Evaluation of TH17 and TH1 Immune Response Profile in Patients After Renal Transplant

IL-17A - A regulator in acute inflammation: Insights from in vitro, in vivo and in silico studies

Acute inflammation following sterile injury is both inevitable and necessary to restore homeostasis and promote tissue repair. However, when excessive, inflammation can jeopardize the viability of organs and cause detrimental systemic effects. Identifying key-regulators of the immune cascade induced by surgery is vital to attenuating excessive inflammation and its subsequent effects. In this review, we describe the emerging role of IL-17A as a key-regulator in acute inflammation. The role of IL-17A in chronic disease states, such as rheumatoid arthritis, psoriasis and cancer has been well documented, but its significance in acute inflammation following surgery, sepsis, or traumatic injury has not been well studied. We aim to highlight the role of IL-17A in acute inflammation caused by trauma, liver ischemia, and organ transplantation, as well as in post-operative surgical infections. Further investigation of the roles of this cytokine in acute inflammation may stimulate novel therapies or diagnostic modalities.

In vitro intracellular IFNγ, IL-17 and IL-10 producing T cells correlates with the occurrence of post-transplant opportunistic infection in liver and kidney recipients

AIM

To validate intracellular cytokine production functional assay as means of cell-mediated immunity monitoring of post-transplant patients with opportunistic infection (OI).

METHODS

Intracellular cytokine-producing CD4⁺ and CD8⁺ T-cell monitoring was carried out in 30 liver transplant (LTr) and 31 kidney transplant (KTr) recipients from 2010 to 2012. Patients were assessed in our Department of Immunology at the Clinical University ‘Hospital Virgen de la Arrixaca-IMIB’ in Murcia, Spain for one year following transplantation. FACS Canto II flow cytometer was employed to quantify the intracellular production of IL-17, IFNγ and IL-10 cytokines on stimulated CD4⁺CD69⁺ and CD8⁺CD69⁺ T cells and BD FACS DIVA v.6 software was used to analysed the data. Statistical analysis was carried out using SPSS 22.0.

RESULTS

LTr with OI had significantly lower % of CD8⁺CD69⁺IFNγ⁺ T cells at 60 (7.95 ± 0.77 vs 26.25 ± 2.09, P < 0.001), 90 (7.47 ± 1.05 vs 30.34 ± 3.52, P < 0.001) and 180 (15.31 ± 3.24 vs 24.59 ± 3.28, P = 0.01) d post-transplantation. Higher % of CD4⁺CD69⁺IL-10⁺ as well as CD4⁺CD69⁺IL-17⁺ T cells were yet reported at 30 (14.06 ± 1.65 vs 6.09 ± 0.53, P = 0.0007 and 4.23 ± 0.56 vs 0.81 ± 0.14, P = 0.005; respectively), 60 (11.46 ± 1.42 vs 4.54 ± 0.91, P = 0.001 and 4.21 ± 0.59 vs 1.43 ± 0.42, P = 0.03; respectively) and 90 d (16.85 ± 1.60 vs 4.07 ± 0.63, P < 0.001 and 3.97 ± 0.43 vs 0.96 ± 0.17, P = 0.001). Yet, KTr with OI had significantly lower percentage of CD4⁺CD69⁺IFNγ⁺ at 30 (11.80 ± 1.59 vs 20.64 ± 3.26, P = 0.035), 60 (11.19 ± 1.35 vs 15.85 ± 1.58, P = 0.02), 90 (11.37 ± 1.42 vs 22.99 ± 4.12, P = 0.028) and 180 (13.63 ± 2.21 vs 21.93 ± 3.88, P = 0.008) d post-transplantation as opposed to CD4⁺CD69⁺IL-10⁺ and CD8⁺CD69⁺IL-10⁺ T cells which percentages were higher at 30 (25.21 ± 2.74 vs 8.54 ± 1.64, P < 0.001 and 22.37 ± 1.35 vs 17.18 ± 3.54, P = 0.032; respectively), 90 (16.85 ± 1.60 vs 4.07 ± 0.63, P < 0.001 and 23.06 ± 2.89 vs 10.19 ± 1.98, P = 0.002) and 180 (21.81 ± 1.72 vs 6.07 ± 0.98, P < 0.001 and 19.68 ± 2.27 vs 10.59 ± 3.17, P = 0.016) d post-transplantation. The auROC curve model determined the most accurate cut-off values to stratify LTr and KTr at high risk of OI and Cox Regression model confirmed these biomarkers as the most significant risk factors to opportunistic infection.

CONCLUSION

Post-transplant percentages of T-cell subsets differed significantly amongst infected- and non-infected-LTr and -KTr and yet this imbalance was found to contribute towards a worst clinical outcome.