Quantitative characterization of T-cell repertoire and biomarkers in kidney transplant rejection

Abstract

Background: T-cell-mediated rejection (TCMR) remains a major cause of kidney allograft failure. The characterization of T-cell repertoire in different immunological disorders has emerged recently as a novel tool with significant implications. We herein sought to characterize T-cell repertoire using next generation sequencing to diagnose TCMR.

Methods: In this prospective study, we analyzed samples from 50 kidney transplant recipients. We collected blood and kidney transplant biopsy samples at sequential time points before and post transplant. We used next generation sequencing to characterize T-cell receptor (TCR) repertoire by using illumina miSeq on cDNA synthesized from RNA extracted from six patients' samples. We also measured RNA expression levels of FOXP3, CD8, CD4, granzyme and perforin in blood samples from all 50 patients.

Results: Seven patients developed TCMR during the first three months of the study. Out of six patients who had complete sets of blood and biopsy samples two had TCMR. We found an expansion of the TCR repertoire in blood at time of rejection when compared to that at pre-transplant or one-month post transplant. Patients with TCMR (n = 7) had significantly higher RNA expression levels of FOXP3, Perforin, Granzyme, CD4 and CD8 in blood samples than those with no TCMR (n = 43) (P = 0.02, P = 0.003, P = 0.002, P = 0.017, and P = 0.01, respectively).

Conclusions: Our study provides a potential utilization of TCR clone kinetics analysis in the diagnosis of TCMR. This approach may allow for the identification of the expanded T-cell clones associated with the rejection and lead to potential noninvasive diagnosis and targeted therapies of TCMR.

Keywords: Kidney transplant; T cell mediated rejection; T cell sequencing; T-cell.

Fig. 1

The clonality of T lymphocytes in blood and grafts of six kidney transplant patients. The distribution of the unique CDR3 sequences detected in TCRB. Each pie graph represents one sample, showing the frequencies of the ranked top ten clones and the light blue color represent sum of the frequencies of the remaining clones

Fig. 2

Expansion of TCR repertoire at the time of graft rejection. We generated the recurrent TCR repertoire by combining all TCR clones appeared at any time point (before and after transplant) in samples obtained from blood or graft. And then compared the frequency of each clone in the recurrent repertoire at the time of rejection (or the same time in case of patients with no rejection) with that at the earliest time point available for analysis (before transplant or 1 month post transplant)

Fig. 3

Tracking the top ten clones presented in the graft at the time of rejection to their earliest presence in blood or graft. We obtained the top ten most frequent clones observed in graft of patient #3 (TCMR), and showed the frequencies at which these clones were present in the blood and graft samples obtained at earlier time point

Fig. 4

TCR repertoire diversity in blood kidney transplant patients. The diversity of the TCR repertoire was calculated for each sample using Simpson index. (a) Diversity indexes were compared between blood and graft samples. Diversity of TCR repertoire in blood samples (b) and graft (c) were compared between different patients

Fig. 5

TCR repertoire diversity according to graft rejection status. The diversity of TCR repertoire of samples obtained from blood pre and post transplant (a) or post-transplant (b) was compared between patients with graft rejection and those without

Fig. 6

T-cells markers expression according to graft rejection status. The mRNA expression of T-cell markers (Perforin, Granzyme, CD4 and CD8) were measured in blood samples obtained from patients with graft rejection and those without rejection