Within the B-cell compartment, we identified 10 distinct B-cell subpopulations, including B cells with a naive (IgD+CD27−),52 regulatory (CD25hi),53,54 antibody-secreting (IgD−CD27+CD38+),55 and memory (IgD−CD27+CD38−)52 phenotype. We did not detect statistically significant differences at any time point in B-cell subpopulations between DSAPOS and DSANEG recipients (Figure 5B).
However, we noticed a trend toward increased B cells with antibody-secreting or memory phenotypes at the time of DSA in DSAPOS recipients compared with DSANEG individuals. We then hypothesized that stratification of DSAPOS recipients according to the development of AMR within the first 5 years posttransplant would elucidate cells potentially responsible for this immunological process. B cells with antibody-secreting or memory phenotypes were significantly increased at the time of DSA detection only in DSAPOS recipients that later developed AMR (Figure 6). Of note, these cells were present in the peripheral blood ≈18 months before the onset of AMR diagnosis by biopsy (Table 2). None of the major immune compartments differed significantly at any time points between DSAPOS patients who did or did not develop AMR. DSA levels at 2 and 3 years after transplant in DSAPOS patients who developed AMR did not significantly differ compared with those of DSAPOS patients who did not develop AMR (DSA at 2 y: 12 170 ± 7722 vs 8540 ± 7799, P = 0.48; at 3 y: 11 970 ± 3997 vs 11 600 ± 7214 MFI; P = 0.92, respectively). The 3 patients who lost their grafts developed AMR and had high levels of B cells with antibody-secreting and memory phenotypes.
Identifying cellular immune mediators responsible for AMR in kidney transplant recipients has proven difficult due to the limited number of markers that can be probed using flow cytometry. We utilized unbiased CyTOF analyses to comprehensively characterize the immune phenotype in pediatric kidney transplant recipients using serial samples collected before and at the time of DSA development. While CyTOF has been used with great success in the oncologic sciences, its implementation in human solid organ transplantation has been limited to a few studies.46,56 Herein, we discovered that, while percentages of circulating B cells with an antibody-secreting or memory phenotype did not significantly differ between DSAPOS and DSANEG recipients before DSA detection, they were enriched at the time of DSA detection only in recipients who developed AMR >1 year later.
It is well established that DSA positivity portends inferior allograft outcomes due to the increased risk of AMR.8,57,58 However, the factors leading to dnDSA development and progression to AMR are unclear. Half of the DSAPOS recipients in our cohort developed AMR despite similar baseline characteristics, immunosuppression regimens, and donor/recipient HLA matches (Table 1). Nonadherence has been implied as a major risk factor for the development of DSA, especially in pediatric recipients.43,44 IPV in cyclosporine and tacrolimus levels was within target ranges and similar across all recipients (Figure S1, SDC, http://links.lww.com/TXD/A217), suggesting that nonadherence was not a major determinant for dnDSA development in our cohort.42-44
DSA levels at the time of DSA detection were similar as well, making this information of little value to risk-stratify DSA recipients who will develop AMR (Table S3, SDC, http://links.lww.com/TXD/A217). Others have reported that the ability to fix and activate the complement cascade, as determined by C1q and C3d binding, identifies pathogenic DSA and correlates with shorter allograft survival.21,23-27,59,60 However, 9 out of the 10 recipients in our cohort had DSA that bound C1q (Table 3). More DSAPOSAMRPOS recipients had C3d-binding DSA, but this trend did not reach statistical significance (P = 0.52). Therefore, in this pediatric population, C1q and C3d staining did not prove to be useful predictors of AMR development.
B cells with memory or antibody-secreting phenotype were the only cell subsets that we identified as differentially increased in DSAPOS recipients that later developed AMR. These cells were identified based on their absence of IgD and expression of CD27—signifying mature B cells61—and differential expression of CD38. CD38 is a highly conserved type II glycoprotein that possesses pleiotropic effects on B-cell function and maturation.62-64 Whereas CD38 induces apoptosis in early B cells, it promotes survival in germinal center B cells.65 Antibody-secreting cells, including plasma cells and immature plasmablasts,66 express high levels of CD38, whereas memory B cells, a long-lasting B-cell subset capable of differentiating into antibody-secreting B cells and producing high-affinity antibodies upon antigen re-encounter,33-35 lack CD38 expression.67,68 Our data confirm and expand to a pediatric population previous evidence by Luque et al52 showing increased donor-reactive memory B cells in the circulation of adult DSAPOS recipients with ongoing AMR. Intriguingly, these authors identified donor-reactive memory B cells by Elispot, while they failed to identify a difference in any of the B cell subsets measured by flow cytometry.52 The increased sensitivity of the CyTOF technique when compared with flow cytometry provides the opportunity to identify and quantify low-frequency lymphocyte populations in peripheral blood. Indeed, we were able to probe for differences in 9 major immune compartments and 25 lymphocyte subpopulations using CyTOF.
Our comprehensive immune phenotypic characterization by CyTOF also allowed us to test for any relationship between circulating T-cell subsets and DSA development. Unexpectedly, we did not detect differences in any of the CD4+ or CD8+ T-cell subsets between DSAPOS and DSANEG recipients at any time point, including circulating TFH—a specialized T-cell subset integral to efficient antibody production that assists B-cell differentiation into plasma cells—and TREG. Different groups have attempted to find a relationship between circulating TFH or TREG and graft outcomes, but results, invariably generated using flow cytometry, have been inconsistent so far.52,69-72 Our comprehensive, unbiased approach on serially collected samples does not support such a relationship, at least in pediatric patients.
Our study has some limitations. The sample size was relatively small, and we did not validate our results in an independent cohort. However, we resampled and reanalyzed the B-cell clusters 5 times to ensure that our findings were statistically robust. CyTOF allowed us to conduct comprehensive immune phenotyping with increased sensitivity for low-expressed markers. Although perfectly suited to extract the most information from a reduced number of samples, it cannot overcome the limitations associated with a small number of patients. We also have not determined that the B cells with a memory or antibody-secreting phenotype are specific to the HLA antigens that the DSAs were against. Lack of functional data on B cells with a memory or antibody-secreting phenotype represents another limitation, although the cell surface markers used to classify these cells are well established in the literature.67,68 Our phenotypic data complement functional studies by others showing that memory B cells can be detected in the circulation before DSA development.52 Future studies will be required to define antigen specificity of B cells with memory or antibody-secreting phenotype.
Overall, the present study demonstrates that circulating B cells with an antibody-secreting and memory phenotype increase in DSAPOS recipients before the development of AMR. We also show that these cells are detectable in the peripheral circulation at the time of DSA onset, more than a year before biopsy-proven rejection, highlighting a possible role for aggressive B-cell–targeted immunosuppression in these at-risk recipients. These pilot results warrant further validation in larger cohort studies.
1. Kidney Disease: Improving Global Outcomes (KDIGO) Transplant Work Group. KDIGO clinical practice guideline for the care of kidney transplant recipients. Am J Transplant. 2009;9(Suppl 3):S1–S155.
2. Kasiske BL, Zeier MG, Chapman JR, et al; Kidney Disease: Improving Global Outcomes. KDIGO clinical practice guideline for the care of kidney transplant recipients: a summary. Kidney Int. 2010;77:299–311.
3. Lamb KE, Lodhi S, Meier-Kriesche HU. Long-term renal allograft survival in the United States: a critical reappraisal. Am J Transplant. 2011;11:450–462.
4. Lodhi SA, Lamb KE, Meier-Kriesche HU. Solid organ allograft survival improvement in the United States: the long-term does not mirror the dramatic short-term success. Am J Transplant. 2011;11:1226–1235.
5. Meier-Kriesche HU, Schold JD, Srinivas TR, et al. Lack of improvement in renal allograft survival despite a marked decrease in acute rejection rates over the most recent era. Am J Transplant. 2004;4:378–383.
6. Van Arendonk KJ, Boyarsky BJ, Orandi BJ, et al. National trends over 25 years in pediatric kidney transplant outcomes. Pediatrics. 2014;133:594–601.
7. Zhang R. Donor-specific antibodies in kidney transplant recipients. Clin J Am Soc Nephrol. 2018;13:182–192.
8. Wiebe C, Gibson IW, Blydt-Hansen TD, et al. Evolution and clinical pathologic correlations of de novo donor-specific HLA antibody post kidney transplant. Am J Transplant. 2012;12:1157–1167.
9. Hart A, Smith JM, Skeans MA, et al. Kidney. Am J Transplant. 2016;16(Suppl 2):11–46.
10. Hart A, Smith JM, Skeans MA, et al. OPTN/SRTR 2016 Annual Data Report: kidney. Am J Transplant. 2018;18(Suppl 1):18–113.
11. Chehade H, Pascual M. The challenge of acute antibody-mediated rejection in kidney transplantation. Transplantation. 2016;100:264–265.
12. Montgomery RA, Loupy A, Segev DL. Antibody-mediated rejection: new approaches in prevention and management. Am J Transplant. 2018;18(Suppl 3):3–17.
13. Gaston RS, Cecka JM, Kasiske BL, et al. Evidence for antibody-mediated injury as a major determinant of late kidney allograft failure. Transplantation. 2010;90:68–74.
14. Nankivell BJ, Kuypers DR. Diagnosis and prevention of chronic kidney allograft loss. Lancet. 2011;378:1428–1437.
15. Sautenet B, Blancho G, Büchler M, et al. One-year results of the effects of rituximab on acute antibody-mediated rejection in renal transplantation: RITUX ERAH, a multicenter double-blind randomized placebo-controlled trial. Transplantation. 2016;100:391–399.
16. Valenzuela NM, Reed EF. Zachary AA, Leffell MS. Antibodies in transplantation: the effects of HLA and Non-HLA antibody binding and mechanisms of injury. In: Transplantation Immunology: Methods and Protocols. 2013:Totowa, NJ: Humana Press; 41–70.
17. Kosmoliaptsis V, Sharples LD, Chaudhry AN, et al. Predicting HLA class II alloantigen immunogenicity from the number and physiochemical properties of amino acid polymorphisms. Transplantation. 2011;91:183–190.
18. Loupy A, Vernerey D, Tinel C, et al. Subclinical rejection phenotypes at 1 year post-transplant and outcome of kidney allografts. J Am Soc Nephrol. 2015;26:1721–1731.
19. Kumbala D, Zhang R. Essential concept of transplant immunology for clinical practice. World J Transplant. 2013;3:113–118.
20. Thomas KA, Valenzuela NM, Reed EF. The perfect storm: HLA antibodies, complement, fcγrs, and endothelium in transplant rejection. Trends Mol Med. 2015;21:319–329.
21. Comoli P, Cioni M, Tagliamacco A, et al. Acquisition of C3d-binding activity by de novo donor-specific HLA antibodies correlates with graft loss in nonsensitized pediatric kidney recipients. Am J Transplant. 2016;16:2106–2116.
22. Chen G, Sequeira F, Tyan DB. Novel C1Q assay reveals a clinically relevant subset of human leukocyte antigen antibodies independent of immunoglobulin G strength on single antigen beads. Hum Immunol. 2011;72:849–858.
23. Yabu JM, Higgins JP, Chen G, et al. C1q-fixing human leukocyte antigen antibodies are specific for predicting transplant glomerulopathy and late graft failure after kidney transplantation. Transplantation. 2011;91:342–347.
24. Freitas MC, Rebellato LM, Ozawa M, et al. The role of immunoglobulin-G subclasses and C1Q in de novo HLA-DQ donor-specific antibody kidney transplantation outcomes. Transplantation. 2013;95:1113–1119.
25. Sutherland SM, Chen G, Sequeira FA, et al. Complement-fixing donor-specific antibodies identified by a novel C1Q assay are associated with allograft loss. Pediatr Transplant. 2012;16:12–17.
26. Sicard A, Ducreux S, Rabeyrin M, et al. Detection of C3d-binding donor-specific anti-HLA antibodies at diagnosis of humoral rejection predicts renal graft loss. J Am Soc Nephrol. 2015;26:457–467.
27. Loupy A, Lefaucheur C, Vernerey D, et al. Complement-binding anti-HLA antibodies and kidney-allograft survival. N Engl J Med. 2013;369:1215–1226.
28. Lee H, Han E, Choi AR, et al. Clinical impact of complement (C1q, C3d) binding de novo donor-specific HLA antibody in kidney transplant recipients. PLOS One. 2018;13:e0207434.
29. Okabe Y, Noguchi H, Miyamoto K, et al. Preformed C1q-binding donor-specific anti-HLA antibodies and graft function after kidney transplantation. Transplant Proc. 2018;50:3460–3466.
30. Moreno Gonzales MA, Mitema DG, Smith BH, et al. Comparison between total IgG, C1q, and C3d single antigen bead assays in detecting class I complement-binding anti-HLA antibodies. Transplant Proc. 2017;49:2031–2035.
31. Bamoulid J, Roodenburg A, Staeck O, et al. Clinical outcome of patients with de novo C1q-binding donor-specific HLA antibodies after renal transplantation. Transplantation. 2017;101:2165–2174.
32. Guidicelli G, Guerville F, Lepreux S, et al. Non-complement-binding de novo donor-specific anti-HLA antibodies and kidney allograft survival. J Am Soc Nephrol. 2016;27:615–625.
33. Buisman AM, de Rond CG, Oztürk K, et al. Long-term presence of memory B-cells specific for different vaccine components. Vaccine. 2009;28:179–186.
34. Crotty S, Aubert RD, Glidewell J, et al. Tracking human antigen-specific memory B cells: a sensitive and generalized ELISPOT system. J Immunol Methods. 2004;286:111–122.
35. Tarlinton D, Good-Jacobson K. Diversity among memory B cells: origin, consequences, and utility. Science. 2013;341:1205–1211.
36. McHeyzer-Williams MG, Ahmed R. B cell memory and the long-lived plasma cell. Curr Opin Immunol. 1999;11172–179.
37. Chong AS, Sciammas R. Memory B cells in transplantation. Transplantation. 2015;99:21–28.
38. Lúcia M, Luque S, Crespo E, et al. Preformed circulating HLA-specific memory B cells predict high risk of humoral rejection in kidney transplantation. Kidney Int. 2015;88:874–887.
39. Haas M, Sis B, Racusen LC, et al; Banff Meeting Report Writing Committee. Banff 2013 meeting report: inclusion of c4d-negative antibody-mediated rejection and antibody-associated arterial lesions. Am J Transplant. 2014;14:272–283.
40. Tagliamacco A, Cioni M, Comoli P, et al. DQ molecules are the principal stimulators of de novo donor-specific antibodies in nonsensitized pediatric recipients receiving a first kidney transplant. Transpl Int. 2014;27:667–673.
41. Visentin J, Vigata M, Daburon S, et al. Deciphering complement interference in anti-human leukocyte antigen antibody detection with flow beads assays. Transplantation. 2014;98:625–631.
42. Shuker N, van Gelder T, Hesselink DA. Intra-patient variability in tacrolimus exposure: causes, consequences for clinical management. Transplant Rev (Orlando). 2015;29:78–84.
43. van Gelder T. Within-patient variability in immunosuppressive drug exposure as a predictor for poor outcome after transplantation. Kidney Int. 2014;85:1267–1268.
44. Prytula AA, Bouts AH, Mathot RA, et al. Intra-patient variability in tacrolimus trough concentrations and renal function decline in pediatric renal transplant recipients. Pediatr Transplant. 2012;16:613–618.
45. Lavin Y, Kobayashi S, Leader A, et al. Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell. 2017;169:750.e17–765.e17.
46. Fribourg F, Fischman C, Anderson L, et al. T-cell exhaustion in kidney transplant patients. In: Paper presented at: American Transplant Congress; June 5, 2018.Seattle, Washington.
47. DiGiuseppe JA, Cardinali JL, Rezuke WN, et al. Phenograph and visne facilitate the identification of abnormal T-cell populations in routine clinical flow cytometric data. Cytometry B Clin Cytom. 2018;94:588–601.
48. Schwartz GJ, Haycock GB, Edelmann CM Jr, et al. A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine. Pediatrics. 1976;58:259–263.
49. Levine JH, Simonds EF, Bendall SC, et al. Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell. 2015;162:184–197.
50. Campbell DJ, Kim CH, Butcher EC. Separable effector T cell populations specialized for B cell help or tissue inflammation. Nat Immunol. 2001;2:876–881.
51. Qi H. T follicular helper cells in space-time. Nat Rev Immunol. 2016;16:612–625.
52. Luque S, Lúcia M, Melilli E, et al. Value of monitoring circulating donor-reactive memory B cells to characterize antibody-mediated rejection after kidney transplantation. Am J Transplant. 2019;19:368–380.
53. Rosser EC, Mauri C. Regulatory B cells: origin, phenotype, and function. Immunity. 2015;42:607–612.
54. van de Veen W, Stanic B, Yaman G, et al. IgG4 production is confined to human IL-10-producing regulatory B cells that suppress antigen-specific immune responses. J Allergy Clin Immunol. 2013;131:1204–1212.
55. Matsumoto M, Baba A, Yokota T, et al. Interleukin-10-producing plasmablasts exert regulatory function in autoimmune inflammation. Immunity. 2014;41:1040–1051.
56. Yabu JM, Siebert JC, Maecker HT. Immune profiles to predict response to desensitization therapy in highly HLA-sensitized kidney transplant candidates. PLOS One. 2016;114e0153355.
57. Worthington JE, Martin S, Al-Husseini DM, et al. Posttransplantation production of donor HLA-specific antibodies as a predictor of renal transplant outcome. Transplantation. 2003;75:1034–1040.
58. Lefaucheur C, Loupy A, Hill GS, et al. Preexisting donor-specific HLA antibodies predict outcome in kidney transplantation. J Am Soc Nephrol. 2010;21:1398–1406.
59. Bartel G, Wahrmann M, Schwaiger E, et al. Solid phase detection of C4d-fixing HLA antibodies to predict rejection in high immunological risk kidney transplant recipients. Transpl Int. 2013;26:121–130.
60. Lawrence C, Willicombe M, Brookes PA, et al. Preformed complement-activating low-level donor-specific antibody predicts early antibody-mediated rejection in renal allografts. Transplantation. 2013;95:341–346.
61. Jacquot S. CD27/CD70 interactions regulate T dependent B cell differentiation. Immunol Res. 2000;21:23–30.
62. Funaro A, Spagnoli GC, Ausiello CM, et al. Involvement of the multilineage CD38 molecule in a unique pathway of cell activation and proliferation. J Immunol. 1990;145:2390–2396.
63. Zupo S, Rugari E, Dono M, et al. CD38 signaling by agonistic monoclonal antibody prevents apoptosis of human germinal center B cells. Eur J Immunol. 1994;24:1218–1222.
64. Deaglio S, Vaisitti T, Bergui L, et al. CD38 and CD100 lead a network of surface receptors relaying positive signals for B-CLL growth and survival. Blood. 2005;105:3042–3050.
65. Deaglio S, Capobianco A, Bergui L, et al. CD38 is a signaling molecule in B-cell chronic lymphocytic leukemia cells. Blood. 2003;102:2146–2155.
66. Nutt SL, Hodgkin PD, Tarlinton DM, et al. The generation of antibody-secreting plasma cells. Nat Rev Immunol. 2015;15:160–171.
67. Jelinek DF, Splawski JB, Lipsky PE. Human peripheral blood B lymphocyte subpopulations: functional and phenotypic analysis of surface IgD positive and negative subsets. J Immunol. 1986;136:83–92.
68. Liu YJ, Barthélémy C, de Bouteiller O, et al. Memory B cells from human tonsils colonize mucosal epithelium and directly present antigen to T cells by rapid up-regulation of B7-1 and B7-2. Immunity. 1995;2:239–248.
69. Cano-Romero FL, Laguna Goya R, Utrero-Rico A, et al. Longitudinal profile of circulating T follicular helper lymphocytes parallels anti-HLA sensitization in renal transplant recipients. Am J Transplant. 2019;19:89–97.
70. de Graav GN, Dieterich M, Hesselink DA, et al. Follicular T helper cells and humoral reactivity in kidney transplant patients. Clin Exp Immunol. 2015;180:329–340.
71. Chenouard A, Chesneau M, Bui Nguyen L, et al. Renal operational tolerance is associated with a defect of blood tfh cells that exhibit impaired B cell help. Am J Transplant. 2017;17:1490–1501.
72. Alberu J, Vargas-Rojas MI, Morales-Buenrostro LE, et al. De novo donor-specific HLA antibody development and peripheral CD4(+)CD25(high) cells in kidney transplant recipients: a place for interaction? J Transplant. 2012;2012:302539.