End-stage renal failure (ESRF), the incidence of which has rocketed worldwide over the last decades, has become a major public health problem (
). Kidney transplantation represents the best therapeutic option for patients with ESRF, providing both a better quality of life and a longer life expectancy, www.who.int 1 , for only a fraction of the costs of chronic hemodialysis. 2 3 , 4
The current major challenge faced by kidney transplantation is to prolong the duration of graft function.
5 , Accumulating evidence has identified antibody-mediated rejection (AMR) as the main cause of kidney transplant loss. 6 The development of alloantibodies against mismatched donor HLA molecules (donor-specific antibody, DSA), despite maintenance immunosuppression, is due to: nonadherence to treatment, 7–10 7 , CNI minimization strategies, 8 11 , and the limited efficacy of available immunosuppressive drugs to completely abrogate the helper functions of recipients’ T follicular helper cells. 12 13 , 14
There is a significant interindividual heterogeneity in the natural evolution of AMR and in its response to therapy.
This suggests that the pathogenic mechanisms involved in the development of histologic lesions are not the same in all patients. Understanding the molecular mechanisms underlying this heterogeneity appears as a first mandatory step to improve personalized care of patients diagnosed with AMR. 15–17
The pathophysiologic sequence by which DSAs induce histologic damage to the graft has progressively been elucidated over the last two decades.
DSAs, which have limited ability to diffuse outside a recipient’s circulation, bind to directly accessible allogeneic HLA molecules expressed by graft endothelium. 18 Depending on the titer 19 and on the physico-chemical properties of the Igs, 15 20 , DSAs sometimes activate the classic complement pathway, thereby accelerating the rejection process. 21 15 , Complement activation is, however, not mandatory for the development of chronic AMR, 22 as clearly demonstrated in experimental models. 23 Indeed, the binding of DSAs to graft endothelium also recruits Fc 24–26 γ receptor–expressing innate immune effectors, which in turn promote damage to graft endothelial cells (ECs). 25 , 27 , 28
Among the innate immune cells participating in DSA-induced microvascular inflammation are natural killer (NK) cells,
29 , which have been shown to be critical for the development of endothelial damage. 30 25 , 27 , 28 , 31 , 32
For their activation,
NK cells rely not only on their ability to collaborate with the humoral arm of the adaptive immune system, but also integrate signals provided by various surface receptors, including inhibitory killer-cell Ig-like receptors (KIRs). In steady state, the latter interact with self HLA I molecules of surrounding healthy cells and provide negative signals to NK cells, thereby preventing their activation. 33 , Interestingly, our group has recently reported that in the setting of transplantation, the inability of graft ECs (which are from donor origin 34 ) to provide HLA I–mediated inhibitory signals to recipients’ circulating 19 NK cells triggers their activation. This process, known as “ 35 missing self” (MS), in turn promotes microvascular inflammation and graft rejection independently from DSAs. 35
Whether DSAs and MS can synergize to enhance NK cell activation and worsen AMR outcome has not been evaluated so far. We therefore initiated the present translational study to evaluate in patients and experimental models whether MS could explain part of the heterogeneity of AMR outcome.
The study was carried out in accordance with French legislation on biomedical research and the Declaration of Helsinki. All patients gave their informed consent for the utilization of clinical data (Données Informatiques Validées en Transplantation [DIVAT]) and biologic samples for research purposes (No. of biocollection: AC- 2011–1375 and AC-2016–2706).
The reports of all kidney allograft biopsies performed between September 1, 2004 and December 31, 2017 in either Edouard Herriot Hospital or Lyon Sud Hospital, the two university hospitals of Lyon (France), were screened (1682 patients) by means of the pathology department’s computer database (DIAMIC). Information from the DIAMIC database was crossed with one of the immunology department’s computer databases to identify patients with microvascular inflammation and concomitant DSAs (
n=135), thus fulfilling the diagnostic criteria of AMR according to the Banff classification. The steps of selection are summarized in Figure 1A. Figure 1.:
Characteristics of the study population. Kidney allograft biopsy specimens of 1682 patients were screened for microvascular inflammation (MVI: g+ptc ≥2) lesions. Patients with MVI presenting circulating anti-HLA DSAs in synchronous serum were diagnosed with AMR and enrolled in the study (
n=135). Depending on the ability of their DSA to activate the complement cascade in vitro, two groups of patients were defined: MVI +DSA +C3d + ( n=73; solid dark-gray line) and MVI +DSA +C3d − ( n=62; dashed purple line). The existence of a MS was assessed in MVI +DSA +C3d + and MVI +DSA +C3d − patients with available DNA for donor and recipient (respectively n=40 and n=44), allowing distribution of the patients into four subgroups: MVI +DSA +C3d +MS − ( n=17; solid light-gray line), MVI +DSA +C3d +MS + ( n=23; solid black line), MVI +DSA +C3d −MS − ( n=23; dashed blue line), and MVI +DSA +C3d −MS + ( n=21; dashed red line). (A) Flow chart showing the distribution of the patients in the different groups. (B) Renal graft survival of patients diagnosed with AMR (MVI +DSA +). Gray shading indicates 95% confidence interval. (C) Titer of immunodominant DSA was assessed in solid-phase assay. Distribution of this parameter is shown for the different groups. **** P<0.0001. One-way ANOVA.
All patients received an ABO-compatible transplant with negative historical and current complement-dependent cytotoxicity crossmatches. Clinical data were obtained from two independent national registries (Cristal [
] and Données Informatiques Validées en Transplantation [ http://www.sipg.sante.fr/portail/ ]) and crosschecked. The characteristics of the patients and their rejections are summarized in http://www.divat.fr/ Table 1.
Table 1. -
+DSA + ( n=135) MVI
+DSA +C3d + ( n=73) MVI
+DSA +C3d −MS − (£) ( n=23) MVI
+DSA +C3d −MS + ($) ( n=21)
P Value £ versus $
Characteristics at the time of transplantation
n (%) 82 (60.7)
n (%) 29 (21.5)
Time since dialysis (mo)
n (%) 125 (92.6)
Cold ischemia time (min)
No. of HLA A/B/DR mismatches
Delayed graft function,
n (%) 25 (18.5)
Characteristics of AMR
Time post-transplantation (mo)
eGFR (ml/min per 1.73 m
Histologic characteristics (Banff scores
Interstitial inflammation and tubulitis
Interstitial fibrosis and tubular atrophy
Types of DSA,
De novo DSA 108 (80.0)
de novo DSA 8 (5.9)
No. of DSAs
Classes of DSA,
MFI of immuno-dominant DSA
Data are displayed as mean±SD. MVI, microvascular inflammation.
aSimultaneous pancreas and kidney transplantations. bCalculated with the Modification of Diet in Renal Disease formula. cBanff scores (0, no significant lesion; 1, mild; 2, moderate; 3, severe). dSum of the Banff scores for glomerulitis and capillaritis. eMFI of the standard IgG detection assay. Allograft Pathology
Kidney graft biopsies were performed systematically as part of the routine follow-up procedure at 3 months and 1 year after transplantation, or when rejection was suspected at the other time points. Renal specimens were fixed in acetic acid–formol–absolute alcohol, and paraffin-embedded sections were stained by routine methods. C4d staining was performed by indirect immunofluorescence on frozen sections using an anti-human C4d complement–rabbit clonal antibody (clone A24-T, produced by DB Biotech, Kosice, Slovak Republic). Renal allograft lesions were graded according to the 2013 Banff classification.
Histologic criteria for AMR were defined by a sum of the scores for glomerulitis and peritubular capillaritis ≥2, with or without concurrent positive C4d staining. All of the biopsy specimens of the patients involved in the study were reviewed by a single renal pathologist (Maud Rabeyrin) who was blinded to clinical and immunologic data. 36
For computer-assisted analysis of graft inflammation (CAGI), double stainings with anti-CD34 (ECs) and respectively one antibody among anti-CD3 (T cells), anti-CD20 (B cells), anti-CD66b (granulocytes), anti-CD68 (macrophages), and anti-CD56 (
NK cells) were performed by immunochemistry on paraffin-embedded sections using an anti-human CD34 (clone QBEnd10, 1/200; Dako, Les Ulis, France) and respectively an anti-human CD3 (clone SK7, 1/150; Becton Dickinson, Le Pont de Claix, France), an anti-human CD20 (Clone L26, 1/400; Dako), an anti-human CD66b (clone G10F5, 1/300; Becton Dickinson), an anti-human CD68 (clone PGM1, 1/100; Dako), and an anti-human CD56 (clone CD564, 1/10; produced by Novocastra and distributed by Leica Microsystemes SAS, Nanterre, France). Of note, CD56 staining, although extremely sensitive (94%), is not fully specific for NK cells. About three-quarters of CD56 + cells are NK cells (Nkp46 +). The majority of CD56 + Nkp46 − cells are either NKT or CD8 + T cells. Computerized quantitative analyses were conducted to quantify the density of each immune cell type in the microcirculation and tubulointerstitial compartment of renal allograft as described. 16 Transcriptomic Analysis of Renal Graft Biopsy Specimens
For each renal allograft biopsy specimen included in this study, at least half of a core was immediately stored on Allprotect Tissue Reagent (Qiagen Benelux BV, Venlo, The Netherlands), and after incubation at 4°C for at least 24 hours and maximum 72 hours, stored at −20°C. RNA extraction was performed using the Allprep DNA/RNA/miRNA Universal Kit (Qiagen Benelux BV, Venlo, The Netherlands) on a QIAcube instrument (Qiagen Benelux BV, Venlo, The Netherlands). The quantity (absorbance at 260 nm) and purity (ratio of the absorbance at 230, 260, and 280 nm) of the RNA isolated from the biopsy specimens were measured using the NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Life Technologies Europe BV, Ghent, Belgium). RNA integrity was evaluated using the Eukaryote nano/pico RNA Kit (Agilent Technologies Belgium NV, Diegem, Belgium) on the Bioanalyzer 2100 instrument (Agilent Technologies). Samples were stored at −80°C until further analysis.
RNA extracted from the biopsy samples was first amplified and biotinylated to complementary RNA (cRNA) using the GeneChip 3′ IVT PLUS Reagent Kit (Affymetrix Inc., High Wycombe, UK) and subsequently hybridized onto Affymetrix GeneChip Human Genome U133 Plus 2.0 Arrays (Affymetrix Inc.), which cover over 54,000 transcripts, according to the manufacturer’s instructions. The arrays were scanned using the GeneChip Scanner 3000 7G System (Affymetrix Inc.), and image files were generated using the GeneChip Command Console Software (AGCC). Finally, Robust Multichip Average (RMA) background correction and normalization was performed using the Affymetrix Expression Console Software, and expression values were log
2 scaled. Fifty-four biopsy specimens survived prehybridization quality control checks, and were analyzed. CIBERSORT Algorithm
CIBERSORT (Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts) is a recently introduced computational method allowing the exploration of the heterogeneity of infiltrating immune cells in complex solid tissues.
This deconvolution algorithm calculates the relative fraction of different phenotypes of human hematopoietic cells in tissue samples, on the basis of the expression of 547 genes. To obtain an estimation of absolute intragraft NK-cell count, we adjusted the CIBERSORT data for the expression of pan-leukocyte marker CD45/PTPRC. 37 Detection and Characterization of Anti-HLA Antibodies
Serum samples banked at the time of biopsy were analyzed using Single Antigen Flow Beads assays (LSA class I and class II, Immucor, Norcross, GA). The MFI was measured on a LABscan IS 200, and all of the specificities with an MFI>500 and AD-BCR>5 were considered positive (AD-BCR is MFI adjusted to the quantity of coated antigen per bead).
Serum samples were analyzed in a blinded fashion for the presence of C3d-binding anti-HLA DSA (Valérie Dubois at the Etablissement Français du Sang, Lyon, France) with the use of single-antigen flow bead assays according to the manufacturer’s protocol (C3d-binding antibody assay; Immucor).
HLA and KIR Genotyping
Donor and recipient HLA typing were performed by PCR-SSO reverse (One Lambda, Canoga Park, CA). HLA-C1 and -C2 groups were determined for the donors and recipients considering the HLA C typing obtained by PCR-SSO reverse. The presence or not of Bw4 motif was determined for the donors and recipients considering the HLA A and B typing obtained by PCR-SSO reverse (
). Supplemental Figure 1
Genotyping of inhibitory KIR genes (
2DL1, 2DL2, 2DL3, 3DL1, 3DL2) was realized for the recipients by PCR-SSO reverse (KIR SSO Genotyping Test; One Lambda and Lifecodes KIR Genotyping, Immucor) according to the manufacturers’ instructions ( ). Supplemental Figure 1 Genetic Prediction of MS
2DL1, 2DL2, 2DL3, 3DL1, and 3DL2 inhibitory KIRs educated
NK cells only when the recipient expressed their respective HLA class I ligand: KIR2DL1/C2; KIR2DL2/C1; KIR2DL3/C1; KIR3DL1/Bw4; and KIR3DL2/A*03, *11.
Genetic prediction of MS was defined as the lack of expression by the graft of the type of HLA class I molecule able to bind to an educating inhibitory KIR of the recipient (
). Supplemental Figure 1 Cell Preparation and Cultures
Primary human arterial ECs were isolated from organ donors (agreement PFS08–017 from the Agence de la Biomédecine,
) and prospectively stored in the DIVAT biobank (No. of biocollection #02G55). They were cultured in EC growth medium 2 (Promocell, Heidelberg, Germany) in flasks coated with fibronectin (Promocell) or gelatin 1% (Sigma, Saint Quentin-Fallavier, France) and used between passages 2 and 7. https://www.agence-biomedecine.fr
Peripheral blood mononuclear cells (PBMCs) were isolated from the blood of healthy volunteers by Ficoll gradient centrifugation (Eurobio, Courtaboeuf, France). PBMCs were cultured overnight at 37°C in 5% CO
2 in RPMI-1640 (ThermoFisher Scientific, Courtaboeuf, France) supplemented with FBS 10%, l-glutamine 2 mM (ThermoFisher Scientific), penicillin 100 U/ml, streptomycin 100 µM, HEPES 25 mM (ThermoFisher Scientific), and 60 UI of recombinant human IL-2 (R&D Systems, Minneapolis, MN). NK cells were purified (>90%) from PBMCs by negative selection with magnetic enrichment kits (Stemcell, Grenoble, France). Evaluation of CD16
+inhKIR + NK Cell Population
One-hundred-microliter whole-blood samples were incubated with anti-CD3 (clone SK7, 1/20; Biolegend), -CD14 (clone M5E2, 1/20; BD Biosciences), -CD19 (clone HIB19, 1/20; BD Biosciences), -CD56 (clone NCAM16.2, 1/40; BD Biosciences), -CD16 (clone B73.1, 1/20; BD Biosciences), -KIR3DL1 (clone DX9, 1/10; BD Biosciences), -KIR2DL1/S1 (clone HP3E4, 1/10; BD Biosciences), and -KIR2DL2–3/S2 (clone GL183, 1/10; Beckman Coulter, Villepinte, France) antibodies for 30 minutes at 4°C. The samples were then incubated with a lysing solution (BD Biosciences) to eliminate the red blood cells for 3 minutes at room temperature. After washing, cells were fixed with paraformaldehyde 2% (ThermoFisher Scientific) and the samples were stored at 4°C until analysis. Sample acquisition was done on a LSR FORTESSA (BD Biosciences) and analyses were performed with FlowJo software version 10.0.8r1 (Tree Star Inc., Ashland, OR). Briefly, the following gating strategy was applied to assess the proportion of CD16
+inhKIR + NK cells among PBMCs. After a morphologic gate on lymphocytes followed by a gating on single cells, CD56 +CD3 −CD14 −CD19 − cells ( i.e., NK cells) were selected. Then, CD16 +inhKIR + NK cells were easily selected by using anti-KIR2DL1, -2DL2–3, and -3DL1 antibodies coupled to the same fluorochrome. NKG2A expression by NK cells was not assessed in this experiment. Analysis of EC Viability
In each culture well, 10,000 human primary ECs expressing HLA A2 and the inhibitory KIR ligands (C1
+, C2 +, Bw4 +) were seeded. When indicated, human primary ECs were preincubated with a serum containing an anti-A2 antibody (pure or diluted at 1:2 or 1:5) for 30 minutes at 37°C before seeding. After 24 hours, bulk purified NK cells from donors all expressing the following functional inhibitory KIRs: KIR2DL1 +/C2 +, KIR2DL2–3 +/C1 +, and KIR3DL1 +/Bw4 + were added to the culture (the number of NK cells was standardized in order to have the same number of CD16 +inhKIR + NK cells, i.e., 35,000 for all of the donors). When indicated, anti-KIR2DL1 (clone HP3E4; BD Biosciences), -KIR2L2–3 (clone GL183; Beckman Coulter), and -KIR3LD1 (clone DX9; BD Biosciences) blocking monoclonal antibodies or isotype controls were added to the culture at a final concentration of 1 µg/ml for each antibody. In absence of an existing anti-KIR3DL2 blocking mAb, KIR3DL2/A3, A11 MS was not tested in this experiment.
EC viability was monitored every 5 minutes for 10 hours by electrical impedance measurement with an xCELLigence RTCA SP instrument (ACEA Biosciences, San Diego, CA). The cell indexes were normalized to the reference value (measured just before adding
NK cells to the culture). EC viability in the experimental well was normalized over the control well. Statistical Analyses
Categoric variables were expressed as percentages and compared with the chi-squared test. Continuous variables were expressed as mean±SD and compared using the unpaired
Graft survival was calculated from the date of rejection diagnosis until the beginning of hemodialysis. Survival curves were constructed with the Kaplan–Meier method and compared with the log-rank test.
The Cox proportional hazards regression model was used in both univariable and multivariable models. All significant variables in the univariate analysis with a level set at <0.05 were incorporated into multivariate models. All tests were two sided, and
P values <0.05 were considered to represent statistically significant differences. Statistical analyses were done using R software version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria, 2018, ) and GraphPad Prism 6.0a for Mac OS X. https://www.R-project.org/ Results
Characteristics of the Study Population
Of 1682 kidney transplant recipients followed in our institutions over the study period for whom a graft biopsy was performed, 135 (8%) fulfilled the diagnostic criteria for AMR (
i.e., presence of circulating anti-HLA DSAs and sum of the Banff scores for glomerulitis and peritubular capillaritis ≥2) and were enrolled in the study ( Figure 1A). The clinical characteristics of these patients are detailed in Table 1.
In accordance with the literature,
15 , kidney allograft survival after AMR diagnosis was highly heterogeneous (77%, 50%, and 30% at 1, 4, and 7 years, respectively) ( 22 Figure 1B). Activation of Complement Cascade by DSAs Worsens AMR Outcome
On the basis of abundant literature demonstrating the role of complement in antibody-mediated accelerated graft destruction,
15 , the ability of DSAs to activate the classic complement pathway was evaluated at the time of diagnosis with the C3d binding assay. Of the 135 patients, 73 (54%) had C3d-binding DSAs (MVI 22 +DSA +C3d + group) and 62 (46%) had non–C3d-binding DSAs (MVI +DSA +C3d − group) ( Figure 1A). As expected, the intensity of C4d deposits in allograft biopsy specimens was higher in the MVI +DSA +C3d + group (Banff score 2.0±1.1 versus 1.3±1.2 for MVI +DSA +C3d − group; P=0.006). It is well known that the ability of DSAs to recruit C1q highly depends on DSA quantity. MVI 38 +DSA +C3d + patients had a more diverse DSA repertoire (number of DSA specificities: 2.1±1.2 versus 1.5±0.7 for MVI +DSA +C3d −; P=0.002) and higher DSA titers (MFI of immuno-dominant DSA obtained with the standard IgG detection assay: 11,802±4973 versus 3719±2862 for MVI +DSA +C3d −; P<0.0001). In line with previous publications, 15 , the presence of circulating C3d-binding DSAs at time of rejection strongly correlated with a higher risk for renal graft failure ( 39 P=0.002, log-rank test; Figure 2A). We confirmed that this correlation was the consequence of complement activation and not of the higher titer of immuno-dominant DSA in the MVI +DSA +C3d + group by conducting the same analysis on patients with comparable MFI within MVI +DSA +C3d − and MVI +DSA +C3d + groups ( P=0.02, log-rank test; ). Supplemental Figure 2 Figure 2.:
C3d binding capacity of DSA and MS affect allograft survival. (A) Renal graft survival of MVI
+DSA +C3d − (dashed purple line) and of MVI +DSA +C3d + (solid dark-gray line) were compared. (B) Renal graft survival of MVI +DSA +C3d −MS − (dashed blue line) and of MVI +DSA +C3d −MS + (dashed red line) were compared. (C) Renal graft survival of MVI +DSA +C3d +MS − (solid light-gray line) and of MVI +DSA +C3d +MS + (solid black line) were compared. * P<0.05, ** P<0.01. Log-rank test. MS Effect on Allograft Survival of Patients with AMR
Low-titer DSAs, which cannot activate the complement cascade, trigger chronic AMR.
25 , 27 , 28 , 31 , We have recently demonstrated that the inability of graft ECs to deliver self HLA I–mediated inhibitory signals to recipient’s 32 NK cells ( i.e., MS) was sufficient to promote NK cell–mediated chronic vascular rejection. We therefore hypothesized that MS could synergize with low-titer DSAs to accelerate graft loss in chronic AMR. To test this theory, we integrated, for each donor/recipient pair, the genetic analyses of: recipient inhibitory KIRs and recipient HLA I (in order to identify educating inhibitory KIRs, 35 i.e., functional inhibitory KIRs susceptible to sense MS on graft ECs), with the donor HLA I genotype, so as to identify situations of MS ( ). These analyses revealed that 42.5% ( Supplemental Figure 1 n=17/40) of MVI +DSA +C3d + patients and 48% ( n=21/44) of MVI +DSA +C3d − patients had a MS ( Figure 1A). In line with our hypothesis, MVI +DSA +C3d −MS + patients had a significantly higher risk for renal graft loss as compared with MVI +DSA +C3d −MS − patients ( P=0.02, log-rank test; Figure 2B). Of note, the additional effect of MS could not be observed in the group of MVI +DSA +C3d + patients, in whom the activation of complement led to a very fast graft loss ( P=0.7, log-rank test; Figure 2C). MS Is an Independent Predictive Factor for Allograft Loss in Chronic AMR
Although univariate analysis showed that the presence of a MS correlates with a higher risk of graft loss in chronic AMR (
Figure 2B), this difference could be due to many confounding factors. To rule out this possibility, the characteristics of the MVI +DSA +C3d −MS + and MVI +DSA +C3d −MS − patients were compared ( Table 1). Baseline characteristics of donors and recipients at time of transplantation were similar between the two groups as was the treatment of AMR. However, at the time of rejection, patients with a MS had significantly more interstitial fibrosis and tubular atrophy on graft biopsy (IFTA Banff score: 1.8±0.9 versus 1.1±0.7, respectively; P=0.007; Table 1). On the other hand, MVI +DSA +C3d −MS + patients had lower titers of circulating DSAs (MFI of immunodominant DSA obtained with the standard IgG detection assay: 2607±1444 versus 4322±2993; P=0.04; Table 1) than MVI +DSA +C3d −MS − patients.
To test whether MS was an independent risk factor for graft loss in chronic AMR, a multivariable analysis was conducted using a Cox regression proportional hazard model. Exploratory analysis identified three risk factors statistically associated with graft failure (
Table 2, left column): MS, proteinuria at time of diagnosis of AMR, and the intensity of microvascular inflammation. When integrated in a multivariable analysis ( Table 2, right column), only two independent predictors for allograft failure at diagnosis of chronic AMR remained: proteinuria (hazard ratio, 7.24; 95% confidence interval, 1.51 to 34.60; P=0.01) and the presence of a MS (hazard ratio, 3.57; 95% confidence interval, 1.04 to 12.18; P=0.04). We concluded that MS is an independent mechanism that synergizes with low-titer DSAs to accelerate graft loss in chronic AMR.
Table 2. -
Univariable and multivariable analyses of risk factors for death-censored allograft loss
No. of Patients
P Value HR
(0.39 to 3.17)
Recipient age (per 1-yr increment)
(0.98 to 1.05)
(0.15 to 1.96)
(0.26 to 17.62)
Donor age (per 1-yr increment)
(0.97 to 1.03)
Number of mismatches A/B/DR
(0.13 to 2.61)
Cold-ischemia time per 1-min increment
(0.99 to 1.00)
eGFR at the time of rejection
(ml/min per 1.73 m b
(0.94 to 6.38)
Proteinuria at the time of rejection (grams/d)
(1.67 to 16.90)
(1.51 to 34.60)
2 or 3
(1.02 to 8.32)
Interstitial inflammation and tubulitis
0 or 1
(0.50 to 3.55)
0 or 1
(0.22 to 4.36)
(0.05 to 3.10)
0 or 1
(0.74 to 6.72)
Interstitial fibrosis and tubular atrophy
0 or 1
(0.78 to 5.93)
(1.12 to 9.15)
(1.04 to 12.18)
MFI of immuno-dominant DSA
(0.36 to 7.36)
MFI of immuno-dominant DSA
(per one-unit increment) e
(0.99 to 1.00)
Number of DSA
(0.30 to 2.89)
HR, hazard ratio; 95% CI, confidence interval; NS, not significant; MFI, mean fluorescence intensity.
aIndicates the variables that were not tested in the multivariable model. bCalculated with the Modification of Diet in Renal Disease formula. cBanff scores (0, no significant lesion; 1, mild; 2, moderate; 3, severe). dSum of the Banff scores for glomerulitis and capillaritis. eMFI of the standard IgG detection assay. Variables at the P level <0.05 in the univariate model were incorporated into the multivariable model. MS Increases NK Cell Recruitment and Activation during Chronic AMR
We next wondered what is the effect of MS-induced NK cell activation on the histologic lesions of chronic AMR.
First, the intensity of chronic and acute histologic lesions, graded according to the international Banff classification, was compared between MVI
+DSA +C3d +, MVI+DSA+C3d−MS− and MVI+DSA+C3d−MS+ groups. The two groups with the worst graft survival (MVI +DSA +C3d + and MVI +DSA +C3d −MS +) had significantly more interstitial fibrosis and tubular atrophy than MVI +DSA +C3d −MS − (1.8±0.9 and 1.7±0.8 versus 1.1±0.7, respectively; P=0.006; Figure 3A, Table 1), suggesting a more aggressive pathogenic mechanism. However, biopsy specimens of the three groups showed comparable Banff scores for acute lesions: both microvascular (glomerulitis and peritubular capillaritis) and tubulo-interstitial inflammation ( Figure 3, B and C, Table 1). These data led us to hypothesize that it was the nature, rather than the mere “quantity” of inflammation, that was the main factor accounting for the differences in graft survival. Figure 3.:
MS increases NK cell recruitment during chronic AMR. (A–C) The intensities of interstitial fibrosis and tubular atrophy (IFTA) (A), microvascular inflammation (defined as the sum of Banff scores for glomerulitis [g, 0–3] and peritubular capillaritis [ptc, 0–3]) (B), and tubulo-interstitial inflammation (defined as the sum of Banff scores for interstitial inflammation [i, 0–3] and tubulitis [t, 0–3]) (C) were compared between MVI
+DSA +C3d +, MVI +DSA +C3d −MS −, and MVI +DSA +C3d −MS + patients. * P<0.05. Kruskal–Wallis test. (D–F) For CAGI analysis, paraffin-embedded sections of available graft biopsy specimens from MVI +DSA +C3d + ( n=61), MVI +DSA +C3d −MS − ( n=17), and MVI +DSA +C3d −MS + ( n=13) patients were stained for ECs (CD34) and NK cells (CD56) or macrophages (CD68), or neutrophils (CD66b), or T cells (CD3), or B cells (CD20). The density of the infiltration of each immune subset was measured in the microcirculation and the interstitium of the graft. (D) We applied a discriminant analysis on the CAGI dataset of the 91 patients with available data. The scatter plot of the first two canonical function is shown. Entropy r 2=0.39. (E) A representative image of NK cell (CD56 +) infiltration of graft microcirculation (glomeruli, upper row; peritubular capillaries, middle row) and interstitium (lower row) is shown for each group. Scale bar, 50 μm. (E) The density of NK cells infiltrating microvascular and interstitial compartments of the graft was compared between the three groups. * P<0.05. One-way ANOVA. (G) The CIBERSORT algorithm was applied to the transcriptomic data of allograft biopsy samples of MVI −DSA − ( n=43, green), MVI +DSA +C3d −MS − ( n=5, blue), and MVI +DSA +C3d −MS + ( n=6, red) patients. Absolute NK cell infiltration was estimated by adjusting the relative percentages of activated and resting NK cells on the expression of the pan-leukocyte marker CD45 in the biopsy specimen. Box, interquartile range; line, median; whiskers, 10th and 90th percentiles. * P<0.05; **** P<0.0001. One-way ANOVA. A.U., arbritary unit.
To better characterize graft inflammation, we used the CAGI technique,
which allows for a precise quantification of the innate and adaptive immune cell subset densities in the microcirculation (glomerular and peritubular capillaries) and the interstitium of renal allograft. Linear discriminant analysis conducted on the whole CAGI dataset of patients with available biopsy material ( 16 n=91) accurately identified the three groups (MVI +DSA +C3d +, MVI +DSA +C3d −MS +, and MVI +DSA +C3d −MS −), confirming that the nature of graft inflammation differs between the groups ( Figure 3D). Interestingly, the single parameter that distinguished patients from the MVI +DSA +C3d −MS + group from those of MVI +DSA +C3d −MS − and MVI +DSA +C3d + group was an increased graft infiltration by NK cells (36±49 versus 6±5 and 15±17 CD56 pos cells/mm 2, respectively; P=0.03; Figure 3E, ). This increased density of Supplemental Figures 3 and 4 NK cells in grafts from MVI +DSA +C3d −MS + patients was observed in both microvascular and interstitial compartments ( Figure 3, E and F).
In order to further assess the effect of MS on
NK cells during AMR, we analyzed the transcriptomic data from the graft biopsies of an independent cohort of 54 renal recipients. A recently published computational method named CIBERSORT was applied to deconvolute the dataset and evaluate the amounts of both activated and resting 37 NK cells infiltrating the grafts. The results obtained in the 43 patients without MVI or DSA (MVI −DSA −; control group) were compared with those of patients diagnosed with chronic AMR, with and without MS (MVI +DSA +C3d −MS +, n=6; and MVI +DSA +C3d −MS −, n=5, respectively). As expected, NK cell infiltrate was more abundant in chronic AMR biopsy specimens as compared with controls. In line with the CAGI data presented ( Figure 3F), the presence of a MS was associated with an increased number of NK cells infiltrating the graft. Furthermore, transcriptomic analysis also revealed that there were more activated NK cells in the grafts of MVI +DSA +C3d −MS + than in those of MVI +DSA +C3d −MS − patients ( Figure 3G). Altogether, these data support the theory that MS synergizes with DSA to promote NK cell recruitment and activation during chronic AMR. MS Enhances EC Damage
Having shown that MS enhances NK cell recruitment and activation in rejected grafts, we next evaluated whether this parameter also increases the cytotoxic activity of
NK cells, which could account for the accelerated destruction of these grafts. To test this hypothesis, bulk NK cells purified from the PBMCs of healthy volunteers were cocultured on a monolayer of HLA A2–expressing primary allogeneic human ECs, the integrity of which was monitored by real-time impedance measurement. Because the number of NK cells able to respond to the two stimuli ( i.e., NK cells expressing both the Fc γ receptor CD16 and iKIR) was highly variable in healthy volunteers ( Figure 4A), the coculture conditions were adjusted to contain the same number of CD16 pos iKIR pos ( i.e., responder) NK cells. DSA-dependent NK cell activation was triggered using the serum of a transplanted patient highly sensitized against HLA A2 (MFI=18,867; Figure 4B). This very high titer of DSA induced a rapid and complete destruction of the endothelial targets but did not reflect the clinical situation of MVI +DSA +C3d − patients. To better mimic chronic AMR in vitro, we tested different dilutions of the serum. Dilution by 1:2 was still sufficient to induce a rapid and total destruction of endothelial targets in the absence of MS ( Figure 4C). In contrast, 1:5 dilution resulted in slower and less-complete destruction of ECs, leaving room to observe a putative additional effect of MS. Interestingly, serum diluted at 1:5 corresponded to anti-HLA A2 DSA MFI of approximately 7000 ( Figure 4B), a titer comparable to what was observed in MVI +DSA +C3d − patients ( Figures 1C and 4D). MS was triggered by adding to the coculture a cocktail of blocking monoclonal antibodies directed against four inhibitory KIRs (KIR2DL1, KIR2DL2, KIR2DL3, KIR3DL1; ). This allowed using the same allogeneic ECs in all of the experimental conditions, thus guaranteeing the comparability of the results between the various culture conditions. The survival of the same primary matched allogeneic ECs exposed to Supplemental Figure 1 NK cells from the same donor was compared for four distinct situations ( Figure 4E): ( 1) absence of both DSA and MS ( i.e., control; left panel, green); ( 2) DSA alone (middle left panel, blue); ( 3) MS alone (middle right panel, orange); and ( 4) DSA and MS (right panel, red). This in vitro experiment, replicated with six different pairs, confirmed that MS synergizes with DSA to accelerate and aggravate EC destruction by NK cells ( Figure 4F). Figure 4.:
MS enhances EC damage
in vitro. (A) The expression of Fc γRIIIA (CD16) and each inhibitory KIR (KIR2DL1, KIR2DL2, KIR2DL3, and KIR3DL1) was analyzed by flow cytometry on circulating NK cells from 14 healthy volunteers. The proportion of NK cells expressing all of the receptors is shown. (B) The serum of a transplanted patient, sensitized against HLA A2, was diluted and tested in solid-phase assay. The MFI of an HLA A2 bead is plotted for the various dilutions. Dashed lines indicate: in the y axis, the threshold of MFI associated with C3d assay positivity (see receiver operating characteristic [ROC] curve in D); and in the x axis, the corresponding serum dilution (1:5). (C) Purified NK cells from a healthy donor were cocultured with the same primary human ECs in absence (0: control; light blue) or presence of decreasing titers of DSA (dilution of sensitized serum: pure, 1:2, 1:5; darker shades of blue). The impedance profile of each culture conditions is shown (mean±SEM). (D) ROC curve for prediction of the ability of DSA to activate the complement according to MFI titer of the immunodominant DSA (sensitivity of 82.2%, specificity of 87.1%, and likelihood ratio at 6.4). AUC, area under the curve. (E and F) Bulk purified NK cells from healthy volunteers bearing CD16, KIR2DL1, KIR2DL2–3, and KIR3DL1 were cocultured with the same primary allogeneic HLA A2–expressing human ECs ( 1) in presence of human AB serum (SAB) and an isotype control mAb cocktail (control, left panel); ( 2) in presence of a low-titer DSA and an isotype control mAb cocktail (DSA alone, middle left panel); ( 3) in presence of SAB and a blocking anti-inhibitory KIR mAb cocktail (MS alone, middle right panel); or ( 4) in presence of a low-titer DSA and a blocking anti-inhibitory KIR mAb cocktail (DSA + MS, right panel). (E) Schematic representation of the experimental model. (F) The viability of ECs was assessed by real-time impedance measurement in each coculture and the data were normalized over control. Left panel: impedance profiles of the four coculture conditions are shown for one representative experiment (mean±SEM; left panel). Right panel: AUCs of the impedance profiles from six independent experiments are compared. * P<0.05. Friedman test. A.U., arbritary unit. Discussion
The recipient’s humoral alloimmune response is widely accepted as a major cause of allograft loss after organ transplantation. AMR outcome is, however, highly heterogeneous at the individual level, suggesting that different patients with AMR have different immunopathologic mechanisms involved in the destruction of their graft. Understanding these various mechanisms and identifying which of them are involved in a given patient could pave the way for more efficient, personalized treatments.
Analyzing a cohort of renal transplant recipients diagnosed with AMR, our translational study confirms previous publications, which reported that complement activation is a major accelerator of allograft destruction.
15 , 22 , 39 , 40
For patients whose DSA titer is too low to trigger complement activation, graft destruction is thought to result from the recruitment of Fc
γ receptor–expressing innate effectors. 18 , Several lines of experimental evidence point toward the central role of 41 NK cells in this process. 25 , In line with these data, a recent clinical study has reported that the intensity of NK cell infiltration within the graft is correlated with transplant survival in AMR. 27–29 Recently, our group demonstrated that in the absence of DSA, MS alone was sufficient to trigger NK cell–mediated chronic vascular rejection. 30 In this study, we show for the first time that the inability of the graft to deliver HLA I–mediated inhibitory signals to 35 NK cells ( i.e., MS) synergizes with DSA to increase NK cell recruitment and cytotoxicity, which in turn accelerate graft destruction. In fact, despite lower DSA titers, patients with chronic AMR in whom these two pathogenic mechanisms were identified had a graft survival equally gloomy as for patients with complement-dependent (“acute”) AMR.
Our study has, of course, several limitations, notably the fact that the clinical data were obtained retrospectively in a monocentric cohort of limited size. Nevertheless, these limits are balanced by the concordant transcriptomic data obtained in an independent cohort of patients receiving kidney transplant and the results of
in vitro models. The latter indeed validated the mechanistic role of MS in potentiating NK cell recruitment and cytotoxicity in chronic AMR.
Another limitation of this study is that MS was defined only upon HLA class I/educated inhibitory KIR combinations. However, this molecular mechanism is not the only antibody-independent process by which
NK cells could receive a synergistic activation signal during AMR. NK cell activation indeed depends on the integration of activating and inhibitory signals coming from several surface receptors. Besides inhibitory KIRs, which play a critical role in the acquisition of their functions, 42 NK cells also possess other inhibitory receptors such as NKG2A which can also modulate their reactivity. The latter interacts with HLA E, a nonclassic HLA class I molecule expressed by all nucleated cells. 43 Even if the HLA E molecule is characterized by a limited polymorphism, its stabilization on the cell surface is known to be modulated by its ability to load peptide derived from the classic HLA class I leader sequence. 44 The leader sequence derived from most HLA B haplotypes does not bind effectively to HLA E, resulting in decreased surface expression of HLA E–peptide complexes and thus a reduced capacity for the cell to deliver NKG2A-mediated inhibitory signals to 45 NK cells. 43 , In the context of allogeneic organ transplantation, it is tempting to speculate that, depending on the HLA B haplotypes of the donor, the inability of graft ECs to deliver enough HLA E–mediated inhibitory signals might promote recipients’ NK cell activation. Finally, in other circumstances, 45 NK cells could be activated not by a lack of inhibitory signals but by an excess of activating signals, i.e., the recognition of “induced self.” In the context of organ transplantation, ischemia/reperfusion is known to induce the expression of stress ligands on graft ECs, 46 which in turn bind to NK cell–activating receptors (NKG2D or activating KIRs) and trigger activation. 47–49 50 , Future studies are needed to determine the respective importance of these molecular mechanisms in the pathophysiology of rejection, not only AMR but also TCMR. 51
In conclusion, our translational study demonstrates that the combination of MS- and DSA-induced activation of recipient’s
NK cells is synergistically deleterious for graft survival. Identification of patients with MS at the time of diagnosis of chronic AMR could help in stratifying the risk of graft loss and to guide a personalized therapeutic approach. Disclosures
B. Charreau reports current employment with CRTI INSERM UMR1064. V. Dubois reports current employment with EFS AURA. A. Koenig is supported by INSERM (Institut National de la Santé et de la Recherche Médicale) (poste accueil 2015/1239/BT), the Hospices Civils de Lyon, and the Fondation du Rein, outside of the submitted work. E. Morelon reports research funding and honoraria from Astellas. M. Naesens reports scientific advisor or membership as an Editorial Board member for several journals and advisor for the European Medicines Agency. O. Thaunat reports consultancy agreements with NOVARTIS; research funding from BIOMERIEUX, BMS, IMMUCOR, and NOVARTIS; and scientific advisor or membership with ESOT. All remaining authors have nothing to disclose.
This work was supported by the
(ANR-16-CE17-0007-01) and the Agence Nationale de la Recherche (PME20180639518). Fondation pour la Recherche Médicale
We wish to thank Dr. Christelle Forcet and Violaine Tribollet for help with Xcelligence experiments, and Mathilde Koenig for her help with the design of the figures.
Alice Koenig and Olivier Thaunat designed the study; Alice Koenig and Virginie Mathias performed the experiments; Alice Koenig, Sarah Mezaache, Thomas Barba, Virginie Mathias, Maud Rabeyrin, Vannary Meas-Yedid, and Valérie Dubois analyzed the data; Alice Koenig, Sarah Mezaache, and Olivier Thaunat wrote the paper; and Jasper Callemeyn, Antonie Sicard, Béatrice Charreau, Frédérique Dijoud, Cécile Picard, Jean-Christrophe Olivo-Marin, Emmanuel Morelon, Maarten Naesens, and Valérie Dubois contributed to the discussion.
This article contains the following supplemental material online at
. NK cell education and activation by Supplemental Figure 1 missing self.
. Activation of complement in patients with similar MFI of immuno-dominant DSA. Supplemental Figure 2
. Computer-assisted analysis of allograft inflammation (CAGI): three groups analysis. Supplemental Figure 3
. Computer-assisted analysis of allograft inflammation (CAGI): four groups analysis. Supplemental Figure 4 References
1. Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, et al.: Systematic review: Kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant 11: 2093–2109, 201121883901
2. Wolfe RA, Ashby VB, Milford EL, Ojo AO, Ettenger RE, Agodoa LY, et al.: Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant. N Engl J Med 341: 1725–1730, 199910580071
3. Wong G, Howard K, Chapman JR, Chadban S, Cross N, Tong A, et al.: Comparative survival and economic benefits of deceased donor kidney transplantation and dialysis in people with varying ages and co-morbidities. PLoS One 7: e29591, 201222279541
4. Laupacis A, Keown P, Pus N, Krueger H, Ferguson B, Wong C, et al.: A study of the quality of life and cost-utility of
. Kidney Int 50: 235–242, 19968807593
5. Lamb KE, Lodhi S, Meier-Kriesche H-U: Long-term renal allograft survival in the United States: A critical reappraisal. Am J Transplant 11: 450–462, 201120973913
6. Coemans M, Süsal C, Döhler B, Anglicheau D, Giral M, Bestard O, et al.: Analyses of the short- and long-term graft survival after kidney transplantation in Europe between 1986 and 2015. Kidney Int 94: 964–973, 201830049474
7. Wiebe C, Gibson IW, Blydt-Hansen TD, Karpinski M, Ho J, Storsley LJ, et al.: Evolution and clinical pathologic correlations of de novo donor-specific HLA antibody post kidney transplant. Am J Transplant 12: 1157–1167, 201222429309
8. Sellarés J, de Freitas DG, Mengel M, Reeve J, Einecke G, Sis B, et al.: Understanding the causes of kidney transplant failure: The dominant role of antibody-mediated rejection and nonadherence. Am J Transplant 12: 388–399, 201222081892
9. Einecke G, Sis B, Reeve J, Mengel M, Campbell PM, Hidalgo LG, et al.: Antibody-mediated microcirculation injury is the major cause of late kidney transplant failure. Am J Transplant 9: 2520–2531, 200919843030
10. Halloran PF, Chang J, Famulski K, Hidalgo LG, Salazar IDR, Merino Lopez M, et al.: Disappearance of T Cell-mediated rejection despite continued antibody-mediated rejection in late kidney transplant recipients. J Am Soc Nephrol 26: 1711–1720, 201525377077
11. Girerd S, Schikowski J, Girerd N, Duarte K, Busby H, Gambier N, et al.: Impact of reduced exposure to calcineurin inhibitors on the development of de novo DSA: A cohort of non-immunized first kidney graft recipients between 2007 and 2014. BMC Nephrol 19: 232, 201830219043
12. Thaunat O, Koenig A, Leibler C, Grimbert P: Effect of immunosuppressive drugs on humoral allosensitization after kidney transplant. J Am Soc Nephrol 27: 1890–1900, 201626872489
13. Chen C-C, Koenig A, Saison C, Dahdal S, Rigault G, Barba T, et al.: CD4+ T cell help is mandatory for naive and memory donor-specific antibody responses: Impact of therapeutic immunosuppression. Front Immunol 9: 275, 201829515582
14. Dahdal S, Saison C, Valette M, Bachy E, Pallet N, Lina B, et al.: Residual activatability of circulating Tfh17 predicts humoral response to thymodependent antigens in patients on therapeutic immunosuppression. Front Immunol 9: 3178, 201930804950
15. Sicard A, Ducreux S, Rabeyrin M, Couzi L, McGregor B, Badet L, et al.: Detection of C3d-binding donor-specific anti-HLA antibodies at diagnosis of humoral rejection predicts renal graft loss. J Am Soc Nephrol 26: 457–467, 201525125383
16. Sicard A, Meas-Yedid V, Rabeyrin M, Koenig A, Ducreux S, Dijoud F, et al.: Computer-assisted topological analysis of renal allograft inflammation adds to risk evaluation at diagnosis of humoral rejection. Kidney Int 92: 214–226, 201728318622
17. Lefaucheur C, Viglietti D, Hidalgo LG, Ratner LE, Bagnasco SM, Batal I, et al.: Complement-activating anti-HLA antibodies in kidney transplantation: Allograft gene expression profiling and response to treatment. J Am Soc Nephrol 29: 620–635, 201829042454
18. Pouliquen E, Koenig A, Chen CC, Sicard A, Rabeyrin M, Morelon E, et al.: Recent advances in
: Antibody-mediated rejection takes center stage. F1000Prime Rep 7: 51, 201526097724
19. Chen C-C, Pouliquen E, Broisat A, Andreata F, Racapé M, Bruneval P, et al.: Endothelial chimerism and vascular sequestration protect pancreatic islet grafts from antibody-mediated rejection. J Clin Invest 128: 219–232, 201829202467
20. Lefaucheur C, Viglietti D, Bentlejewski C, van Huyen J-PD, Vernerey D, Aubert O: IgG donor-specific anti-human HLA antibody subclasses and kidney allograft antibody-mediated injury. J Am Soc Nephrol 27: 293–304, 2016 10.1881/ASN.2014111120
21. Barba T, Harb J, Ducreux S, Koenig A, Mathias V, Rabeyrin M, et al.: Highly variable sialylation status of donor-specific antibodies does not impact humoral rejection outcomes. Front Immunol 10: 513, 201930949173
22. Loupy A, Lefaucheur C, Vernerey D, Prugger C, Duong van Huyen J-P, Mooney N, et al.: Complement-binding anti-HLA antibodies and kidney-allograft survival. N Engl J Med 369: 1215–1226, 201324066742
23. Guidicelli G, Guerville F, Lepreux S, Wiebe C, Thaunat O, Dubois V, et al.: Non-complement-binding de novo donor-specific anti-HLA antibodies and kidney allograft survival. J Am Soc Nephrol 27: 615–625, 201626047793
24. Hirohashi T, Uehara S, Chase CM, DellaPelle P, Madsen JC, Russell PS, et al.: Complement independent antibody-mediated endarteritis and transplant arteriopathy in mice. Am J Transplant 10: 510–517, 201020055805
25. Hirohashi T, Chase CM, Della Pelle P, Sebastian D, Alessandrini A, Madsen JC, et al.: A novel pathway of chronic allograft rejection mediated by
and alloantibody. Am J Transplant 12: 313–321, 201222070565
26. Bian H, Reed EF: Alloantibody-mediated class I signal transduction in endothelial cells and smooth muscle cells: Enhancement by IFN-gamma and TNF-alpha. J Immunol 163: 1010–1018, 199910395699
27. Venner JM, Hidalgo LG, Famulski KS, Chang J, Halloran PF: The molecular landscape of antibody-mediated kidney transplant rejection: Evidence for NK involvement through CD16a Fc receptors. Am J Transplant 15: 1336–1348, 201525787894
28. Parkes MD, Halloran PF, Hidalgo LG: Evidence for CD16a-mediated NK cell stimulation in antibody-mediated kidney transplant rejection. Transplantation 101: e102–e111, 201727906829
29. Hidalgo LG, Sis B, Sellares J, Campbell PM, Mengel M, Einecke G, et al.: NK cell transcripts and
in kidney biopsies from patients with donor-specific antibodies: Evidence for NK cell involvement in antibody-mediated rejection. Am J Transplant 10: 1812–1822, 201020659089
30. Yazdani S, Callemeyn J, Gazut S, Lerut E, de Loor H, Wevers M, et al.: Natural killer cell infiltration is discriminative for antibody-mediated rejection and predicts outcome after kidney transplantation. Kidney Int 95: 188–198, 201930396694
31. Kohei N, Tanaka T, Tanabe K, Masumori N, Dvorina N, Valujskikh A, et al.: Natural killer cells play a critical role in mediating inflammation and graft failure during antibody-mediated rejection of kidney allografts. Kidney Int 89: 1293–1306, 201627165816
32. Yagisawa T, Tanaka T, Miyairi S, Tanabe K, Dvorina N, Yokoyama WM, et al.: In the absence of natural killer cell activation donor-specific antibody mediates chronic, but not acute, kidney allograft rejection. Kidney Int 95: 350–362, 201930503624
33. Thielens A, Vivier E, Romagné F: NK cell MHC class I specific receptors (KIR): From biology to clinical intervention. Curr Opin Immunol 24: 239–245, 201222264929
34. Campbell KS, Purdy AK: Structure/function of human killer cell immunoglobulin-like receptors: Lessons from polymorphisms, evolution, crystal structures and mutations. Immunology 132: 315–325, 201121214544
35. Koenig A, Chen C-C, Marçais A, Barba T, Mathias V, Sicard A, et al.:
triggers NK cell-mediated chronic vascular rejection of solid organ transplants. Nat Commun 10: 5350, 201931767837
36. Haas M, Sis B, Racusen LC, Solez K, Glotz D, Colvin RB, 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 14: 272–283, 201424472190
37. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al.: Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12: 453–457, 201525822800
38. Diebolder CA, Beurskens FJ, de Jong RN, Koning RI, Strumane K, Lindorfer MA, et al.: Complement is activated by IgG hexamers assembled at the cell surface. Science 343: 1260–1263, 201424626930
39. Courant M, Visentin J, Linares G, Dubois V, Lepreux S, Guidicelli G, et al.: The disappointing contribution of anti-human leukocyte antigen donor-specific antibodies characteristics for predicting allograft loss. Nephrol Dial Transplant 33: 1853–1863, 201829672702
40. Bouquegneau A, Loheac C, Aubert O, Bouatou Y, Viglietti D, Empana J-P, et al.: Complement-activating donor-specific anti-HLA antibodies and solid organ transplant survival: A systematic review and meta-analysis. PLoS Med 15: e1002572, 201829799874
41. Koenig A, Mariat C, Mousson C, Wood KJ, Rifle G, Thaunat O: B cells and antibodies in transplantation. Transplantation 100: 1460–1464, 201626845305
42. Anfossi N, André P, Guia S, Falk CS, Roetynck S, Stewart CA, et al.: Human NK cell education by inhibitory receptors for MHC class I. Immunity 25: 331–342, 200616901727
43. Horowitz A, Djaoud Z, Nemat-Gorgani N, Blokhuis J, Hilton HG, Béziat V, et al.: Class I HLA haplotypes form two schools that educate
in different ways [published online ahead of print September 9, 2016]. Sci Immunol 1: eaag1672, 2016 10.1126/sciimmunol.aag1672 27868107
44. Braud VM, Allan DS, O’Callaghan CA, Söderström K, D’Andrea A, Ogg GS, et al.: HLA-E binds to natural killer cell receptors CD94/NKG2A, B and C. Nature 391: 795–799, 19989486650
45. Lee N, Goodlett DR, Ishitani A, Marquardt H, Geraghty DE: HLA-E surface expression depends on binding of TAP-dependent peptides derived from certain HLA class I signal sequences. J Immunol 160: 4951–4960, 1998
46. Vivier E, Raulet DH, Moretta A, Caligiuri MA, Zitvogel L, Lanier LL, et al.: Innate or adaptive immunity? The example of natural killer cells. Science 331: 44–49, 201121212348
47. González S, López-Soto A, Suarez-Alvarez B, López-Vázquez A, López-Larrea C: NKG2D ligands: Key targets of the immune response. Trends Immunol 29: 397–403, 200818602338
48. Feng L, Cheng F, Ye Z, Li S, He Y, Yao X, et al.: The effect of renal ischemia-reperfusion injury on expression of RAE-1 and H60 in mice kidney. Transplant Proc 38: 2195–2198, 200616980040
49. Tonnerre P, Gérard N, Chatelais M, Poli C, Allard S, Cury S, et al.: MICA variant promotes allosensitization after kidney transplantation. J Am Soc Nephrol 24: 954–966, 201323539759
50. Kim J, Chang CK, Hayden T, Liu F-C, Benjamin J, Hamerman JA, et al.: The activating immunoreceptor NKG2D and its ligands are involved in allograft transplant rejection. J Immunol 179: 6416–6420, 200717982029
51. Chauveau A, Tonnerre P, Pabois A, Gavlovsky P-J, Chatelais M, Coupel S, et al.: Endothelial cell activation and proliferation modulate NKG2D activity by regulating MICA expression and shedding. J Innate Immun 6: 89–104, 201423860405