Liver-resident mesenchymal stem cells (L-MSCs) are superior inhibitors of alloreactive T cell responses compared to their counterparts from bone marrow (BM-MSCs) or adipose tissue (A-MSCs), ...suggesting a role in liver’s overall tolerogenic microenvironment. Whether L-MSCs also impact NK cell functions differently than other MSCs is not known. We generated and characterized L-MSCs, A-MSCs and BM-MSCs from human tissues. The mass spectrometry analysis demonstrated that L-MSC secretome is uniquely different than that of A-MSC/BM-MSC, with enriched protein sets involved in IFNγ responses and signaling. When co-cultured with primary human NK cells, L-MSCs but not other MSCs, decreased surface expression of activating receptors NKp44 and NKG2D. L-MSCs also decreased IFNγ secretion by IL-2-stimulated NK cells more effectively than other MSCs. Cytolytic function of NK cells were reduced significantly when co-cultured with L-MSCs, whereas A-MSCs or BM-MSCs did not have a major impact. Mechanistic studies showed that the L-MSC-mediated reduction in NK cell cytotoxicity is not through changes in secretion of the cytotoxic proteins Perforin, Granzyme A or B, but through increased production of HLA-C1 found in L-MSC secretome that inhibits NK cells by stimulating their inhibitory receptor KIRDL2/3. L-MSCs are more potent inhibitors of NK cell functions than A-MSC or BM-MSC. Combined with their T cell inhibitory features, these results suggest L-MSCs contribute to the tolerogenic liver microenvironment and liver-induced systemic tolerance often observed after liver transplantation.
The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized ...kidney tissue sections stained with periodic acid-Schiff (PAS).
We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network's glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies.
The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was "glomeruli" in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by "tubuli combined" and "interstitium." The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures.
This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.
Over the past decade, several studies have suggested that the complement system has an active role in both acute and chronic allograft rejection. These studies have been facilitated by improved ...techniques to detect antibody-mediated organ rejection, including immunohistological staining for C4d deposition in the allograft and solid-phase assays that identify donor-specific alloantibodies (DSAs) in the serum of transplant recipients. Studies with eculizumab, a humanized monoclonal antibody directed against complement component C5, have shown that activation of the terminal complement pathway is necessary for the development of acute antibody-mediated rejection in recipients of living-donor kidney allografts who have high levels of DSAs. The extent to which complement activation drives chronic antibody-mediated injury leading to organ rejection is less clear. In chronic antibody-mediated injury, early complement activation might facilitate chemotaxis of inflammatory cells into the allograft in a process that later becomes somewhat independent of DSA levels and complement factors. In this Review, we discuss the different roles that the complement system might have in antibody-mediated allograft rejection, with specific emphasis on renal transplantation.
AbstractObjectiveTo develop and validate an integrative system to predict long term kidney allograft failure.DesignInternational cohort study.SettingThree cohorts including kidney transplant ...recipients from 10 academic medical centres from Europe and the United States.ParticipantsDerivation cohort: 4000 consecutive kidney recipients prospectively recruited in four French centres between 2005 and 2014. Validation cohorts: 2129 kidney recipients from three centres in Europe and 1428 from three centres in North America, recruited between 2002 and 2014. Additional validation in three randomised controlled trials (NCT01079143, EudraCT 2007-003213-13, and NCT01873157).Main outcome measureAllograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed.ResultsAmong the 7557 kidney transplant recipients included, 1067 (14.1%) allografts failed after a median post-transplant follow-up time of 7.12 (interquartile range 3.51-8.77) years. In the derivation cohort, eight functional, histological, and immunological prognostic factors were independently associated with allograft failure and were then combined into a risk prediction score (iBox). This score showed accurate calibration and discrimination (C index 0.81, 95% confidence interval 0.79 to 0.83). The performance of the iBox was also confirmed in the validation cohorts from Europe (C index 0.81, 0.78 to 0.84) and the US (0.80, 0.76 to 0.84). The iBox system showed accuracy when assessed at different times of evaluation post-transplant, was validated in different clinical scenarios including type of immunosuppressive regimen used and response to rejection therapy, and outperformed previous risk prediction scores as well as a risk score based solely on functional parameters including estimated glomerular filtration rate and proteinuria. Finally, the accuracy of the iBox risk score in predicting long term allograft loss was confirmed in the three randomised controlled trials.ConclusionAn integrative, accurate, and readily implementable risk prediction score for kidney allograft failure has been developed, which shows generalisability across centres worldwide and common clinical scenarios. The iBox risk prediction score may help to guide monitoring of patients and further improve the design and development of a valid and early surrogate endpoint for clinical trials.Trial registrationClinicaltrials.gov NCT03474003.
We report results of a phase 2, randomized, multicenter, open‐label, two‐arm study evaluating the safety and efficacy of eculizumab in preventing acute antibody‐mediated rejection (AMR) in sensitized ...recipients of living‐donor kidney transplants requiring pretransplant desensitization (NCT01399593). In total, 102 patients underwent desensitization. Posttransplant, 51 patients received standard of care (SOC) and 51 received eculizumab. The primary end point was week 9 posttransplant treatment failure rate, a composite of: biopsy‐proven acute AMR (Banff 2007 grade II or III; assessed by blinded central pathology); graft loss; death; or loss to follow‐up. Eculizumab was well tolerated with no new safety concerns. No significant difference in treatment failure rate was observed between eculizumab (9.8%) and SOC (13.7%; P = .760). To determine whether data assessment assumptions affected study outcome, biopsies were reanalyzed by central pathologists using clinical information. The resulting treatment failure rates were 11.8% and 21.6% for the eculizumab and SOC groups, respectively (nominal P = .288). When reassessment included grade I AMR, the treatment failure rates were 11.8% (eculizumab) and 29.4% (SOC; nominal P = .048). This finding suggests a potential benefit for eculizumab compared with SOC in preventing acute AMR in recipients sensitized to their living‐donor kidney transplants (EudraCT 2010‐019630‐28).
In this study of terminal complement inhibition to prevent acute antibody‐mediated rejection in living‐donor kidney transplant recipients with preformed donor‐specific antibodies, prophylactic eculizumab does not significantly reduce the treatment failure rate compared with standard of care, but biopsy reanalysis suggests a benefit for eculizumab in preventing AMR in these patients. See the article by Glotz et al on page 2865.
Kidney allografts transplanted simultaneously with liver allografts from the same donor are known to be immunologically privileged. This is especially evident in recipients with high levels of ...donor-specific anti-HLA antibodies. Here we investigated the mechanisms of liver's protective impact using gene expression in the kidney allograft. Select solitary kidney transplant or simultaneous liver-kidney transplant recipients were retrospectively reviewed and separated into four groups: 16 cross-match negative kidney transplants, 15 cross-match positive kidney transplants, 12 cross-match negative simultaneous liver-kidney transplants, and nine cross-match-positive simultaneous liver-kidney transplants. Surveillance biopsies of cross-match-positive kidney transplants had increased expression of genes associated with donor-specific antigens, inflammation, and endothelial cell activation compared to cross-match-negative kidney transplants. These changes were not found in cross-match-positive simultaneous liver-kidney transplant biopsies when compared to cross-match-negative simultaneous liver-kidney transplants. In addition, simultaneously transplanting a liver markedly increased renal expression of genes associated with tissue integrity/metabolism, regardless of the cross-match status. While the expression of inflammatory gene sets in cross-match-positive simultaneous liver-kidney transplants was not completely reduced to the level of cross-match-negative kidney transplants, the downstream effects of donor-specific anti-HLA antibodies were blocked. Thus, simultaneous liver-kidney transplants can have a profound impact on the kidney allograft, not only by decreasing inflammation and avoiding endothelial cell activation in cross-match-positive recipients, but also by increasing processes associated with tissue integrity/metabolism by unknown mechanisms.
In simultaneous liver-kidney transplantation (SLK), the liver can protect the kidney from hyperacute rejection and may also decrease acute cellular rejection rates. Whether the liver protects against ...chronic injury is unknown. To answer this we studied renal allograft surveillance biopsies in 68 consecutive SLK recipients (14 with donor-specific alloantibodies at transplantation DSA+, 54 with low or no DSA, DSA–). These were compared with biopsies of a matched cohort of kidney transplant alone (KTA) recipients (28 DSA+, 108 DSA–). Overall 5-year patient and graft survival was not different: 93.8% and 91.2% in SLK, and 91.9% and 77.1% in KTA. In DSA+ recipients, KTA had a significantly higher incidence of acute antibody-mediated rejection (46.4% vs. 7.1%) and chronic transplant glomerulopathy (53.6% vs. 0%). In DSA– recipients at 5 years, KTA had a significantly higher cumulative incidence of T cell–mediated rejection (clinical plus subclinical, 30.6% vs. 7.4%). By 5 years, DSA+ KTA had a 44% decline in mean GFR while DSA+SLK had stable GFR. In DSA– KTA, the incidence of a combined endpoint of renal allograft loss or over a 50% decline in GFR was significantly higher (20.4% vs. 7.4%). Simultaneously transplanted liver allograft was the most predictive factor for a significantly lower incidence of cellular (odds ratio 0.13, 95% confidence interval 0.06–0.27) and antibody-mediated injury (odds ratio 0.11, confidence interval 0.03–0.32), as well as graft functional decline (odds ratio 0.22, confidence interval 0.06–0.59). Thus, SLK is associated with reduced chronic cellular and antibody-mediated alloimmune injury in the kidney allograft.
We aimed to determine the long-term outcomes of eculizumab-treated, positive crossmatch (+XM) kidney transplant recipients compared with +XM and age-matched negative crossmatch (−XM) controls. We ...performed an observational retrospective study and examined allograft survival, histologic findings, long-term B-cell flow cytometric XM (BFXM), and allograft-loss–associated factors. The mean (SD) posttransplant follow-up was 6.3 (2.5) years in the eculizumab group; 7.6 (3.5), +XM control group; 7.9 (2.5), −XM control group. The overall and death-censored allograft survival rates were similar in +XM groups (P = .73, P = .48) but reduced compared with −XM control patients (P < .001, P < .001). In the eculizumab-treated group, 57.9% (11/19) of the allografts had chronic antibody-mediated rejection, but death-censored allograft survival was 76.6%, 5 years; 75.4%, 7 years. Baseline IgG3 positivity and BFXM ≥300 were associated with allograft loss. C1q positivity was also associated with allograft loss but did not reach statistical significance. Donor-specific antibodies appeared to decrease in eculizumab-treated patients. After excluding patients with posttransplant plasmapheresis, 42.3% (9/21) had negative BFXMs; 31.8% (7/22), completely negative single-antigen beads 1 year posttransplant. Eculizumab-treated +XM patients had reduced allograft survival compared with −XM controls but similar survival to +XM controls. BFXM and complement-activating donor-specific antibodies (by IgG3 and C1q testing) may be used for risk stratification in +XM transplantation.
The XV. Banff conference for allograft pathology was held in conjunction with the annual meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh, PA (USA) and focused ...on refining recent updates to the classification, advances from the Banff working groups, and standardization of molecular diagnostics. This report on kidney transplant pathology details clarifications and refinements to the criteria for chronic active (CA) T cell–mediated rejection (TCMR), borderline, and antibody‐mediated rejection (ABMR). The main focus of kidney sessions was on how to address biopsies meeting criteria for CA TCMR plus borderline or acute TCMR. Recent studies on the clinical impact of borderline infiltrates were also presented to clarify whether the threshold for interstitial inflammation in diagnosis of borderline should be i0 or i1. Sessions on ABMR focused on biopsies showing microvascular inflammation in the absence of C4d staining or detectable donor‐specific antibodies; the potential value of molecular diagnostics in such cases and recommendations for use of the latter in the setting of solid organ transplantation are presented in the accompanying meeting report. Finally, several speakers discussed the capabilities of artificial intelligence and the potential for use of machine learning algorithms in diagnosis and personalized therapeutics in solid organ transplantation.
This report focuses on the clarification of the criteria for chronic active T cell–mediated rejection and antibody‐mediated rejection and the optimization of the inflammation threshold for the diagnosis of borderline for acute T cell–mediated rejection, and discusses the potential to use machine learning in diagnostics and personalized therapeutics in solid organ transplantation.
Nephron number currently can be estimated only from glomerular density on a kidney biopsy combined with cortical volume from kidney imaging. Because of measurement biases, refinement of this approach ...and validation across different patient populations have been needed. The prognostic importance of nephron number also has been unclear. The authors present an improved method of estimating nephron number that corrects for several biases, resulting in a 27% higher nephron number estimate for donor kidneys compared with a prior method. After accounting for comorbidities, the new nephron number estimate does not differ between kidney donors and kidney patients with tumor and shows consistent associations with clinical characteristics across these two populations. The findings also indicate that low nephron number predicts CKD independent of biopsy and clinical characteristics in both populations.
Nephron number can be estimated from glomerular density and cortical volume. However, because of measurement biases, this approach needs refinement, comparison between disparate populations, and evaluation as a predictor of CKD outcomes.
We studied 3020 living kidney donors and 1354 patients who underwent radical nephrectomy for tumor. We determined cortex volume of the retained kidney from presurgical imaging and glomerular density by morphometric analysis of needle core biopsy of the donated kidney and wedge sections of the removed kidney. Glomerular density was corrected for missing glomerular tufts, absence of the kidney capsule, and then tissue shrinkage on the basis of analysis of 30 autopsy kidneys. We used logistic regression (in donors) and Cox proportional hazard models (in patients with tumor) to assess the risk of CKD outcomes associated with nephron number.
Donors had 1.17 million nephrons per kidney; patients with tumor had 0.99 million nephrons per kidney. A lower nephron number was associated with older age, female sex, shorter height, hypertension, family history of ESKD, lower GFR, and proteinuria. After adjusting for these characteristics, nephron number did not differ between donors and patients with tumor. Low nephron number (defined by <5th or <10th percentile by age and sex in a healthy subset) in both populations predicted future risk of CKD outcomes independent of biopsy and clinical characteristics.
Compared with an older method for estimating nephron number, a new method that addresses several sources of bias results in nephron number estimates that are 27% higher in donors and 1% higher in patients with tumor and shows consistency between two populations. Low nephron number independently predicts CKD in both populations.
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