Differential T cell response against BK virus regulatory and structural antigens: A viral dynamics modelling approach

Abstract

BK virus (BKV) associated nephropathy affects 1–10% of kidney transplant recipients, leading to graft failure in about 50% of cases. Immune responses against different BKV antigens have been shown to have a prognostic value for disease development. Data currently suggest that the structural antigens and regulatory antigens of BKV might each trigger a different mode of action of the immune response. To study the influence of different modes of action of the cellular immune response on BKV clearance dynamics, we have analysed the kinetics of BKV plasma load and anti-BKV T cell response (Elispot) in six patients with BKV associated nephropathy using ODE modelling. The results show that only a small number of hypotheses on the mode of action are compatible with the empirical data. The hypothesis with the highest empirical support is that structural antigens trigger blocking of virus production from infected cells, whereas regulatory antigens trigger an acceleration of death of infected cells. These differential modes of action could be important for our understanding of BKV resolution, as according to the hypothesis, only regulatory antigens would trigger a fast and continuous clearance of the viral load. Other hypotheses showed a lower degree of empirical support, but could potentially explain the clearing mechanisms of individual patients. Our results highlight the heterogeneity of the dynamics, including the delay between immune response against structural versus regulatory antigens, and its relevance for BKV clearance. Our modelling approach is the first that studies the process of BKV clearance by bringing together viral and immune kinetics and can provide a framework for personalised hypotheses generation on the interrelations between cellular immunity and viral dynamics.

BKV, CMV, and EBV Interactions and their Effect on Graft Function One Year Post-Renal Transplantation: Results from a Large Multi-Centre Study

“…The incidence of BKVAN is 1–10% in renal transplantation [ 10 ]. BKVAN is usually encountered in a context of over-immunosuppression, even though it is not associated with a specific immunosuppressive drug [ 9 , 11 , 12 ]. Early diagnosis is vital for a successful treatment, but BKVAN progression occurs without clinical signs except for increasing serum creatinine concentrations and diagnosis relies on renal biopsy [ 9 , 11 ].…”

A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation

“…Pre-transplant HLA assay data were retrospectively analyzed as part of a systems medicine approach towards early risk assessment of ACR [42, 43]. The investigated study group comprised all kidney transplant recipients enrolled in the Harmony trial ( N = 615) who experienced at least one ACR or borderline ACR event in the first year ( N = 77) and all transplant recipients who experienced no serious adverse events ( N = 80).…”

“…Suspected episodes of acute rejection were confirmed through biopsy according to the Banff criteria of 2005 [56]. For the e:KID project, which aims at early risk assessment of ACR by following a systems medicine approach [42, 43], 157 recipients were retrospectively monitored for the presence of HLA antibodies in blood serum on day 0 (pre-transplantation). All patients who experienced ACR (borderline or Banff class 1 or higher) in the first year were assigned to the ACR group ( N = 77).…”

Validated models of immune response to virus infection

“…The most used model is the standard viral dynamics model (Figure 1), which was introduced over 20 years ago (reviewed in [14,15]). The model has since been successfully applied to study a variety of virus infections, including HIV [16], HCV[17], IAV [9], West Nile virus (WNV) [18], Dengue virus (DENV) [19], Adenovirus (ADV) [20], RSV [21], yellow fever virus (YFV) [22], ZV [23], BKV [24,25], and HPV [26,27], among others. These viruses range from acute to chronic and have varied sites of infection (e.g., lung versus liver) and pathologies (e.g., pneumonia versus cirrhosis).…”

“…A recent increase in experimental validation of model predictions has led to important biological insight, improvements in model development and interpretation, and exciting progress in the field. This progress manifested through close collaborations between theoreticians and experimentalists (e.g., as in [24,36–39]), through theoreticians acquiring training in experimental biology (e.g., as in [40,41]), and through experimentalists or clinicians acquiring training in mathematical modeling (e.g., as in [28]). Novel data with measurements on frequent time scales and new research directions arose as a result.…”