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Multicenter Study
. 2017 Oct;17(10):2627-2639.
doi: 10.1111/ajt.14283. Epub 2017 May 2.

B Cell Receptor Genes Associated With Tolerance Identify a Cohort of Immunosuppressed Patients With Improved Renal Allograft Graft Function

A Asare  1 , S Kanaparthi  1 , N Lim  1 , D Phippard  1 , F Vincenti  2 , J Friedewald  3 , M Pavlakis  4 , E Poggio  5 , P Heeger  6 , R Mannon  7 , B E Burrell  1 , Y Morrison  8 , N Bridges  8 , I Sanz  9 , A Chandraker  10 , K A Newell  9 , L A Turka  11
Affiliations
Multicenter Study

B Cell Receptor Genes Associated With Tolerance Identify a Cohort of Immunosuppressed Patients With Improved Renal Allograft Graft Function

A Asare et al. Am J Transplant. 2017 Oct.

Abstract

We previously reported that two B cell receptor genes, IGKV1D-13 and IGKV4-1, were associated with tolerance following kidney transplantation. To assess the potential utility of this "signature," we conducted a prospective, multicenter study to determine the frequency of patients predicted tolerant within a cohort of patients deemed to be candidates for immunosuppressive minimization. At any single time point, 25-30% of patients were predicted to be tolerant, while 13.7% consistently displayed the tolerance "signature" over the 2-year study. We also examined the relationship of the presence of the tolerance "signature" on drug use and graft function. Contrary to expectations, the frequency of predicted tolerance was increased in patients receiving tacrolimus and reduced in those receiving corticosteroids, mycophenolate mofetil, or Thymoglobulin as induction. Surprisingly, patients consistently predicted to be tolerant displayed a statistically and clinically significant improvement in estimated glomerular filtration rate that increased over time following transplantation. These findings indicate that the frequency of patients consistently predicted to be tolerant is sufficiently high to be clinically relevant and confirm recent findings by others that immunosuppressive agents impact putative biomarkers of tolerance. The association of a B cell-based "signature" with graft function suggests that B cells may contribute to the function/survival of transplanted kidneys.

Keywords: biomarker; clinical research/practice; graft survival; kidney transplantation/nephrology.

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Conflict of interest statement

Disclosure

The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.

Figures

Figure 1
Figure 1
Prevalence of TOL signature over the three time-points. Participants Predicted TOL and non-TOL remain relatively stable over time. https://www.itntrialshare.org/ARTIST_fig1.url
Figure 2
Figure 2
Creatinine and eGFR Levels between 17 consistently Predicted TOL (dark blue), Predicted TOL at that visit but not for all three time points (light blue), Predicted non-TOL (light red) at that time point, 71 consistently Predicted non-TOL (red). Participants consistently Predicted TOL have lower Creatinine and higher eGFR compared to the other groups. Creatinine and eGFR are statistically significant for 71 consistently Predicted non-TOL vs. 17 consistently Predicted TOL. https://www.itntrialshare.org/ARTIST_fig2.url
Figure 3
Figure 3
Creatinine and eGFR Levels between 17 consistently Predicted TOL vs. 71 consistently Predicted non-TOL. Solid line shows smooth line for each group with shading representing 95% confidence intervals (CI). Data shown for all three time-points as available per participant. https://www.itntrialshare.org/ARTIST_fig3.url.
Figure 4
Figure 4
B-Cell subsets as absolute counts between 17 consistently Predicted TOL vs. 71 consistently Predicted non-TOL, P<0.05. B-Cell populations as % B-Cell (see Figure S2) are not statistically significant between 17 consistently Predicted TOL vs. 71 consistently Predicted non-TOL. SM – switched memory, USM – unswitched memory, DN – double negative, T1+T2 – transitional B cell subsets 1 and 2; T3 – transitional B cell subset 3. https://www.itntrialshare.org/ARTIST_fig4.url
Figure 5
Figure 5
B-Cell gene expression normalized by CD19 absolute counts between all Predicted TOL vs All Predicted non-TOL are statistically significant. Per cell gene expression levels between 17 consistently Predicted TOL vs. 71 consistently Predicted non-TOL show a similar pattern, but are not statistically significant likely due to the smaller number of participants (not shown). https://www.itntrialshare.org/ARTIST_fig5.url
Figure 6a
Figure 6a
Percentage of participants Predicted TOL within clinical sub-groups. Generally, no Thymo induction, no steroid usage, Tacrolimus, and only Campath shows higher proportion of participants with TOL prediction. Comparisons statistically significant, P<0.05 (*), with two to three participants in the mTOR inhibitor only group depending upon visit. Percentage of Predicted TOLs within each sub-group is shown on x-axis and proportion of Predicted TOLs is shown as bar labels. https://www.itntrialshare.org/ARTIST_fig6a.url
Figure 6b
Figure 6b
Proportion of 17 consistently Predicted TOL across clinical subgroups. Similar to the proportions for all TOL participants within each visit, no Thymo induction, no steroid usage, Tacrolimus, and Campath only leads to higher number of participants with TOL prediction. Comparisons statistically significant, P<0.05 (*). Percentage of consistently Predicted TOLs with in each sub-group is shown on x-axis and proportion of consistently Predicted TOLs is shown as bar labels. https://www.itntrialshare.org/ARTIST_fig6b.url
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References

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