| Literature DB >> 30347791 |
Aileen Y Chang1, Sarah Tritsch2, St Patrick Reid3, Karen Martins4, Liliana Encinales5, Nelly Pacheco6, Richard L Amdur7, Alexandra Porras-Ramirez8, Alejandro Rico-Mendoza9, Guangzhao Li10, Jin Peng11, Gary S Firestein12, Gary L Simon13, Jeff M Bethony14.
Abstract
The cytokine profile during acute chikungunya infection that predicts future chronic arthritis has not yet been investigated. We conducted a nested case-control study comparing serum cytokine concentrations during acute chikungunya infection in cases (n = 121) that reported the presence of chronic joint pain versus age- and gender-matched controls (n = 121) who reported recovery at 20 months post infection. We observed that a robust cytokine response during acute infection was correlated with a decreased incidence of chronic joint pain and that low TNFα, IL-13, IL-2, and IL-4 during acute infection was predictive of chronic joint pain. These data suggest that a robust cytokine response is necessary for viral clearance and cytokines that are related to immune tolerance during acute infection may be protective for chronic arthritis pathogenesis.Entities:
Keywords: alphavirus; arthritis; chikungunya; cytokine
Year: 2018 PMID: 30347791 PMCID: PMC6313749 DOI: 10.3390/diseases6040095
Source DB: PubMed Journal: Diseases ISSN: 2079-9721
Patient characteristics 20 months post chikungunya infection.
| Patient Characteristic | With Joint Pain | Without Joint Pain |
|---|---|---|
| Age, | 49 ± 17 | 48 ± 17 |
| Female, | 89% | 89% |
Figure 1Association of cytokine quintiles with joint pain.
The final logistic regression model for cytokines.
| Cytokine Quintile | Adjusted OR | 95% Wald Confidence Limits |
| Parameter Estimate (se) | |
|---|---|---|---|---|---|
| TNFα | 0.650 | 0.487 | 0.866 | 0.0033 | −0.43 (0.15) |
| IL-13 | 0.799 | 0.567 | 1.125 | 0.1984 | −0.22 (0.17) |
| IL-2 | 0.573 | 0.401 | 0.819 | 0.0023 | −0.56 (0.18) |
| IL-4 | 0.504 | 0.372 | 0.683 | <0.0001 | −0.68 (0.15) |
| Intercept | <0.0001 | 3.66 | |||
Associations with joint pain. The equation to calculate the probability of having joint pain was risk = 3.66, –0.43(TNFα), –0.22(IL-13), –0.56(IL-2), –0.68(IL-4), where the quintile (scored 0–4) is used for each cytokine. Probability = exp(risk)/(1 + exp(risk)). OR, odds ratio.
Figure 2Calibration of the logistic regression model’s risk scores versus incidence of joint pain. There is very strong correspondence between the predicted probability and the observed incidence of joint pain across risk quintiles.