This is among the first prospective longitudinal studies to identify predictors of infection in RA by assessing the function of the innate and adaptive immune systems. We observed that the production of seven cytokines by PBMC in response to various stimuli was associated with the 6-month risk of infection in patients with RA. A multi-cytokine score summarizing this data was found to be predictive of incident infection at six months. Importantly, this score provided information above and beyond the baseline markers of disease activity, severity, and use of RA drug therapies. The main contribution of this study is that immune function measures could be useful in the identification of patients at increased short-term risk of infection.
While at the population level it is known that patients with RA have increased risk of infection compared to the general population, it is unknown how to translate this risk to an individual patient [1
]. This can be explained in part by our current inattention to the functional aspects of the immune system likely to be important in host defense against infection. The pathogenesis of RA involves multiple derangements of the immune system and is not captured by a single cell type or cytokine. An example of the diversity of these alterations is the polarized immune response of IFN-γ producing T cells in RA; inflamed synovium has increased IFN-γ levels while the peripheral blood has reduced IFN-γ levels [15
]. The impaired ability of RA lymphocytes to respond to novel antigens is one mechanism thought to derail host defense [17
]. The diversity of stimulus-cytokine combinations incorporated in our approach reflects the broad involvement of innate and adaptive immunity in the pathogenesis of RA.
Previous studies have evaluated cytokine response profiles in other patient populations. Consistent with the findings of this study, TNF-α was positively correlated with infection risk [18
]. Conflicting associations of IL-10 with infection risk have been reported [19
]. We showed an association between increased IFNγ and increased infection risk. This finding contrasts earlier reports that higher IFN-γ is associated with reduced numbers of infections [21
], possibly reflecting differences in the stimulation technique or the study populations. These contradictory results highlight the necessity of evaluating multiple, rather than just single cytokines, which may provide the most accurate assessment of infection risk. The overlap of cytokine roles is accounted for in statistical analysis and in previous studies has used different techniques [24
]. Our study utilized a predictive score in attempt to summarize the effects of multiple cytokine pathways and demonstrate the information gained above and beyond usual clinical assessments.
This study has limitations. The number of infections was small, limiting our statistical power to identify all potential immunological predictors of infection. Although the infection types were heterogeneous in the pathogenic microorganisms as well as organ system involvement, we anticipated that common immunological characteristics could be identified underlying the risk of many infections. A limitation of this study was that infection data was identified by medical record review. Treatment with conventional and biologic DMARDs was examined as a key confounder, but the short-term observational study design and small sample size precluded full understanding of treatment effects on infections. Because not all eligible subjects in our cohort participated, there is the possibility that patients with more severe disease —who could be at higher risk of infections—were not included, potentially biasing our results [9
]. However, the inclusion of such individuals with severe illness would potentially have resulted in even more robust differences between the groups with and without infections during follow-up.
Despite the limitations, there are several important strengths that contribute to the confidence of this approach. The unique capabilities of the Rochester Epidemiology Project enabled us to prospectively ascertain incident infections in a population-based cohort design. While minor infections that did not require medical attention were not captured in this study, serious infections were likely ascertained in completion. This underscores the benefits of the Rochester Epidemiology Project, which facilitates access to all data for emergency room visits, hospitalizations, and outpatient appointments [7
]. The innovation of this study is supported by the assessment of dynamic immune function with cell-based stimulated cytokine assays as opposed to serum biomarkers. This study was one attempt to identify changes in immune function that might predispose certain patients with RA to infection. For this to be clinically useful the technique would need to be easily reproducible in clinical laboratories, so we are taking steps to enhance the standardization and reproducibility of the developed assays. We have reported data that suggest this cell-based approach offers potentially lower variability than comparable approaches using serum samples [6
In summary, we report the findings of a pilot study that represents one step toward a risk assessment tool for predicting infections that could be useful in personalized management strategies for RA. This would have implications for the selection of therapies, monitoring for early signs and symptoms of infection, and potentially for antimicrobial prophylaxis. It is foreseeable that the ability to predict and prevent infections could markedly reduce morbidity and mortality in individuals with RA. The new findings of this study also should inform future research into the mechanisms underlying aberrant immune function that might contribute to the high burden of infections in patients with RA.
We studied immune response profiles as predictors of infection in rheumatoid arthritis patients.
Profiles were defined by measurement of cytokine production from stimulated blood leukocytes.
A 7-cytokine profile was predictive of incident infection at 6-months of follow-up.
This profile conveyed new information on infection risk beyond standard assessments.