Renal transplantation is the optimal treatment for end-stage renal disease as it allows rehabilitation with better survival than hemodialysis or peritoneal dialysis.¹ In 2016, the annual mortality rate per 100 patient-years in Hong Kong was only 1.88 for renal transplant recipients, compared to 17.89 for patients on peritoneal dialysis and 18.89 for those on hemodialysis.¹ However, despite the low mortality rate, about 35% of recipients lose their allograft by 10 years.² Late allograft loss is increasingly attributed to the cumulative effects of underlying subacute immunological injury identified only after irreversible damage has already occurred.^3,4 In this regard, an early immunological biomarkers that predict future rejection and chronic allograft loss are needed to advise preemptive therapy and improve long-term outcomes.⁵

Up to 30% of surveillance biopsies in the first post-transplant year showed subclinical rejection, implying that current immunosuppressive therapy may reduce acute clinical rejection but not prevent subtle immune-mediated damages that can smolder unrecognized allograft loss.⁵ Thus, it is necessary to identify patients at high risk in advance to allow preemptive treatment before the effector alloimmune response fully matures into irreversible damage.⁵

However, the clinical and laboratory parameters currently in use may not be able to identify subclinical rejection as the parameters are associated with worse outcomes but have limited predictive value.⁵ On the other hand, frequent surveillance biopsies are impractical to individuals at high risk for future rejection or those whose rejection may be refractory to therapy.⁵ As a result, there is a need to develop non-invasive and predictive biomarkers for better patient identification.⁵

Previously, human regulatory B cell activity, best defined by the ratio of interleukin-10 (IL-10) to tumor necrosis factor–α (TNFα) expression by transitional B cells (T1B), was shown to be associated with late rejection.⁵ To confirm its predictive value for future rejection and long-term outcomes, a recent study had prospectively examined the human regulatory B cell activity ratio three months after transplantation as a predictive biomarker for clinical and subclinical renal allograft rejection and its subsequent clinical course.⁵

244 kidney transplant recipients from the University of Pittsburgh School of Medicine participated in this study and were divided into the Training Set (n=162) and Internal Validation Set (n=82).⁵ In the Training Set, 3 months after transplantation, a significantly lower T1B cell frequency and IL-10/TNFα ratio were observed among patients with T-cell-mediated rejection (TCMR) compared to those without (p<0.001).⁵ The ratio at 3 months was the strongest predictor of rejection in the first post-transplant year.⁵ A 71% reduction in the risk of TCMR was also observed with every unit (integer) increase in the T1B IL-10/TNFα ratio in the Training Set (p<0.001).⁵

In the secondary analysis, patients in both the Training and Internal Validation Sets were combined and stratified into three distinct risk groups on the basis of distribution of their T1B IL-10/TNFα ratios, namely the high-risk (ratio: 0-1.3; 83% TCMR incidence), intermediate-risk (ratio: 1.31-1.6; 18% TCMR incidence) and low-risk ratios (ratio: >1.6; 6.5% TCMR incidence).⁵ Among the identified high-risk patients, 60% of them had early TCMR at 3 months, and of which 48% developed recurrent or recalcitrant late TCMR in the first post-transplant year despite anti-rejection therapy.⁵ Moreover, in the remaining 40% of high-risk patients without early TCMR, 74% developed de novo late TCMR subsequently.⁵ In contrast, less than 10% of low-risk patients had either early or late rejection.⁵ These results reinforced the potency of T1B IL-10/TNFα ratio as a predictor for not only early TCMR, but also late TCMR with an average lead time of 8 months.⁵

To conclude, this validation study suggested that the T1B IL-10/TNFα ratio could be a strong biomarker to identify high-risk patients and predict subsequent late rejection.⁵ The evidence supported the utilization of this immunological biomarker in renal transplant recipients to predict subsequent TCMR and graft loss, allowing an early introduction of preemptive therapeutic intervention to improve the clinical course of patients following transplantation.⁵