA we have identified that autoantibodies, circulating cytokines/chemokines and CRP are elevated pre-clinical RA, and that autoantibody positivity is highly specific for future seropositive RA.(10
) We have additionally shown that there is an increased duration of pre-clinical biomarker positivity in individuals with older age-at-diagnosis, and we have developed a regression model that utilizes cytokine/chemokine counts and age-at-diagnosis to estimate the time from pre-clinical sample to the time of RA diagnosis. Importantly, since this model was developed using pre-diagnosis case samples positive for highly RA-specific autoantibodies (anti-CCP and/or 2 or more RF isotypes), in prospective study of individuals without symptomatic RA but who are positive for these autoantibodies, application of this model will allow for prediction of age-related timing of onset of symptomatic disease as well as identification of subjects who may be ideal candidates for prevention trials due to their likely imminent onset of symptomatic disease. Of note, while this RA-specific autoantibody profile is most likely to be positive within 5-years prior-to-diagnosis, it may be present up to 10 years pre-diagnosis (). As such, cytokine/chemokine analyses in these high-risk subjects allows for finer specification of time-to-diagnosis than autoantibody testing alone. Also, while this model used age-at-diagnosis (by decade) to predict the time-to-diagnosis in RA cases, it will apply to estimate the timing of onset of future symptomatic RA in asymptomatic subjects followed prospectively with current age replacing age-at-diagnosis, as the 10-year intervals allow for adequate bracketing of subjects into age groups where the biologic and other factors influencing duration of pre-clinical biomarker positivity are appropriately accounted for.
The relationship between age and the increased duration of pre-RA diagnosis biomarker positivity identified here and in prior studies (13
) may be due to differing genetic and environmental influences on disease development in younger versus older cases, or may be due to factors related to senescence of the effecter mechanisms of the immune system in older subjects.(13
) Non-biologic factors may also influence the duration of pre-diagnosis autoimmunity and inflammation in military RA subjects. For example, older military subjects may be less likely to present to health-care with medical complaints to protect their work or retirement status, or they may be more likely to be in engaged in sedentary tasks where joint symptoms may be less debilitating, although herein there was no difference in time of onset of pre-diagnosis symptoms by age-at-diagnosis grouping. Furthermore, younger military subjects may appear comparatively to have a shorter pre-clinical duration of biomarker positivity because they have a smaller temporal span of pre-clinical samples available than older subjects. However, as the mean duration from first pre-clinical sample to diagnosis was not significantly different between age groups (by decade) used in the prediction model, this was likely not a significant issue here. Also, there may be an unidentifiable duration of pre-clinical biomarker positivity if subjects’ earliest available pre-diagnosis samples were biomarker positive – we investigated this issue and found that there was no significant difference between age-at-diagnosis groups (<40, ≥40) in the number of initial pre-clinical samples that were positive for a biomarker, with the exception that GM-CSF was positive in the initial sample in a higher proportion of cases <40 at diagnosis. And, for all autoantibodies and IL-1α, IL-6, IL-15, IP-10, MCP-1 and CRP, there was a non-statistically significant trend for the ≥40 group to have an increased
proportion of first-sample biomarker positivity, suggesting that the longer duration of biomarker positivity pre-RA diagnosis in older cases may actually be underestimated. In sum, age-related duration of pre-RA diagnosis biomarker positivity in this population is likely a real phenomenon, important for understanding the evolution of RA as well as developing models to predict the timing of onset of future disease.
The elevations of the cytokines/chemokines assessed here likely reflect various underlying processes including: general inflammation (IL-1α and β, TNFα, IL-6, CRP), Th1-related processes (IL-12), Th2-related processes (eotaxin), T cell regulation (IL-10, IL-15), or cellular signaling/growth factors (FGF-2, Flt3 Ligand, GM-CSF). Due to limitations in the size of our sample set and number/type of cytokines/chemokines assessed here, inferences regarding the biology and timing of specific immune responses in pre-clinical RA are likewise limited; however, there are several findings of particular interest. Firstly, IL-6 elevation in a subset of subjects prior to anti-CCP positivity is of interest as this cytokine is associated with Th17 cell development – cells thought to be important in RA pathogenesis (29
). IL-17 and IL-23 are also important factors in this pathway, and although we did not assess these cytokines, Kokkonen et al demonstrated pre-RA elevations of IL-17 (16
), and their findings coupled with ours suggest that the Th17 pathway is important in pre-clinical RA. Secondly, IP-10 elevation prior to anti-CCP positivity is of interest in terms of disease pathogenesis, as this chemokine is an IFNγ-induced protein promoting chemoattraction for macrophages, dendritic cells and T cells, as well as in terms of therapeutics, as blockade of IP-10 has reduced the severity of collagen-induced arthritis in mice.(30
) Thirdly, the increased proportion of IL-10 positivity in cases that were <40 at diagnosis is of also of interest, with the T cell regulatory aspects of this cytokine perhaps playing a role in age-of-onset of disease.(31
) Fourthly, the pre-clinical fluctuations in positivity of individual cytokines/chemokines likely reflects that inflammation, due to evolving immune reactions and/or level of tissue injury, builds and eventually reaches a threshold state when an individual transitions from asymptomatic autoimmunity/inflammation to clinically-apparent disease (although the exact anatomic site(s) of these early inflammatory/autoimmune processes in pre-clinical RA are unknown). Furthermore, the loss of significant differences in pre-clinical positivity for a subset of biomarkers when samples from 0-6 months prior-to-diagnosis were removed from analyses highlights that the immediate pre-diagnosis period is a time of increasing systemic inflammation, when early RA symptoms may be present, although statistical power issues due to loss of samples, and possible inaccuracies in patient recall of symptom onset may be factors here.(32
) Of note, because of overlap between increasing cytokines/chemokines and symptoms during this immediate pre-diagnosis period, these military cases may be similar to the Dutch patients described by Bos, Verweij and colleagues who have autoantibody positivity and arthralgia as well as increased gene expression for cytokines/chemokines but no clinical synovitis who may later progress to definable RA.(33
) Finally, while CRP levels did not predict the time of onset of RA, the highest proportion of cases with CRP positivity was <1 year pre-diagnosis, suggesting that CRP elevation in an at-risk individual may indicate impending onset of symptomatic RA. All of these latter issues will need to be explored prospectively in additional sample sets, where shortcomings of ascertainment of pre-diagnosis symptoms in retrospectively assembled cohorts can be addressed.
There are other caveats to our findings. There are not standardized cut-offs for positivity for cytokines/chemokines using the methodology presented here (Luminex), and our cut-offs for positivity may not be applicable to other populations. Also, because our cut-off levels were established using post-RA diagnosis samples, treatment factors may influence these levels, although it is likely that these levels were higher than may be expected in the pre-clinical period, leading to conservative estimates of pre-diagnosis cytokine/chemokine positivity. Notably, there were differences in the diagnostic accuracy of cytokines/chemokines for future RA in our study compared to that by Kokkonen et al -- on average we found ~42% sensitivity and ~74% specificity of the individual 14 cytokines/chemokines for future RA compared to an average of ~17% sensitivity and a set ~95% specificity of any of the 15 cytokines reported in the study by Kokkonen and colleagues.(16
) These differences may be due to RA case ascertainment, methodologies of biomarker testing, and methodologies to determine cut-off values and sensitivity/specificity for the biomarkers for future RA. Additionally, compared to testing a single pre-diagnosis sample, our testing of multiple pre-diagnosis samples per individual likely allows for greater sensitivity to detect elevations, especially given the fluctuations of cytokines/chemokines positivity demonstrated here. In the future, standardization of cytokine/chemokine assessment and cut-offs for positive will overcome many of these issues. There may also be non-RA related factors affecting cytokine/chemokine, levels including methodologies of sample collection and sample storage.(35
) And, while military subjects were to have blood sampled for the DoDSR at defined times, it is possible that they preferentially had sampling during times of illness. However, by using samples from carefully-matched military controls for comparisons, we believe that such effects are accounted for. Regarding the wider applicability of these findings, this military cohort may not represent typical RA in the general population – it was predominately male, and the mean age of onset of disease was earlier than seen in the general population. There also may be biases in terms of which military subjects are referred for rheumatology evaluation, and these cases may represent more severe RA, evidenced by a relatively high proportion of seropositive disease (~88%). These concerns, as well as the role of genetic and environmental factors (such as smoking) in prediction of RA, need to be addressed by application of this model in additional populations.