Stegall, Mark D.

Significance Statement The quality of a kidney obtained from a living donor is often inferred from the donor’s age, risk factors, and kidney function. Little is known about the influence of a donated kidney’s structural features on the risk of death-censored graft failure in the recipient. In an analysis of 2293 kidney donor-recipient pairs, the authors identified subclinical nephrosclerosis, larger nephron size (but not nephron number), and smaller medullary volume as structural predictors of death-censored graft failure that were independent of both donor and recipient clinical characteristics. These findings provide important insights into the factors that define the “intrinsic quality” of the living kidney donor graft at the time of donation, and support use of intraoperative biopsies to identify donor kidneys that are at higher risk for failure. Background Nephrosclerosis, nephron size, and nephron number vary among kidneys transplanted from living donors. However, whether these structural features predict kidney transplant recipient outcomes is unclear. Methods Our study used computed tomography (CT) and implantation biopsy to investigate donated kidney features as predictors of death-censored graft failure at three transplant centers participating in the Aging Kidney Anatomy study. We used global glomerulosclerosis, interstitial fibrosis/tubular atrophy, artery luminal stenosis, and arteriolar hyalinosis to measure nephrosclerosis; mean glomerular volume, cortex volume per glomerulus, and mean cross-sectional tubular area to measure nephron size; and calculations from CT cortical volume and glomerular density on biopsy to assess nephron number. We also determined the death-censored risk of graft failure with each structural feature after adjusting for the predictive clinical characteristics of donor and recipient. Results The analysis involved 2293 donor-recipient pairs. Mean recipient follow-up was 6.3 years, during which 287 death-censored graft failures and 424 deaths occurred. Factors that predicted death-censored graft failure independent of both donor and recipient clinical characteristics included interstitial fibrosis/tubular atrophy, larger cortical nephron size (but not nephron number), and smaller medullary volume. In a subset with 12 biopsy section slides, arteriolar hyalinosis also predicted death-censored graft failure. Conclusions Subclinical nephrosclerosis, larger cortical nephron size, and smaller medullary volume in healthy donors modestly predict death-censored graft failure in the recipient, independent of donor or recipient clinical characteristics. These findings provide insights into a graft’s “intrinsic quality” at the time of donation, and further support the use of intraoperative biopsies to identify kidney grafts that are at higher risk for failure.

The liver is an immunologically active organ with a tolerogenic microenvironment at a quiescent state. The immunoregulatory properties of the liver appear to be retained after transplantation because liver allografts can reduce alloresponses against other organs that are simultaneously transplanted. Mechanisms of this phenomenon remain unknown. Given the known immunomodulatory properties of mesenchymal stromal cells (MSCs), we hypothesized that liver mesenchymal stromal cells (L‐MSCs) are superior immunomodulators and contribute to liver‐mediated tolerance. L‐MSCs, generated from human liver allograft biopsies, were compared with adipose mesenchymal stromal cells (A‐MSCs) and bone marrow mesenchymal stromal cells (BM‐MSCs). Trilineage differentiation of L‐MSCs was confirmed by immunohistochemistry. Comparative phenotypic analyses were done by flow cytometry and transcriptome analyses by RNA sequencing in unaltered cell cultures. The in vitro functional analyses were performed using alloreactive T cell proliferation assays. The transcriptome analysis showed that the L‐MSCs are different than the A‐MSCs and BM‐MSCs, with significant enrichment of genes and gene sets associated with immunoregulation. Compared with the others, L‐MSCs were found to express higher cell surface levels of several select immunomodulatory molecules. L‐MSCs (versus A‐MSCs/BM‐MSCs) inhibited alloreactive T cell proliferation (22.7% versus 56.4%/58.7%, respectively; P < 0.05) and reduced the frequency of interferon ɤ–producing T cells better than other MSCs (52.8% versus 94.4%/155.4%; P < 0.05). The antiproliferative impact of L‐MSCs was not dependent on cell‐to‐cell contact, could be reversed incompletely by blocking programmed death ligand 1, and required a higher concentration of the competitive inhibitor of indoleamine 2,3‐dioxygenase for complete reversal. In conclusion, L‐MSCs appear to be uniquely well‐equipped immunomodulatory cells, and they are more potent than A‐MSCs and BM‐MSCs in that capacity, which suggests that they may contribute to liver‐induced systemic tolerance.

Background. Glucagon-like peptide-1 receptor agonists (GLP1RA) have been shown to improve glucose control and diabetes-related comorbidities in patients without solid organ transplants. The effectiveness, safety, and tolerability of GLP1RA after kidney transplantation have not been adequately studied. Methods. We retrospectively reviewed data on kidney transplant recipients performed in our institution, who were initiated on GLP1RA either for the treatment of type 2 diabetes diagnosed before transplantation or posttransplant diabetes. We analyzed efficacy, safety, and the effect on kidney allograft function. Results. Seventeen kidney transplant recipients were initiated on GLP1RA therapy, 14 of which remained on the medication for at least 12 months. The use of GLP1RA had no significant impact on weight loss, but was associated with a significant reduction in the total daily insulin dose, from the median of 63 [interquartile range 43-113] IU to 44 [interquartile range 25-88] and reduction in the risk of hypoglycemia in patients who were on therapy for at least approximately 12 months. Kidney function remained stable and none of the recipients experienced acute rejection. Tacrolimus dose was not significantly changed. Five patients (29%) discontinued GLP1RA therapy—4 due to side effects and 1 due to uncontrolled hyperglycemia. Conclusions. GLP1RA may be a relatively safe and effective treatment for kidney transplant recipients with type 2 diabetes that allows for a reduction in insulin requirements. More studies are needed to determine whether the use of these agents will translate into an improvement in allograft and patient survival.

AbstractLarge multicenter, randomized controlled trials are the paradigm for determining the efficacy and safety of new therapies. However, applying this classical approach to many areas of transplantation is difficult. For most types of organ transplants, the number of transplants performed is too small for such a trial (lung, pancreas, or vascular composite transplantation are examples). In larger populations such as kidney transplantation, the major unmet needs commonly involve small subsets of patients (antibody‐mediated rejection, recurrent renal disease, etc). This issue is not unique to transplantation and has been successfully overcome in other areas of medicine. In oncology, for example, novel trial designs such as adaptive trial design and master protocols are now relatively common. In addition, the existence of multicenter, ongoing clinical research consortia have greatly enhanced the successful implementation of these novel trial designs. In this manuscript, we examine how novel trial designs, master protocols, and research consortia might enhance studies in transplantation aimed at the regulatory approval of new agents. Our premise is that more efficient approaches to clinical trials already exist and, through a coordinated effort by researchers, the pharmaceutical industry, and regulatory bodies like the FDA, they can be implemented in transplantation.

AbstractKidney paired donation (KPD) and the new kidney allocation system (KAS) in the United States have led to improved transplantation rates for highly sensitized candidates. We aimed to assess the potential need for other approaches to improve the transplantation rate of highly sensitized candidates such as desensitization. Using the UNOS STAR file, we analyzed transplant rates in a prevalent active waiting‐list cohort as of June 1, 2016, followed for 1 year. The overall transplantation rate was 18.9% (11 129/58769). However, only 9.7% (213/2204) of candidates with a calculated panel reactive antibody ≥99.9% received a transplant, and highly sensitized candidates were less likely to receive a living donor transplant. Among candidates with a CPRA ≥ 99.5% (ie. 100%), only 2.5% of transplants were from living donors (13 total, 7 from KPD). Nearly 4 years after KAS (6/30/2018), 1791 actively wait‐listed candidates had a CPRA of ≥99.9% and 34.6% (620/1791) of these had ≥5 years of waiting time. Thus, despite KPD and KAS, many sensitized candidates have not been transplanted even with prolonged waiting time. We conclude that candidates with a CPRA ≥ 99.9% and sensitized candidates with an incompatible living donor and prolonged waiting time may benefit from desensitization to improve their ability to receive a transplant.

Abstract Background: Post-transplant lymphoproliferative disorder (PTLD) represents one of the most serious consequences of immunosuppression in patients with solid organ transplantation. The incidence of PTLD is related to the organ transplanted and is dependent on the duration of follow-up. In various publications, the incidence of PTLD in renal transplantation ranges between 0.8% to 1.2%. In a previous study, the development of monoclonal (M) protein following liver transplantation is associated with the development of PTLD. In this study, we investigate this relationship in the kidney transplant population. Methods: A total of 3518 patients underwent kidney transplantation between 1963 to March 2006. These patients were cross referenced with the Monoclonal Gammopathy of Undetermined Significance (MGUS) database. Results: We identified 97 patients who had a monoclonal gammopathy either before or after transplantation. Patients with amyloidosis, multiple myeloma, heavy and light chain deposition disease and multi-organ transplantation were excluded from the analysis. A total of 69 patients met the inclusion criteria. Ten of the 69 (14.5%) patients developed PTLD. Median follow-up was 14.8 years. Twenty three patients had pretransplant MGUS, 20 patients developed MGUS following the transplant, and the other 26 did not have a monoclonal protein study prior to the transplant. Of the 23 patients who had a positive MGUS prior to the transplant, 4 patients (17.3%) developed PTLD, 1 patient developed EBV positive diffuse large cell lymphoma (DLCL), 1 developed EBV negative DLCL, 1 developed Hodgkin’s lymphoma and 1 developed increased plasma cells in bone marrow (20%) with stable M protein with no evidence of progression to multiple myeloma. None of these patients had a quantifiable M-protein prior to transplantation. The mean duration from diagnosis of MGUS to PTLD was 8.2 years (range 3 to 14 years). Of the 20 patients with a negative pre-transplant study for para proteniemia, 2 (10%) developed PTLD (T cell lymphoproliferative disorder). Two patients developed MGUS after the transplant at 1 and 12 years post transplant. It took an average of 15 years to develop PTLD after the diagnosis of MGUS. Four of the 26 patients who did not have a pretransplant study for MGUS developed PTLD. These included an EBV positive gamma delta type T cell lymphoproliferative disorder, an EBV positive plasmablastic lymphoma, one multiple myeloma and a plasmacytoma. The latter two patients had M-protein > 3g/dL. It took an average of 14 years after their transplant for these patients to develop PTLD. Conclusion: Our study showed that the development of a monoclonal protein in patients undergoing kidney transplantation is a strong risk factor for PTLD. Monoclonal protein study should be performed pretransplant and monitored post transplant as a surveillance of PTLD. Those who are positive or convert should be monitored closely for development of lymphoproliferative disorder.

Abstract Background: Monoclonal gammopathy of undetermined significance (MGUS) is reported in 3 to 5 percent of population, with the prevalence increasing with advancing age. Patients with MGUS are at increased risk for progression to multiple myeloma or other plasma cell dyscrasias. There is a paucity of information on clinical outcomes of patients with MGUS undergoing renal transplantation. A retrospective study was performed to determine wether MGUS is a contraindication to renal transplantation. Methods: Data was collected from both the kidney transplant and MGUS database. The diagnosis of MGUS was made on the basis of either serum protein electrophoresis (SPEP) or immunofixation after excluding multiple myeloma, amyloidosis and monoclonal immunoglobulin deposition disease. Results: Between 1977 and 2004, 3518 patients underwent kidney transplantation of whom 23 patients had a preexisting monoclonal gammopathy of undetermined significance (MGUS). Fourteen (61%) of these patients were males. The median age at the time of transplant was 59 ±12 years. Ten patients (43.5%) had IgG Kappa (GK), 7 (30.4%) had IgG Lambda (GL), 2 (8.7%) had IgA Lambda (AL), 1 (4.3%) had IgA Kappa (AK), 2 (8.7%) had IgM Lambda (ML). One patient had a biclonal gammopathy GL and ML. Patients were monitored with either SPEP or immunofixation for median duration of 1542 days after transplantation. Thirteen patients had either no change or stable monoclonal protein, 6 had a decrease in their paraprotein level. Two patients had a mild increase in their paraprotein. Two patients with GK developed into biclonal gammopathy (GK and AK). The median follow up of this cohort after the renal transplant was 1783 days. Twelve (52%) patients remained alive at the time of the study. A patient with GK prior to the transplant who underwent kidney transplantation twice developed a biclonal gammopathy and was found to have increased plasma cells (20%) in bone marrow after 14 years. On follow up for 6 years, his M-protein remained stable. Another patient was found to have 17% plasma cells around the time of kidney transplantation. He had a stable M-protein at follow-up, but underwent a stem cell transplant for recurrent immunotactoid glomerulonephritis. Two (9%) patients developed more than 15% plasma cells in their bone marrow with a stable M-protein. None of the patients with a preexisting MGUS evolved into multiple myeloma. Conclusion: In this small study, the presence of MGUS prior to kidney transplantation did not appear to have increased the incidence of multiple myeloma post transplant. Therefore, MGUS by itself should not be considered as an absolute contraindication for renal transplantation.

AbstractBackgroundCurrent therapy for Type 1 diabetes (T1D) is characterized by significant glucose variability (GV). Pancreas transplantation (PT) is performed in certain T1D patients with and without end‐stage renal disease. To date, GV has been examined to a limited extent after PT.MethodsWe investigated GV using continuous glucose monitoring (CGM) 3‐6 weeks after PT.ResultsEleven patients had simultaneous kidney pancreas transplantation (SPK), nine pancreas after kidney (PAK), and six pancreas transplantation alone (PTA). Mean CGM showed no difference between SPK, 126.5 ± 13.9, PAK 119.9 ± 12.8, and PTA 131.1 ± 29 mg/dL (P value .6). Percentage of time in range (TIR, 70‐180 mg/dL) was 92% for SPK, 93.4% in PAK, and 88.5% in PTA with only 0.3%, 1.5%, and 0.3% of time <70 mg/dL. Percentage >180 mg/dL was 7.9% for SPK, 4.9% PAK, and 11% in PTA. Other measures of GV were similar in the three cohorts. In six patients, CGM was performed before and after PT and improved significantly. GV was also better compared with a matched cohort of T1D patients.ConclusionsAll 3 types of PT resulted in excellent glucose control 3‐6 weeks post‐procedure. CGM outcomes represent an important objective outcome after PT.

Background. We examined the 10-year experience of Mayo Clinic's kidney paired donation (KPD).We aimed to determine the benefits for the recipients of enrolled ABO/HLA compatible pairs and determine the factors associated with prolonged KPD waiting time. Methods. We performed a retrospective study of 332 kidney transplants facilitated by the Mayo 3-site KPD program from September 2007 to June 2018. Results. The median (interquartile range) time from KPD entry to transplantation was 89 days (42-187 days). The factors independently associated with receiving a transplant >3 months after KPD entry included recipient blood type O and calculated panel reactive antibodies ≥98%. Fifty-four ABO/HLA compatible pairs participated in KPD for the following reasons: cytomegalovirus mismatch (18.5% [10/54]), Epstein-Barr virus (EBV) mismatch (EBV) (9.3% [5/54]), age/size mismatch (51.9% [28/54]), or altruistic reasons (20.3% [11/54]). Cytomegalovirus and EBV mismatch were avoided in 90% (9/10) and 100% (5/5) of cases. Recipients who entered KPD for age/size mismatch and altruistic reasons received kidneys from donors with lower Living Kidney Donor Profile Index scores than their actual donor (median [interquartile range] 31.5 [12.3-47]; P < 0.001 and 26 (-1 to 46); P = 0.01 points lower, respectively). Median time to transplant from KPD entry for compatible pair recipients was 70 days (41-163 days), and 44.4% (24/54) of these transplants were preemptive. All chains/swaps incorporating compatible pairs included ABO/HLA incompatible pairs. Conclusions. KPD should be considered for all living donor/recipient pairs because the recipients of these pairs can derive personal benefit from KPD while increasing the donor pool for difficult to match pairs.

Significance Statement Histopathologic assessment of kidney tissue currently relies on manual scoring or traditional image-processing techniques to quantify and classify tissue features, time-consuming approaches that have limited reproducibility. The authors present an alternative approach, featuring a convolutional neural network for multiclass segmentation of kidney tissue in sections stained by periodic acid–Schiff. Their findings demonstrate applicability of convolutional neural networks for tissue from multiple centers, for biopsies and nephrectomy samples, and for the analysis of both healthy and pathologic tissues. In addition, they validated the network’s results with components from the Banff classification system. Their convolutional neural network may have utility for quantitative studies involving kidney histopathology across centers and potential for application in routine diagnostics. Background 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). Methods 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. Results 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. Conclusions 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.