American Journal of Transplantation 2015; 15: 806–814 Wiley Periodicals Inc.
C
Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13010
Brief Communication
Circulating NK-Cell Subsets in Renal Allograft Recipients With Anti-HLA Donor-Specific Antibodies M. Crespo1,2,*, J. Yelamos2,3, D. Redondo1,2, A. Muntasell2, M. J. Perez-Sae´z1, ~ e´s4, C. Garcı´a5, A. Torio6, M. Lo´pez-Montan y 1 M. Mir , J. J. Herna´ndez5, M. Lo´pez-Botet2,3,4, y and J. Pascual1,2,
Abbreviations: ABMR, antibody-mediated rejection; ADCC, antibody-dependent cell mediated cytotoxicity; CDC, complement-dependent cytotoxicity; DSA, donor specific-antibodies; IQR, interquartilic range; MFI, mean fluorescence intensity; NK, natural killer; SAB, single antigen beads
1
Received 28 May 2014, revised 02 September 2014 and accepted for publication 06 September 2014
Department of Nephrology, Hospital del Mar, Barcelona, Spain 2 Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain 3 Department of Immunology, Hospital del Mar, Barcelona, Spain 4 Universitat Pompeu Fabra, Barcelona, Spain 5 Catalunya Reference Laboratory, El Prat de Llobregat Barcelona, Spain 6 Immunology Unit, Complejo Hospitalario Insular Materno Infantil, Las Palmas de Gran Canaria, Spain Corresponding author: Marta Crespo, [email protected] y Both authors contributed equally.
Detection of posttransplant donor-specific anti-HLA antibodies (DSA) constitutes a risk factor for kidney allograft loss. Together with complement activation, NK-cell antibody-dependent cell mediated cytotoxicity (ADCC) has been proposed to contribute to the microvascular damage associated to humoral rejection. In the present observational exploratory study, we have tried to find a relationship of circulating donor-specific and nondonor-specific anti-HLA antibodies (DSA and HLA non-DSA) with peripheral blood NK-cell subsets and clinical features in 393 renal allograft recipients. Multivariate analysis indicated that retransplantation and pretransplant sensitization were associated with detection of posttransplant DSA. Recipient female gender, DR mismatch and acute rejection were significantly associated with posttransplant DSA compared to HLA non-DSA. In contrast with patients without detectable anti-HLA antibodies, DSA and HLA non-DSA patients displayed lower proportions of NK-cells, associated with increased CD56bright and NKG2Aþ subsets, the latter being more marked in DSA cases. These differences appeared unrelated to retransplantation, previous acute rejection or immunosuppressive therapy. Although preliminary and observational in nature, our results suggest that the assessment of the NK-cell immunophenotype may contribute to define signatures of alloreactive humoral responses in renal allograft recipients. 806
Introduction Posttransplant donor-specific anti-HLA antibodies (DSA) are increasingly recognized as risk factors for kidney allograft loss (1–4). Detection of DSA together with typical histological changes and the presence of complement C4d deposits in peritubular capillaries in kidney graft biopsies were the criteria established for the diagnosis of antibodymediated rejection (ABMR) a decade ago (5). Nevertheless, several reports have found that microvascular damage is the cornerstone of chronic humoral rejection which may occur in the absence of complement deposition in the tissue (6–10). Some groups have hypothesized that effector mechanisms other than complement may be activated in the presence of posttransplant DSA (8,9). Activation of natural killer (NK) cells through FcgR-IIIA (CD16) to mediate antibody-dependent cell-mediated cytotoxicity (ADCC) has been proposed to play a role (9). An involvement of NK-cells in ABMR was supported by differential gene expression analysis in graft biopsies (10–12). Patients with DSA and microcirculation damage displayed increased expression of a subset of NK-cell-related genes, and biopsies showed that CD56þ cells were increased in ABMR compared with T cellmediated rejection, compatible with a role for NK-cells as potential effectors in endothelial injury (16). NK-cell effector functions are regulated by inhibitory and activating receptors. Among them, the CD94/NKG2A heterodimer and members of the killer immunoglobulinlike receptor (KIR) family repress NK-cell functions interacting with HLA-E and distinct sets of classical HLA class I molecules (13,14). The combinatorial distribution of these receptors determines the existence of different NK-cell subsets capable of responding against pathological cells which down-regulate HLA class I expression, as well as against normal allogeneic cells lacking the appropriate HLA ligands. CD56bright and CD56dim NK cell subsets represent
NK-Cell Subsets and Donor-Specific Antibodies
different stages of differentiation, which display distinct phenotypic and functional profiles (15). Most CD56bright NKcells, which constitute a minor proportion of circulating NKcells, express the CD94/NKG2A inhibitory receptor as well as activating NKG2D and natural cytotoxicity receptors, but lack KIR and CD16. CD56brightNK-cells secrete pro-inflammatory cytokines, have a low cytotoxic potential and are believed to differentiate into the more abundant and functionally mature CD16þNKG2DþCD56dim NK-cells. This population contains distinct subsets (e.g. NKG2AþKIRþ, NKG2ANKG2CþKIRþ, NKG2ANKG2C) which reflect further differentiation events, partially resulting from the influence of cytomegalovirus infection (16,17). The putative influence of NK-cell alloreactivity in solid organ transplantation has been addressed based on the genetic analysis of KIR–HLA mismatch with conflicting results (18,19). In the present study, we explored the potential relationship between circulating anti-HLA antibodies, clinical features and the distribution of peripheral blood NK-cell subsets in a large population of kidney transplant recipients, followed-up for an extended time period. Rather than comparing patients with and without DSA (2,3), we categorized them in three groups, i.e. without anti-HLA antibodies, with anti-HLA DSA and antiHLA non-DSA. Our results indicate that patients with DSA display lower numbers of circulating NK-cells, associated with higher proportions of the CD56bright and NKG2Aþ subsets.
Methods Patient population From 1979 to March 2012, 849 kidney transplants were performed at our institution. Of them, 441 patients over 3 months after transplantation who attended the outpatient clinic from 2008 to March 2012 were recruited. The study was approved by the Hospital Research Ethical Committee (2010/3904/I) and all patients signed informed consents. Periodical posttransplant serum samples were monitored for anti-HLA antibodies with Luminex technology. Peripheral blood immunophenotyping together with HLA antibody tests were performed once between April 2011 and December 2012 in 393 patients (Figure 1). A database including clinical and functional information contemporarily with antibody and immunophenotyping tests was filled.
Cross-match and HLA typing All patients were transplanted with a negative complement-dependent cytotoxicity (CDC) cross-match with mixed lymphocytes. Before 2000, HLA Class I and II antigens (HLA-A, -B, -DR) were determined by CDC technique. Low resolution DNA typing was performed using PCR–SSP commercial kits for donors and PCR–SSO for receptors afterwards. When anti-DQ antibodies were detected by single antigen beads (SAB), assignation as DSA was made by HLA-DQB1 genotyping of the donor by PCR–SSP or based on linkage disequilibrium when donor DNA samples were not available. Since no data for donor HLA-C or DP were available, antiC or anti-DP antibodies were not considered in the analysis.
using the Luminex Lifecodes LifeScreen Deluxe assay (Gen-probe, Stanford, CT), according to the manufacturer instructions. The kit was composed of seven beads coated with HLA Class I molecules and five beads coated with HLA Class II molecules. Briefly, 5 mL of multiplexed microbeads were incubated with 12.5 mL of serum for 30 min and washed three times to remove unbound antibody. 50 mL of anti-human IgG antibody conjugated to phycoerythrin was added for 30 min. Samples were analyzed on a Luminex 200 instrument (Luminex1, Austin, TX) using Bio-Plex Manager 6.0 as software for data acquisition, and MatchIt! Antibody v1.1.0.2 (Gen-Probe) program as analysis software. A bead was considered positive if more than 2 of the 3 adjusted ratio values (AR) were higher than 5. The AR values were calculated dividing the individual bead median fluorescence intensity (MFI) by the MFI of three negative control beads, and subtracting the background adjustment factor for each appropriate bead-control combination. A sample was considered positive for HLA-specific antibodies if at least one of the beads was positive. Positive and negative control sera were included in each test. Anti-HLA alloantibody IgG identification was performed using the Lifecodes LSA Class I and/or Class II assays (Gen-probe), according to the manufacturer instructions. The LSA Class I kit was composed of 93 beads coated with HLA Class I molecules (HLA-A, -B, -C), and LSA Class II kit was composed of 84 beads coated with HLA Class II molecules (HLA-DR, -DQ, -DP). Data were analyzed using MatchIT software, and the cutoff for a positive reaction was set in MFI > 1000. Donor HLA antibody specificity was ascribed considering donor HLA A, B, DRB and some DQB typing. Antibodies against C or most DQ antigens were assigned considering linkage disequilibrium.
Immunophenotypic analysis Immunophenotyping was performed by flow cytometry on fresh peripheral blood samples, obtained by venous puncture in EDTA tubes. Samples were pretreated with saturating concentrations of human aggregated immunoglobulins (Ig) to block FcgR and then labeled with different antibody combinations to define total T and B lymphocytes and NK-cell subsets. For direct immunofluorescence staining we used the following antibodies: FITC-CD3 (Clone SK7), APC-CD3 (Clone SK7), PerCP-CD45 (Clone 2D1), APC-CD45 (Clone 2D1), PerCP-CD19 (Clone SJ25C1), FITC-CD56 (Clone NCAM16.2), from BD biosciences. NK-cells were defined as CD3CD56þ lymphocytes; CD56dim and CD56bright subsets were identified according to the staining intensity with the specific monoclonal antibody. Additional NK-cell subsets were identified by indirect immunofluorescence staining using the following antibodies specific for: NKG2A (clone Z199; provided by Dr. A. Moretta), NKG2C (clone MAB1381; R&D systems, Minneapolis, MN), ILT2 (LILRB1) (clone HP-F1; generated in our lab) (20) and CD161 (clone HP-3G10, generated in our lab). KIR staining was performed using a mixture of antibodies specific for KIR3DL1/L2 (clone 5.133, provided by Dr. M. Colonna), KIR2DL2/S2/L3 (clone CH-L, provided by Dr. S. Ferrini), KIR3DL1 (clone DX9, provided by Dr. L. L. Lanier), and KIR2DL1/S1/S4 (clone HP-3E4, generated in our lab) (21). PE-conjugated F(ab’)2 rabbit anti-mouse Ig (Dako, Glostrup, Denmark) was used as secondary antibody. After washing and erythrocyte lysis, samples were acquired with a FACScalibur1 cytometer and the data analyzed with the CellQuest software (BD Biosciences). Absolute numbers of cells were calculated from blood counts obtained in parallel. The percentages of CD3þ, CD19þ and CD3CD56þ cells are referred to total lymphocytes; the percentages of CD3CD56bright, CD3CD56dim, CD3CD56þNKG2Aþ, CD3CD56þNKG2Cþ, CD3CD56þILT2þ, CD3CD56þKIRþ and CD3CD56þCD161þ are referred to NK-cells (CD3CD56þ).
Statistical analysis Anti-HLA antibody screening and characterization Pre and posttransplant serum samples were collected and freshly processed or stored at 808C until use. Screening for anti-HLA antibodies was performed
American Journal of Transplantation 2015; 15: 806–814
Comparisons between clinical variables were carried out using Student’s ttest for parametric continuous variables and U Mann–Whitney test for nonparametric data. Chi-squared or Fisher’s exact tests were used to test
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Crespo et al Recruitment of all funconing kidney transplants (2008-2012) n=441
Excluded (n=48) -
393 transplant recipients
Gra loss: dialysis (n=22), retransplant (n=5) Loss to follow-up (n=3) Death with funcon (n=14)
Postransplant negave HLA recipients
Postransplant HLA non DSA recipients
Postransplant DSA recipients
(n=300)
(n=55)
(n=38)
HLA class I
HLA class I&II
(n=12)
(n=9)
HLA
DSA HLA class I
DSA HLA class I&II
DSA HLA class II
(n=2)
(n=2)
(n=34)
class II (n=34)
Figure 1: Patient flow chart.
categorical variables. Multivariate analysis was employed to look for factors associated with the detection of posttransplant DSA. Goodness of fit for the model was assessed by means of a ROC curve with 95% confidence interval. The studies were performed using software SPSS v.21.
Results Clinical characteristics of kidney transplant recipients according to anti-HLA antibody status Kidney allograft recipients (n ¼ 393) were tested for antiHLA antibodies and immunophenotypic analyses, a median of 58 months after transplantation (IQR 18–127 months). Anti-HLA antibodies were detectable in 93 patients: 38 DSA (2 anti-class I, 34 anti-class II, 2 I þ II) and 55 anti-HLA nonDSA (12 anti-class I, 34 anti-class II, 9 I þ II). According to their baseline characteristics (Table 1), HLA non-DSA and DSA cases were more frequently females and retransplants compared with patients with no antibodies. DR mismatching was greater in DSA patients. Data on renal function and immunosuppressive treatment were collected at the time antibody tests and immunophenotyping were performed (Table 2). Patients with DSA developed a higher rate of acute rejection than HLA non-DSA recipients 808
(p ¼ 0.04). Median postransplantation time to acute rejection was 23 days (IQR 9–159), without significant differences between patients with DSA versus no DSA. Patients with DSA showed higher proteinuria but similar eGFR than those without anti-HLA antibodies. We did not find significant differences between groups in immunosuppressive treatment. After a similar follow-up period, graft loss was more frequent in the DSA group (p ¼ 0.003). NK-cell immunophenotypic profile As shown in Table 3, the proportions of CD3þ T cells were lower in patients without antibodies than in HLA non-DSA, and the percentage of CD19þ B cells were similar in the three groups. Both DSA and HLA non-DSA groups displayed a lower percentage of CD3CD56þNK-cells, and the absolute NK-cell numbers were significantly reduced in DSA cases. Analysis of different NK-cell subsets revealed that the DSA group displayed a higher percentage of CD56bright and NKG2Aþ NK-cells, together with a lower percentage of CD56dim NK-cells, as compared to patients without antibodies and to the HLA non-DSA group, which displayed an intermediate phenotypic profile. Higher percentages of CD56dimNKG2AþNK-cells were also significantly associated to DSA (Figure 2). Of note, the absolute numbers of American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies Table 1: Baseline characteristics in patients with anti-HLA antibodies (DSA or HLA non-DSA) and without anti-HLA antibodies No antibodies n ¼ 300
Anti-HLA non-DSA n ¼ 55
Anti-HLA DSA n ¼ 38
p1
p2
p3
49.8 14 32 90.7 9.0 2.5 8.2 0.1 1.3 1.0 3.4 86 26.8 76.7 87.7 37.3 15.7 6.0
48.1 15.4 70.9 89.1 34.5 9.5 16.7 1.0 3.8 7.3 37.1 73.6 32.1 74.5 83.6 38.2 16.4 1.8
45.9 13.7 47.4 92.1 47.4 14.7 23.7 6.3 14.8 21.1 66.7 97.2 35.1 73.7 89.5 39.5 7.9 13.2
0.43 0.000 0.71 0.000 0.003 0.096 0.02 0.000 0.02 0.67 0.94 0.41 0.90 0.89 0.20
0.47 0.02 0.73 0.21 0.25 0.04 0.06 0.02 0.003 0.95 0.96 0.42 0.9 0.23 0.04
0.1 0.06 0,77 0.000 0.003 0.01 0.000 0.000 0.06 0.53 0.87 1 0.79 0.33 0.09
Recipient age (years) Female recipient (%) Deceased donor (%) Retransplantation (%) Peak PRA CDC (%) Pretransplant PRA CDC (%) Pretransplant PRA CDC >5% Pretransplant SAB DSA (%) DR mismatches >0 (%) Antilymphocyte induction (%) Initial tacrolimus (%) Initial mycophenolic acid (%) Delayed graft function (%) CMV disease (%) Acute rejection (%)
p1, p-value for statistical differences between No antibody and HLA non-DSA; p2, p-value for statistical differences between HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups. PRA, panel reactive antibodies; CDC, complement-dependent cytotoxicity; SAB, single antigen beads. Results are expressed as mean and SD or percentages.
CD56bright, CD56þNKG2Aþ and CD56dimNKG2Aþ cells were not significantly increased in the DSA group, in contrast to the reduction of both the proportions and absolute numbers of the major CD56dimNK-cell subset. The distribution of NKG2Cþ, KIRþ or CD161þNK-cell subsets appeared similar in the three groups of patients, but ILT2 (LILRB1) expression appeared increased in the HLA non-DSA group.
HLA non-DSA (n ¼ 19) and No antibody (n ¼ 27), we obtained similar results (data not shown).
When we compared the NK-cell immunophenotypic profile between the 64 retransplant patients with DSA (n ¼ 18),
Multivariate logistic regression analysis comparing DSA patients (n ¼ 38) with those without antibodies (n ¼ 300)
NK-cell markers were assessed at a median postransplant time of 58 months. When we compared the NK-cell profiles detected before and after this time point, the differences between the groups persisted (data not shown).
Table 2: Clinical characteristics at the time of antibody tests and immunophenotyping in patients with anti-HLA antibodies (DSA or HLA nonDSA) and without anti-HLA antibodies
Creatinine (mg/dL) (mean SD) MDRD-4 eGFR (mL/min) (mean SD) Urinary protein/creatinine (mg/mg) (median, IQR) Steroid treatment (%) Tacrolimus treatment (%) Cyclosporine treatment (%) mTOR inhibitors treatment (%) Mycophenolic treatment (%) Follow-up months after tests: median (IQR) Graft loss at last follow-up (death censored)
No antibodies (n ¼ 300)
Anti-HLA non-DSA (n ¼ 55)
Anti-HLA DSA (n ¼ 38)
p1
p2
p3
1.5 0.6 54.9 20.6 158 (94.8–158)
1.6 0.8 45.7 18.1 183.6 (83.8–404.5)
1.7 0.8 51.6 26.3 238.2 (105.5–463.8)
0.19 0.002 0.58
0.82 0.2 0.247
0.17 0.46 0.05
53% 77.7% 9.3% 8.3% 78.8% 21 (9–27)
63.6% 80% 10.9% 3.6% 72.7% 21 (8–25)
68.4% 65.8% 13.2% 15.8% 78.9% 21 (18–24.2)
0.14 0.7 0.71 0.32 0.4 0.46
0.63 0.12 0.74 0.06 0.49 0.49
0.07 0.1 0.45 0.13 0.98 0.16
3%
7.3%
13.2%
0.12
0.47
0.003
p1, p-value for statistical differences between No antibody and anti-HLA non-DSA; p2, p-value for statistical differences between anti-HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups.
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Crespo et al Table 3: NK-cell immunophenotypic profile in patients without and with anti-HLA antibodies (DSA and HLA non-DSA) No antibodies (n ¼ 300) median [IQR] Lymphocytes/mL %CD3þ %CD19þ CD3CD56þ (cells/mL) %CD3CD56þ %CD3CD56bright %CD3CD56dim %CD3CD56þNKG2Aþ %CD3CD56þNKG2Cþ %CD3CD56þILT2þ %CD3CD56þKIRþ %CD3CD56þCD161þ Posttransplant time at testing (months) median (IQR)
2.050 79.3 5.9 213.70 10.4 5.7 94.30 36.8 18.3 52.4 60.1 67.8 55
(1.602–2.567) (70.9–85.1) (3.6–8.6) (125.4–349.4) (6.6–17.3) (3.6–9.7) (90.4–96.4) (22.6–53.0) (8.7–36.7) (33.4–68.7) (49.6–71.0) (50.5–79.9) (17–122)
Anti-HLA non-DSA (n ¼ 55) median [IQR] 2.080 83.5 5.3 186 8.7 7.3 92.6 43.3 16.8 55.2 56.8 67.4 83
(1.670–2.920) (75.8–87.6) (3.4–8.1) (105.6–323.9) (4.9–15) (4.0–10.4) (89.2–95.9) (32.7–61) (8–31.9) (39.5–67.9) (47.6–66.7) (55.8–78.0) (22–144)
Anti-HLA DSA (n ¼ 38) median [IQR] 1.745 80.9 6.6 166.7 8.5 11.5 88.47 53.9 14.3 43.3 56.5 72.9 59.5
(1.332–2.410) (73.2–85) (4–9.5) (78–239.6) (4.9–14.2) (6.4–15.9) (84–93.6) (42.6–70) (9.8–19.8) (29.5–57.7) (40.2–70.2) (59.7–80.4) (19.25–140.75)
p1
p2
p3
0.52 0.01 0.29 0.29 0.09 0.04 0.04 0.01 0.66 0.56 0.12 0.79 0.14
0.07 0.26 0.20 0.12 0.57 0.02 0.02 0.01 0.43 0.04 0.66 0.28 0.38
0.09 0.29 0.49 0.009 0.03 0.000 0.000 0.000 0.2 0.077 0.11 0.16 0.83
p1, p-value for statistical differences between No antibody and anti-HLA non-DSA; p2, p-value for statistical differences between anti-HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups. Results are expressed as median and IQ range.
showed that retransplantation and a higher percentage of NKG2Aþ cells were significantly associated with the presence of DSA (OR 1.036 per 1% increase in NKG2Aþ) (Table 4). Similar analysis comparing DSA (n ¼ 38) and HLA non-DSA (n ¼ 55) patients indicated that female gender, DR mismatches, acute rejection and an increased percentage of NKG2Aþ cells were more frequent in patients with DSA (OR 1.041 per 1% increase in NKG2Aþ) (Table 5). Regarding graft function, a correlation between NKG2Aþ cells and serum creatinine (r2 ¼ 0.28, p ¼ 0.03) and eGFR (r2 ¼ -0.32, p ¼ 0.052) was observed in patients with DSA (n ¼ 38) (Figure 3), but not in patients with HLA non-DSA or in patients without antibodies. When we compared DSA patients with NKG2Aþ > 40% (n ¼ 30) and those with NKG2Aþ < 40% (n ¼ 8), we observed a higher serum creatinine (1.82 0.83 vs. 1.17 0.46 mg/dL, p ¼ 0.04) and protein to creatinine ratio in urine (PCOR) (368 372 vs. 209 124 mg/mg, p ¼ 0.057) in those DSA patients with NKG2Aþ > 40%.
The relationship of NK-cell subset distribution and biopsy findings Among the 38 patients with DSA, 29 were biopsied a median of 14 months (IQ: 3,5–20,5) after detection of DSA positivity and NK-cell analysis. Of them, 23 patients had antibody-mediated changes, and showed significantly higher %CD3CD56þNKG2Aþ than the 6 DSA without these lesions (63.3% [IQR:45.4,72.4] vs. 44.4% [IQR:33. 9,51.6], p ¼ 0.03)(Figure 3B). We did not find any correlation between the NK-cell profile and C4d deposits or the existence of transplant glomerulopathy. 810
The relation of DSA with NK-cell subset distribution is independent of immunosuppression We addressed whether immunosuppressive drugs could be a confounding factor in the distribution of peripheral NK-cells according to the presence of posttransplant DSA. We selected 302 patients who were receiving tacrolimus at the study point. We confirmed a higher NKG2Aþ percentage in DSA (n ¼ 25) compared to HLA non-DSA patients (n ¼ 44) (61% [IQR:44.4,70.7] vs. 41.3% [IQR:33,59.5], p ¼ 0.003). A higher percentage was also observed in HLA non-DSA patients than in the 233 cases without antibodies (36.3% [IQR:21.3,51.2], p ¼ 0.02). Moreover, DSA patients showed lower percentages of CD56dim and higher percentage of CD56bright cells than cases without anti-HLA antibodies. Analysis of patients without tacrolimus but on treatment with mTOR inhibitors (n ¼ 33) also showed higher percentages of CD56bright and NKG2Aþ cells (p ¼ 0.02 and p ¼ 0.07) and lower percentage of CD56dim cells (p ¼ 0.02) in DSA (n ¼ 6), compared with cases without antibodies (n ¼ 25).
Discussion In the present study, we explored the potential relationship of circulating DSA and HLA non-DSA with peripheral blood NK-cells and clinical features in 393 renal allograft recipients. Patients with DSA displayed lower proportions of peripheral NK-cells than those without antibodies. Moreover, higher proportions of CD56bright and NKG2AþNK-cells, together with a lower percentage and absolute numbers of the CD56dim subset, were detected in DSA and HLA non-DSA American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies
Figure 2: NK-cell distribution in kidney transplant recipients related to the detection of postransplant anti-HLA antibodies. NK cell subsets were analyzed by flow cytometry in peripheral blood from kidney transplant recipients. (A) Representative dot–plots showing the gating strategy used to define CD3CD56þ, CD3CD56dim and CD3CD56bright NK-cells. (B) Graph showing the percentage of NK-cell subsets. Patients were subdivided in three categories according to the absence (No antibodies) or presence of postransplant anti-HLA antibodies, either donor specific (DSA) or HLA nondonor specific (HLA non-DSA). Statistical analysis was performed using nonparametric tests.
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Crespo et al Table 4: Multivariate analysis for features associated with posttransplant DSA in kidney graft recipients when comparing DSA patients (n ¼ 38) with patients without anti-HLA antibodies (n ¼ 300) OR Retransplantation % CD3CD56þ NKG2Aþ cells Pretransplant PRA CDC (%) Recipient age at transplant Recipient male gender HLA DR mismatches Acute rejection
5.379 1.036 1.108 0.992 1.196 1.513 2.253
CI 95% 2.183 1.013 0.986 0.963 0.524 0.794 0.587
13.250 1.059 1.247 1.022 2.726 2.885 8.641
p 0.000 0.002 0.086 0.584 0.671 0.208 0.236
Discrimination power, AUC (95%IC) 0.821 (0.743–0.899).
patients, as compared to cases without antibodies. Remarkably, the percentage of CD56bright and NKG2Aþ NK-cells were significantly higher in DSA than in HLA nonDSA cases. Our results are in line with a recent study involving 124 patients mainly during the first year posttransplant, in which reduced numbers of CD56dim NK-cells were reported in patients with DSA (22). Based on a larger and longer-term cohort we confirmed this finding, observing in addition a significant increase of the percentage of CD56bright NK-cells in DSAþ kidney recipients. Moreover, this phenotypic profile as well as an increase in the percentage of NKG2Aþ cells, were also significantly different comparing DSA with HLA non-DSA recipients, independently of immunosuppression. Our findings suggest that anti-HLA antibodies, particularly DSA, might selectively influence the NK-cell subset distribution. NK-cells are major effectors of ADCC through the FcgR-IIIA (CD16) receptor, a function that may be triggered by HLA-specific alloantibodies and has been proposed to contribute to allograft rejection (23,24). Of note, CD16 is expressed by the CD56dim NK-cell subset but is virtually absent in CD56bright NK-cells (15). On the other hand, CD16 surface expression is down-regulated in activated NK-cells through a shedding process mediated by ADAM-17 (25). As NK-cell apoptosis was associated to
Table 5: Multivariate analysis for features associated with posttransplant DSA in kidney graft recipients comparing DSA (n ¼ 38) with HLA non-DSA patients (n ¼ 55) OR HLA DR mismatches %CD3CD56þ NKG2Aþ cells Recipient female gender Acute rejection Pretransplant PRA CDC (%) Recipient age at transplant Retransplantation
5.970 1.041 3.690 16.513 1.063 0.985 0.927
CI 95% 2.147 1.007 1.192 1.429 0.992 0.949 0.285
16.605 1.076 11.363 190.833 1.138 1.022 3.018
Discrimination power, AUC (95%IC) 0.729 (0.641–0.817).
812
p 0.001 0.018 0.024 0.025 0.085 0.428 0.900
Figure 3: (A) Correlation between the percentage of NKG2Aþ cells and serum creatinine in patients with DSA. (B) Comparison of the percentage of NKG2Aþ between DSA patients with and without ABMR changes in their biopsies (according to 2009 Banff classification).
ADCC (26) it is plausible that DSA might enhance the turnover of circulating NK-cells. This hypothesis would be consistent with the observed increase of CD56bright NKcells, which lack the FcgR-IIIA receptor being spared from the effect of alloantibodies. Moreover, most CD56bright NKcells are NKG2Aþ and would contribute to increase the proportions of this subset. Yet, an association of anti-HLA antibodies with higher percentage of CD56dimNKG2AþNKcells was also noticed. In this regard, it is conceivable that engagement of the CD94/NKG2A inhibitory receptor by HLA-E might dampen the alloantibody effect. Predictably, this effect would take place in every transplant, as the HLAE dimorphism does not significantly influence CD94/ NKG2A recognition (27). By contrast, the effect of alloantibodies on CD56dimNKG2ANK-cells would vary depending American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies
on recipient KIR-donor HLA class I matching, as well as on the distribution of different KIRþ NK-cell subsets (28). Further studies are required to address this hypothesis, considering as well whether CD16 polymorphisms which influence ADCC might modulate the pathogenic effect of alloantibodies (29). Increased NKG2AþNK-cells were also detected in HLA nonDSA patients, as compared with those without antibodies. Two nonexclusive interpretations may be proposed to explain this observation. First, low concentrations of circulating DSA, undetectable by the SAB assay, might be retained on the graft endothelium and stimulate NK-cells via CD16 (30). Second, non-HLA DSA could be present in some of these HLA non-DSA patients. Eventually, some HLA non-DSA antibodies might establish low-affinity crossreactive interactions with graft alloantigens, engaging NKcell FcgR-IIIA receptors. Given its exploratory nature, our study does not provide a precise assessment of the NK-cell immunophenotype as a predictive biomarker to derive clinical and therapeutic implications, and the limited follow-up after HLA antibody testing and NK-cell immunophenotyping restricts the possibility to explore the impact of combining both studies to predict graft failure. These aspects may be considered in future prospective assessments. In the context of the working hypothesis, other relevant variables should also be assessed in these future prospective studies, particularly the expression of individual KIR, together with KIR and donor HLA class I genotyping, as well as CD16 expression and CD16 gene polymorphisms known to influence ADCC. Studying additional NK-cell markers would potentially enrich the picture, taking into account factors that may influence their expression. In summary, transplant recipients with DSA after kidney transplantation display lower proportions of peripheral NKcells and of the major CD56dim subset than recipients without antibodies. Only the percentages of CD56bright and CD56dim NKG2Aþ cells but not their absolute numbers were higher in patients with antibodies, especially DSA. The observed NK-cell subset redistribution might reflect an enhanced antibody-dependent turnover following activation via CD16. A future working hypothesis may be that the increased percentage of NKG2Aþ NK-cells indirectly reflects their relative resistance to this process, thus becoming a potential marker of ongoing DSA-mediated tissue damage in patients with chronic ABMR.
Acknowledgments We are indebted to our nurse staff particularly the coordinators Anna Faura, Sara Alvarez and Rosa Causadias for their excellent job with all these patients. We thank Dulce Soto for her technical assistance in flow cytometry analysis. This study was performed with funding from the projects PI10/ 01370 and PI13/00598 (Spanish Ministry of Health ISCIII FIS-FEDER), Marato TV3 137/C/2012, RedinRen RD12/0021/0024 and Plan Nacional de
American Journal of Transplantation 2015; 15: 806–814
~ola I þ D (SAF2010-22153-C03). AM is supported by Asociacio´n Espan Contra el Ca´ncer (AECC).
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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23. Van der Touw W, Burrell B, Lal G, Bromberg JS. NK-cells are required for costimulatory blockade induced tolerance to vascularized allografts. Transplantation 2012; 94: 575–584. 24. Farkash EA, Colvin RB. Diagnostic challenges in chronic antibodymediated rejection. Nat Rev Nephrol 2012; 8: 255–257. 25. Romee R, Foley B, Lenvik T, et al. NK cell CD16 surface expression and function is regulated by a disintegrin and metalloprotease-17 (ADAM17). Blood 2013; 121: 3599–3608. 26. Ortaldo JR, Mason AT, O’Shea JJ. Receptor-induced death in human natural killer cells: Involvement of CD16. J Exp Med 1995; 181: 339–344. 27. Kaiser BK, Barahmand-Pour F, Paulsene W, et al. Interactions between NKG2x immunoreceptors and HLA-E ligands display overlapping affinities and thermodynamics. J Immunol 2005; 174: 2878–2884. 28. Vilches C, Parham P, KIR: Diverse, rapidly evolving receptors of innate and adaptive immunity. Annu Rev Immunol 2002; 20: 217–251. 29. Veeramani S, Wang SY, Dahle C, et al. Rituximab infusion induces NK activation in lymphoma patients with the high-affinity CD16 polymorphism. Blood 2011; 118: 3347–3349. 30. Martin L, Guignier F, Bocrie O, et al. Detection of anti-HLA antibodies with flow cytometry in needle core biopsies of renal transplants recipients with chronic allograft nephropathy. Transplantation 2005; 79: 1459–1461.
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Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13010
Brief Communication
Circulating NK-Cell Subsets in Renal Allograft Recipients With Anti-HLA Donor-Specific Antibodies M. Crespo1,2,*, J. Yelamos2,3, D. Redondo1,2, A. Muntasell2, M. J. Perez-Sae´z1, ~ e´s4, C. Garcı´a5, A. Torio6, M. Lo´pez-Montan y 1 M. Mir , J. J. Herna´ndez5, M. Lo´pez-Botet2,3,4, y and J. Pascual1,2,
Abbreviations: ABMR, antibody-mediated rejection; ADCC, antibody-dependent cell mediated cytotoxicity; CDC, complement-dependent cytotoxicity; DSA, donor specific-antibodies; IQR, interquartilic range; MFI, mean fluorescence intensity; NK, natural killer; SAB, single antigen beads
1
Received 28 May 2014, revised 02 September 2014 and accepted for publication 06 September 2014
Department of Nephrology, Hospital del Mar, Barcelona, Spain 2 Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain 3 Department of Immunology, Hospital del Mar, Barcelona, Spain 4 Universitat Pompeu Fabra, Barcelona, Spain 5 Catalunya Reference Laboratory, El Prat de Llobregat Barcelona, Spain 6 Immunology Unit, Complejo Hospitalario Insular Materno Infantil, Las Palmas de Gran Canaria, Spain Corresponding author: Marta Crespo, [email protected] y Both authors contributed equally.
Detection of posttransplant donor-specific anti-HLA antibodies (DSA) constitutes a risk factor for kidney allograft loss. Together with complement activation, NK-cell antibody-dependent cell mediated cytotoxicity (ADCC) has been proposed to contribute to the microvascular damage associated to humoral rejection. In the present observational exploratory study, we have tried to find a relationship of circulating donor-specific and nondonor-specific anti-HLA antibodies (DSA and HLA non-DSA) with peripheral blood NK-cell subsets and clinical features in 393 renal allograft recipients. Multivariate analysis indicated that retransplantation and pretransplant sensitization were associated with detection of posttransplant DSA. Recipient female gender, DR mismatch and acute rejection were significantly associated with posttransplant DSA compared to HLA non-DSA. In contrast with patients without detectable anti-HLA antibodies, DSA and HLA non-DSA patients displayed lower proportions of NK-cells, associated with increased CD56bright and NKG2Aþ subsets, the latter being more marked in DSA cases. These differences appeared unrelated to retransplantation, previous acute rejection or immunosuppressive therapy. Although preliminary and observational in nature, our results suggest that the assessment of the NK-cell immunophenotype may contribute to define signatures of alloreactive humoral responses in renal allograft recipients. 806
Introduction Posttransplant donor-specific anti-HLA antibodies (DSA) are increasingly recognized as risk factors for kidney allograft loss (1–4). Detection of DSA together with typical histological changes and the presence of complement C4d deposits in peritubular capillaries in kidney graft biopsies were the criteria established for the diagnosis of antibodymediated rejection (ABMR) a decade ago (5). Nevertheless, several reports have found that microvascular damage is the cornerstone of chronic humoral rejection which may occur in the absence of complement deposition in the tissue (6–10). Some groups have hypothesized that effector mechanisms other than complement may be activated in the presence of posttransplant DSA (8,9). Activation of natural killer (NK) cells through FcgR-IIIA (CD16) to mediate antibody-dependent cell-mediated cytotoxicity (ADCC) has been proposed to play a role (9). An involvement of NK-cells in ABMR was supported by differential gene expression analysis in graft biopsies (10–12). Patients with DSA and microcirculation damage displayed increased expression of a subset of NK-cell-related genes, and biopsies showed that CD56þ cells were increased in ABMR compared with T cellmediated rejection, compatible with a role for NK-cells as potential effectors in endothelial injury (16). NK-cell effector functions are regulated by inhibitory and activating receptors. Among them, the CD94/NKG2A heterodimer and members of the killer immunoglobulinlike receptor (KIR) family repress NK-cell functions interacting with HLA-E and distinct sets of classical HLA class I molecules (13,14). The combinatorial distribution of these receptors determines the existence of different NK-cell subsets capable of responding against pathological cells which down-regulate HLA class I expression, as well as against normal allogeneic cells lacking the appropriate HLA ligands. CD56bright and CD56dim NK cell subsets represent
NK-Cell Subsets and Donor-Specific Antibodies
different stages of differentiation, which display distinct phenotypic and functional profiles (15). Most CD56bright NKcells, which constitute a minor proportion of circulating NKcells, express the CD94/NKG2A inhibitory receptor as well as activating NKG2D and natural cytotoxicity receptors, but lack KIR and CD16. CD56brightNK-cells secrete pro-inflammatory cytokines, have a low cytotoxic potential and are believed to differentiate into the more abundant and functionally mature CD16þNKG2DþCD56dim NK-cells. This population contains distinct subsets (e.g. NKG2AþKIRþ, NKG2ANKG2CþKIRþ, NKG2ANKG2C) which reflect further differentiation events, partially resulting from the influence of cytomegalovirus infection (16,17). The putative influence of NK-cell alloreactivity in solid organ transplantation has been addressed based on the genetic analysis of KIR–HLA mismatch with conflicting results (18,19). In the present study, we explored the potential relationship between circulating anti-HLA antibodies, clinical features and the distribution of peripheral blood NK-cell subsets in a large population of kidney transplant recipients, followed-up for an extended time period. Rather than comparing patients with and without DSA (2,3), we categorized them in three groups, i.e. without anti-HLA antibodies, with anti-HLA DSA and antiHLA non-DSA. Our results indicate that patients with DSA display lower numbers of circulating NK-cells, associated with higher proportions of the CD56bright and NKG2Aþ subsets.
Methods Patient population From 1979 to March 2012, 849 kidney transplants were performed at our institution. Of them, 441 patients over 3 months after transplantation who attended the outpatient clinic from 2008 to March 2012 were recruited. The study was approved by the Hospital Research Ethical Committee (2010/3904/I) and all patients signed informed consents. Periodical posttransplant serum samples were monitored for anti-HLA antibodies with Luminex technology. Peripheral blood immunophenotyping together with HLA antibody tests were performed once between April 2011 and December 2012 in 393 patients (Figure 1). A database including clinical and functional information contemporarily with antibody and immunophenotyping tests was filled.
Cross-match and HLA typing All patients were transplanted with a negative complement-dependent cytotoxicity (CDC) cross-match with mixed lymphocytes. Before 2000, HLA Class I and II antigens (HLA-A, -B, -DR) were determined by CDC technique. Low resolution DNA typing was performed using PCR–SSP commercial kits for donors and PCR–SSO for receptors afterwards. When anti-DQ antibodies were detected by single antigen beads (SAB), assignation as DSA was made by HLA-DQB1 genotyping of the donor by PCR–SSP or based on linkage disequilibrium when donor DNA samples were not available. Since no data for donor HLA-C or DP were available, antiC or anti-DP antibodies were not considered in the analysis.
using the Luminex Lifecodes LifeScreen Deluxe assay (Gen-probe, Stanford, CT), according to the manufacturer instructions. The kit was composed of seven beads coated with HLA Class I molecules and five beads coated with HLA Class II molecules. Briefly, 5 mL of multiplexed microbeads were incubated with 12.5 mL of serum for 30 min and washed three times to remove unbound antibody. 50 mL of anti-human IgG antibody conjugated to phycoerythrin was added for 30 min. Samples were analyzed on a Luminex 200 instrument (Luminex1, Austin, TX) using Bio-Plex Manager 6.0 as software for data acquisition, and MatchIt! Antibody v1.1.0.2 (Gen-Probe) program as analysis software. A bead was considered positive if more than 2 of the 3 adjusted ratio values (AR) were higher than 5. The AR values were calculated dividing the individual bead median fluorescence intensity (MFI) by the MFI of three negative control beads, and subtracting the background adjustment factor for each appropriate bead-control combination. A sample was considered positive for HLA-specific antibodies if at least one of the beads was positive. Positive and negative control sera were included in each test. Anti-HLA alloantibody IgG identification was performed using the Lifecodes LSA Class I and/or Class II assays (Gen-probe), according to the manufacturer instructions. The LSA Class I kit was composed of 93 beads coated with HLA Class I molecules (HLA-A, -B, -C), and LSA Class II kit was composed of 84 beads coated with HLA Class II molecules (HLA-DR, -DQ, -DP). Data were analyzed using MatchIT software, and the cutoff for a positive reaction was set in MFI > 1000. Donor HLA antibody specificity was ascribed considering donor HLA A, B, DRB and some DQB typing. Antibodies against C or most DQ antigens were assigned considering linkage disequilibrium.
Immunophenotypic analysis Immunophenotyping was performed by flow cytometry on fresh peripheral blood samples, obtained by venous puncture in EDTA tubes. Samples were pretreated with saturating concentrations of human aggregated immunoglobulins (Ig) to block FcgR and then labeled with different antibody combinations to define total T and B lymphocytes and NK-cell subsets. For direct immunofluorescence staining we used the following antibodies: FITC-CD3 (Clone SK7), APC-CD3 (Clone SK7), PerCP-CD45 (Clone 2D1), APC-CD45 (Clone 2D1), PerCP-CD19 (Clone SJ25C1), FITC-CD56 (Clone NCAM16.2), from BD biosciences. NK-cells were defined as CD3CD56þ lymphocytes; CD56dim and CD56bright subsets were identified according to the staining intensity with the specific monoclonal antibody. Additional NK-cell subsets were identified by indirect immunofluorescence staining using the following antibodies specific for: NKG2A (clone Z199; provided by Dr. A. Moretta), NKG2C (clone MAB1381; R&D systems, Minneapolis, MN), ILT2 (LILRB1) (clone HP-F1; generated in our lab) (20) and CD161 (clone HP-3G10, generated in our lab). KIR staining was performed using a mixture of antibodies specific for KIR3DL1/L2 (clone 5.133, provided by Dr. M. Colonna), KIR2DL2/S2/L3 (clone CH-L, provided by Dr. S. Ferrini), KIR3DL1 (clone DX9, provided by Dr. L. L. Lanier), and KIR2DL1/S1/S4 (clone HP-3E4, generated in our lab) (21). PE-conjugated F(ab’)2 rabbit anti-mouse Ig (Dako, Glostrup, Denmark) was used as secondary antibody. After washing and erythrocyte lysis, samples were acquired with a FACScalibur1 cytometer and the data analyzed with the CellQuest software (BD Biosciences). Absolute numbers of cells were calculated from blood counts obtained in parallel. The percentages of CD3þ, CD19þ and CD3CD56þ cells are referred to total lymphocytes; the percentages of CD3CD56bright, CD3CD56dim, CD3CD56þNKG2Aþ, CD3CD56þNKG2Cþ, CD3CD56þILT2þ, CD3CD56þKIRþ and CD3CD56þCD161þ are referred to NK-cells (CD3CD56þ).
Statistical analysis Anti-HLA antibody screening and characterization Pre and posttransplant serum samples were collected and freshly processed or stored at 808C until use. Screening for anti-HLA antibodies was performed
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Comparisons between clinical variables were carried out using Student’s ttest for parametric continuous variables and U Mann–Whitney test for nonparametric data. Chi-squared or Fisher’s exact tests were used to test
807
Crespo et al Recruitment of all funconing kidney transplants (2008-2012) n=441
Excluded (n=48) -
393 transplant recipients
Gra loss: dialysis (n=22), retransplant (n=5) Loss to follow-up (n=3) Death with funcon (n=14)
Postransplant negave HLA recipients
Postransplant HLA non DSA recipients
Postransplant DSA recipients
(n=300)
(n=55)
(n=38)
HLA class I
HLA class I&II
(n=12)
(n=9)
HLA
DSA HLA class I
DSA HLA class I&II
DSA HLA class II
(n=2)
(n=2)
(n=34)
class II (n=34)
Figure 1: Patient flow chart.
categorical variables. Multivariate analysis was employed to look for factors associated with the detection of posttransplant DSA. Goodness of fit for the model was assessed by means of a ROC curve with 95% confidence interval. The studies were performed using software SPSS v.21.
Results Clinical characteristics of kidney transplant recipients according to anti-HLA antibody status Kidney allograft recipients (n ¼ 393) were tested for antiHLA antibodies and immunophenotypic analyses, a median of 58 months after transplantation (IQR 18–127 months). Anti-HLA antibodies were detectable in 93 patients: 38 DSA (2 anti-class I, 34 anti-class II, 2 I þ II) and 55 anti-HLA nonDSA (12 anti-class I, 34 anti-class II, 9 I þ II). According to their baseline characteristics (Table 1), HLA non-DSA and DSA cases were more frequently females and retransplants compared with patients with no antibodies. DR mismatching was greater in DSA patients. Data on renal function and immunosuppressive treatment were collected at the time antibody tests and immunophenotyping were performed (Table 2). Patients with DSA developed a higher rate of acute rejection than HLA non-DSA recipients 808
(p ¼ 0.04). Median postransplantation time to acute rejection was 23 days (IQR 9–159), without significant differences between patients with DSA versus no DSA. Patients with DSA showed higher proteinuria but similar eGFR than those without anti-HLA antibodies. We did not find significant differences between groups in immunosuppressive treatment. After a similar follow-up period, graft loss was more frequent in the DSA group (p ¼ 0.003). NK-cell immunophenotypic profile As shown in Table 3, the proportions of CD3þ T cells were lower in patients without antibodies than in HLA non-DSA, and the percentage of CD19þ B cells were similar in the three groups. Both DSA and HLA non-DSA groups displayed a lower percentage of CD3CD56þNK-cells, and the absolute NK-cell numbers were significantly reduced in DSA cases. Analysis of different NK-cell subsets revealed that the DSA group displayed a higher percentage of CD56bright and NKG2Aþ NK-cells, together with a lower percentage of CD56dim NK-cells, as compared to patients without antibodies and to the HLA non-DSA group, which displayed an intermediate phenotypic profile. Higher percentages of CD56dimNKG2AþNK-cells were also significantly associated to DSA (Figure 2). Of note, the absolute numbers of American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies Table 1: Baseline characteristics in patients with anti-HLA antibodies (DSA or HLA non-DSA) and without anti-HLA antibodies No antibodies n ¼ 300
Anti-HLA non-DSA n ¼ 55
Anti-HLA DSA n ¼ 38
p1
p2
p3
49.8 14 32 90.7 9.0 2.5 8.2 0.1 1.3 1.0 3.4 86 26.8 76.7 87.7 37.3 15.7 6.0
48.1 15.4 70.9 89.1 34.5 9.5 16.7 1.0 3.8 7.3 37.1 73.6 32.1 74.5 83.6 38.2 16.4 1.8
45.9 13.7 47.4 92.1 47.4 14.7 23.7 6.3 14.8 21.1 66.7 97.2 35.1 73.7 89.5 39.5 7.9 13.2
0.43 0.000 0.71 0.000 0.003 0.096 0.02 0.000 0.02 0.67 0.94 0.41 0.90 0.89 0.20
0.47 0.02 0.73 0.21 0.25 0.04 0.06 0.02 0.003 0.95 0.96 0.42 0.9 0.23 0.04
0.1 0.06 0,77 0.000 0.003 0.01 0.000 0.000 0.06 0.53 0.87 1 0.79 0.33 0.09
Recipient age (years) Female recipient (%) Deceased donor (%) Retransplantation (%) Peak PRA CDC (%) Pretransplant PRA CDC (%) Pretransplant PRA CDC >5% Pretransplant SAB DSA (%) DR mismatches >0 (%) Antilymphocyte induction (%) Initial tacrolimus (%) Initial mycophenolic acid (%) Delayed graft function (%) CMV disease (%) Acute rejection (%)
p1, p-value for statistical differences between No antibody and HLA non-DSA; p2, p-value for statistical differences between HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups. PRA, panel reactive antibodies; CDC, complement-dependent cytotoxicity; SAB, single antigen beads. Results are expressed as mean and SD or percentages.
CD56bright, CD56þNKG2Aþ and CD56dimNKG2Aþ cells were not significantly increased in the DSA group, in contrast to the reduction of both the proportions and absolute numbers of the major CD56dimNK-cell subset. The distribution of NKG2Cþ, KIRþ or CD161þNK-cell subsets appeared similar in the three groups of patients, but ILT2 (LILRB1) expression appeared increased in the HLA non-DSA group.
HLA non-DSA (n ¼ 19) and No antibody (n ¼ 27), we obtained similar results (data not shown).
When we compared the NK-cell immunophenotypic profile between the 64 retransplant patients with DSA (n ¼ 18),
Multivariate logistic regression analysis comparing DSA patients (n ¼ 38) with those without antibodies (n ¼ 300)
NK-cell markers were assessed at a median postransplant time of 58 months. When we compared the NK-cell profiles detected before and after this time point, the differences between the groups persisted (data not shown).
Table 2: Clinical characteristics at the time of antibody tests and immunophenotyping in patients with anti-HLA antibodies (DSA or HLA nonDSA) and without anti-HLA antibodies
Creatinine (mg/dL) (mean SD) MDRD-4 eGFR (mL/min) (mean SD) Urinary protein/creatinine (mg/mg) (median, IQR) Steroid treatment (%) Tacrolimus treatment (%) Cyclosporine treatment (%) mTOR inhibitors treatment (%) Mycophenolic treatment (%) Follow-up months after tests: median (IQR) Graft loss at last follow-up (death censored)
No antibodies (n ¼ 300)
Anti-HLA non-DSA (n ¼ 55)
Anti-HLA DSA (n ¼ 38)
p1
p2
p3
1.5 0.6 54.9 20.6 158 (94.8–158)
1.6 0.8 45.7 18.1 183.6 (83.8–404.5)
1.7 0.8 51.6 26.3 238.2 (105.5–463.8)
0.19 0.002 0.58
0.82 0.2 0.247
0.17 0.46 0.05
53% 77.7% 9.3% 8.3% 78.8% 21 (9–27)
63.6% 80% 10.9% 3.6% 72.7% 21 (8–25)
68.4% 65.8% 13.2% 15.8% 78.9% 21 (18–24.2)
0.14 0.7 0.71 0.32 0.4 0.46
0.63 0.12 0.74 0.06 0.49 0.49
0.07 0.1 0.45 0.13 0.98 0.16
3%
7.3%
13.2%
0.12
0.47
0.003
p1, p-value for statistical differences between No antibody and anti-HLA non-DSA; p2, p-value for statistical differences between anti-HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups.
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Crespo et al Table 3: NK-cell immunophenotypic profile in patients without and with anti-HLA antibodies (DSA and HLA non-DSA) No antibodies (n ¼ 300) median [IQR] Lymphocytes/mL %CD3þ %CD19þ CD3CD56þ (cells/mL) %CD3CD56þ %CD3CD56bright %CD3CD56dim %CD3CD56þNKG2Aþ %CD3CD56þNKG2Cþ %CD3CD56þILT2þ %CD3CD56þKIRþ %CD3CD56þCD161þ Posttransplant time at testing (months) median (IQR)
2.050 79.3 5.9 213.70 10.4 5.7 94.30 36.8 18.3 52.4 60.1 67.8 55
(1.602–2.567) (70.9–85.1) (3.6–8.6) (125.4–349.4) (6.6–17.3) (3.6–9.7) (90.4–96.4) (22.6–53.0) (8.7–36.7) (33.4–68.7) (49.6–71.0) (50.5–79.9) (17–122)
Anti-HLA non-DSA (n ¼ 55) median [IQR] 2.080 83.5 5.3 186 8.7 7.3 92.6 43.3 16.8 55.2 56.8 67.4 83
(1.670–2.920) (75.8–87.6) (3.4–8.1) (105.6–323.9) (4.9–15) (4.0–10.4) (89.2–95.9) (32.7–61) (8–31.9) (39.5–67.9) (47.6–66.7) (55.8–78.0) (22–144)
Anti-HLA DSA (n ¼ 38) median [IQR] 1.745 80.9 6.6 166.7 8.5 11.5 88.47 53.9 14.3 43.3 56.5 72.9 59.5
(1.332–2.410) (73.2–85) (4–9.5) (78–239.6) (4.9–14.2) (6.4–15.9) (84–93.6) (42.6–70) (9.8–19.8) (29.5–57.7) (40.2–70.2) (59.7–80.4) (19.25–140.75)
p1
p2
p3
0.52 0.01 0.29 0.29 0.09 0.04 0.04 0.01 0.66 0.56 0.12 0.79 0.14
0.07 0.26 0.20 0.12 0.57 0.02 0.02 0.01 0.43 0.04 0.66 0.28 0.38
0.09 0.29 0.49 0.009 0.03 0.000 0.000 0.000 0.2 0.077 0.11 0.16 0.83
p1, p-value for statistical differences between No antibody and anti-HLA non-DSA; p2, p-value for statistical differences between anti-HLA non-DSA and DSA; p3, p-value for statistical differences between No antibody and DSA groups. Results are expressed as median and IQ range.
showed that retransplantation and a higher percentage of NKG2Aþ cells were significantly associated with the presence of DSA (OR 1.036 per 1% increase in NKG2Aþ) (Table 4). Similar analysis comparing DSA (n ¼ 38) and HLA non-DSA (n ¼ 55) patients indicated that female gender, DR mismatches, acute rejection and an increased percentage of NKG2Aþ cells were more frequent in patients with DSA (OR 1.041 per 1% increase in NKG2Aþ) (Table 5). Regarding graft function, a correlation between NKG2Aþ cells and serum creatinine (r2 ¼ 0.28, p ¼ 0.03) and eGFR (r2 ¼ -0.32, p ¼ 0.052) was observed in patients with DSA (n ¼ 38) (Figure 3), but not in patients with HLA non-DSA or in patients without antibodies. When we compared DSA patients with NKG2Aþ > 40% (n ¼ 30) and those with NKG2Aþ < 40% (n ¼ 8), we observed a higher serum creatinine (1.82 0.83 vs. 1.17 0.46 mg/dL, p ¼ 0.04) and protein to creatinine ratio in urine (PCOR) (368 372 vs. 209 124 mg/mg, p ¼ 0.057) in those DSA patients with NKG2Aþ > 40%.
The relationship of NK-cell subset distribution and biopsy findings Among the 38 patients with DSA, 29 were biopsied a median of 14 months (IQ: 3,5–20,5) after detection of DSA positivity and NK-cell analysis. Of them, 23 patients had antibody-mediated changes, and showed significantly higher %CD3CD56þNKG2Aþ than the 6 DSA without these lesions (63.3% [IQR:45.4,72.4] vs. 44.4% [IQR:33. 9,51.6], p ¼ 0.03)(Figure 3B). We did not find any correlation between the NK-cell profile and C4d deposits or the existence of transplant glomerulopathy. 810
The relation of DSA with NK-cell subset distribution is independent of immunosuppression We addressed whether immunosuppressive drugs could be a confounding factor in the distribution of peripheral NK-cells according to the presence of posttransplant DSA. We selected 302 patients who were receiving tacrolimus at the study point. We confirmed a higher NKG2Aþ percentage in DSA (n ¼ 25) compared to HLA non-DSA patients (n ¼ 44) (61% [IQR:44.4,70.7] vs. 41.3% [IQR:33,59.5], p ¼ 0.003). A higher percentage was also observed in HLA non-DSA patients than in the 233 cases without antibodies (36.3% [IQR:21.3,51.2], p ¼ 0.02). Moreover, DSA patients showed lower percentages of CD56dim and higher percentage of CD56bright cells than cases without anti-HLA antibodies. Analysis of patients without tacrolimus but on treatment with mTOR inhibitors (n ¼ 33) also showed higher percentages of CD56bright and NKG2Aþ cells (p ¼ 0.02 and p ¼ 0.07) and lower percentage of CD56dim cells (p ¼ 0.02) in DSA (n ¼ 6), compared with cases without antibodies (n ¼ 25).
Discussion In the present study, we explored the potential relationship of circulating DSA and HLA non-DSA with peripheral blood NK-cells and clinical features in 393 renal allograft recipients. Patients with DSA displayed lower proportions of peripheral NK-cells than those without antibodies. Moreover, higher proportions of CD56bright and NKG2AþNK-cells, together with a lower percentage and absolute numbers of the CD56dim subset, were detected in DSA and HLA non-DSA American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies
Figure 2: NK-cell distribution in kidney transplant recipients related to the detection of postransplant anti-HLA antibodies. NK cell subsets were analyzed by flow cytometry in peripheral blood from kidney transplant recipients. (A) Representative dot–plots showing the gating strategy used to define CD3CD56þ, CD3CD56dim and CD3CD56bright NK-cells. (B) Graph showing the percentage of NK-cell subsets. Patients were subdivided in three categories according to the absence (No antibodies) or presence of postransplant anti-HLA antibodies, either donor specific (DSA) or HLA nondonor specific (HLA non-DSA). Statistical analysis was performed using nonparametric tests.
American Journal of Transplantation 2015; 15: 806–814
811
Crespo et al Table 4: Multivariate analysis for features associated with posttransplant DSA in kidney graft recipients when comparing DSA patients (n ¼ 38) with patients without anti-HLA antibodies (n ¼ 300) OR Retransplantation % CD3CD56þ NKG2Aþ cells Pretransplant PRA CDC (%) Recipient age at transplant Recipient male gender HLA DR mismatches Acute rejection
5.379 1.036 1.108 0.992 1.196 1.513 2.253
CI 95% 2.183 1.013 0.986 0.963 0.524 0.794 0.587
13.250 1.059 1.247 1.022 2.726 2.885 8.641
p 0.000 0.002 0.086 0.584 0.671 0.208 0.236
Discrimination power, AUC (95%IC) 0.821 (0.743–0.899).
patients, as compared to cases without antibodies. Remarkably, the percentage of CD56bright and NKG2Aþ NK-cells were significantly higher in DSA than in HLA nonDSA cases. Our results are in line with a recent study involving 124 patients mainly during the first year posttransplant, in which reduced numbers of CD56dim NK-cells were reported in patients with DSA (22). Based on a larger and longer-term cohort we confirmed this finding, observing in addition a significant increase of the percentage of CD56bright NK-cells in DSAþ kidney recipients. Moreover, this phenotypic profile as well as an increase in the percentage of NKG2Aþ cells, were also significantly different comparing DSA with HLA non-DSA recipients, independently of immunosuppression. Our findings suggest that anti-HLA antibodies, particularly DSA, might selectively influence the NK-cell subset distribution. NK-cells are major effectors of ADCC through the FcgR-IIIA (CD16) receptor, a function that may be triggered by HLA-specific alloantibodies and has been proposed to contribute to allograft rejection (23,24). Of note, CD16 is expressed by the CD56dim NK-cell subset but is virtually absent in CD56bright NK-cells (15). On the other hand, CD16 surface expression is down-regulated in activated NK-cells through a shedding process mediated by ADAM-17 (25). As NK-cell apoptosis was associated to
Table 5: Multivariate analysis for features associated with posttransplant DSA in kidney graft recipients comparing DSA (n ¼ 38) with HLA non-DSA patients (n ¼ 55) OR HLA DR mismatches %CD3CD56þ NKG2Aþ cells Recipient female gender Acute rejection Pretransplant PRA CDC (%) Recipient age at transplant Retransplantation
5.970 1.041 3.690 16.513 1.063 0.985 0.927
CI 95% 2.147 1.007 1.192 1.429 0.992 0.949 0.285
16.605 1.076 11.363 190.833 1.138 1.022 3.018
Discrimination power, AUC (95%IC) 0.729 (0.641–0.817).
812
p 0.001 0.018 0.024 0.025 0.085 0.428 0.900
Figure 3: (A) Correlation between the percentage of NKG2Aþ cells and serum creatinine in patients with DSA. (B) Comparison of the percentage of NKG2Aþ between DSA patients with and without ABMR changes in their biopsies (according to 2009 Banff classification).
ADCC (26) it is plausible that DSA might enhance the turnover of circulating NK-cells. This hypothesis would be consistent with the observed increase of CD56bright NKcells, which lack the FcgR-IIIA receptor being spared from the effect of alloantibodies. Moreover, most CD56bright NKcells are NKG2Aþ and would contribute to increase the proportions of this subset. Yet, an association of anti-HLA antibodies with higher percentage of CD56dimNKG2AþNKcells was also noticed. In this regard, it is conceivable that engagement of the CD94/NKG2A inhibitory receptor by HLA-E might dampen the alloantibody effect. Predictably, this effect would take place in every transplant, as the HLAE dimorphism does not significantly influence CD94/ NKG2A recognition (27). By contrast, the effect of alloantibodies on CD56dimNKG2ANK-cells would vary depending American Journal of Transplantation 2015; 15: 806–814
NK-Cell Subsets and Donor-Specific Antibodies
on recipient KIR-donor HLA class I matching, as well as on the distribution of different KIRþ NK-cell subsets (28). Further studies are required to address this hypothesis, considering as well whether CD16 polymorphisms which influence ADCC might modulate the pathogenic effect of alloantibodies (29). Increased NKG2AþNK-cells were also detected in HLA nonDSA patients, as compared with those without antibodies. Two nonexclusive interpretations may be proposed to explain this observation. First, low concentrations of circulating DSA, undetectable by the SAB assay, might be retained on the graft endothelium and stimulate NK-cells via CD16 (30). Second, non-HLA DSA could be present in some of these HLA non-DSA patients. Eventually, some HLA non-DSA antibodies might establish low-affinity crossreactive interactions with graft alloantigens, engaging NKcell FcgR-IIIA receptors. Given its exploratory nature, our study does not provide a precise assessment of the NK-cell immunophenotype as a predictive biomarker to derive clinical and therapeutic implications, and the limited follow-up after HLA antibody testing and NK-cell immunophenotyping restricts the possibility to explore the impact of combining both studies to predict graft failure. These aspects may be considered in future prospective assessments. In the context of the working hypothesis, other relevant variables should also be assessed in these future prospective studies, particularly the expression of individual KIR, together with KIR and donor HLA class I genotyping, as well as CD16 expression and CD16 gene polymorphisms known to influence ADCC. Studying additional NK-cell markers would potentially enrich the picture, taking into account factors that may influence their expression. In summary, transplant recipients with DSA after kidney transplantation display lower proportions of peripheral NKcells and of the major CD56dim subset than recipients without antibodies. Only the percentages of CD56bright and CD56dim NKG2Aþ cells but not their absolute numbers were higher in patients with antibodies, especially DSA. The observed NK-cell subset redistribution might reflect an enhanced antibody-dependent turnover following activation via CD16. A future working hypothesis may be that the increased percentage of NKG2Aþ NK-cells indirectly reflects their relative resistance to this process, thus becoming a potential marker of ongoing DSA-mediated tissue damage in patients with chronic ABMR.
Acknowledgments We are indebted to our nurse staff particularly the coordinators Anna Faura, Sara Alvarez and Rosa Causadias for their excellent job with all these patients. We thank Dulce Soto for her technical assistance in flow cytometry analysis. This study was performed with funding from the projects PI10/ 01370 and PI13/00598 (Spanish Ministry of Health ISCIII FIS-FEDER), Marato TV3 137/C/2012, RedinRen RD12/0021/0024 and Plan Nacional de
American Journal of Transplantation 2015; 15: 806–814
~ola I þ D (SAF2010-22153-C03). AM is supported by Asociacio´n Espan Contra el Ca´ncer (AECC).
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation.
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