Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials.

The present AST-IDCOP guidelines update information on BK polyomavirus (BKPyV) infection, replication, and disease, which impact kidney transplantation (KT), but rarely non-kidney solid organ transplantation (SOT). As pretransplant risk factors in KT donors and recipients presently do not translate into clinically validated measures regarding organ allocation, antiviral prophylaxis, or screening, all KT recipients should be screened for BKPyV-DNAemia monthly until month 9, and then every 3 months until 2 years posttransplant. Extended screening after 2 years may be considered in pediatric KT. Stepwise immunosuppression reduction is recommended for KT patients with plasma BKPyV-DNAemia of >1000 copies/mL sustained for 3 weeks or increasing to >10 000 copies/mL reflecting probable and presumptive BKPyV-associated nephropathy, respectively. Reducing immunosuppression is also the primary intervention for biopsy-proven BKPyV-associated nephropathy. Hence, allograft biopsy is not required for treating BKPyV-DNAemic patients with baseline renal function. Despite virological rationales, proper randomized clinical trials are lacking to generally recommend treatment by switching from tacrolimus to cyclosporine-A, from mycophenolate to mTOR inhibitors or leflunomide or by the adjunct use of intravenous immunoglobulins, leflunomide, or cidofovir. Fluoroquinolones are not recommended for prophylaxis or therapy. Retransplantation after allograft loss due to BKPyV nephropathy can be successful if BKPyV-DNAemia is definitively cleared, independent of failed allograft nephrectomy.

BK polyomavirus in solid organ transplantation-Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice.

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.

Deep learning-based histopathologic assessment of kidney tissue

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ajt.15416

Absolute quantification of donor-derived cell-free DNA as a marker of rejection and graft injury in kidney transplantation: Results from a prospective observational study.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ajt.15822

High levels of dd-cfDNA identify patients with TCMR 1A and borderline allograft rejection at elevated risk of graft injury

The Banff Classification of Allograft Pathology is an international consensus classification for the reporting of biopsies from solid organ transplants. Since its initial conception in 1991 for renal transplants, it has undergone review every 2 years, with attendant updated publications. The rapid expansion of knowledge in the field has led to numerous revisions of the classification. The resultant dispersal of relevant content makes it difficult for novices and experienced pathologists to faithfully apply the classification in routine diagnostic work and in clinical trials. This review shall provide a complete and simple illustrated reference guide of the Banff Classification of Kidney Allograft Pathology based on all publications including the 2017 update. It is intended as a concise desktop reference for pathologists and clinicians, providing definitions, Banff Lesion Scores and Banff Diagnostic Categories. An online website reference guide hosted by the Banff Foundation for Allograft Pathology (www.banfffoundation.org) is being developed, which will be updated with future refinement of the Banff Classification from 2019 onward.

/pdf/a-2018-reference-guide-to-the-banff-classification-of-renal-1y52taprfj.pdf

A 2018 Reference Guide to the Banff Classification of Renal Allograft Pathology.

Pancreas transplant longevity is limited by immune rejection, which is diagnosed by graft biopsy using the Banff Classification. The histological criteria for antibody-mediated rejection (AMR) are poorly reproducible and inconsistently associated with outcome. We hypothesized that a 34-gene set associated with antibody-mediated rejection in other solid organ transplants could improve diagnosis in pancreas grafts. The AMR 34-gene set, comprising endothelial, natural killer cell and inflammatory genes, was quantified using the NanoString platform in 52 formalin-fixed, paraffin-embedded pancreas transplant biopsies from 41 patients: 15 with pure AMR or mixed rejection, 22 with T cell-mediated rejection/borderline and 15 without rejection. The AMR 34-gene set was significantly increased in pure AMR and mixed rejection (P = .001) vs no rejection. The gene set predicted histological AMR with an area under the receiver operating characteristic curve (ROC AUC) of 0.714 (P = .004). The AMR 34-gene set was the only biopsy feature significantly predictive of allograft failure in univariate analysis (P = .048). Adding gene expression to DSA and histology increased ROC AUC for the prediction of failure from 0.736 to 0.770, but this difference did not meet statistical significance. In conclusion, assessment of transcripts has the potential to improve diagnosis and outcome prediction in pancreas graft biopsies.

Molecular assessment of antibody-mediated rejection in human pancreas allograft biopsies.

A rare case of nephrotic syndrome and Tangier disease.

Background Post-transplant glomerulonephritis (PTGN) has been associated with inferior long-term allograft survival, and its incidence varies widely in the literature. Methods This is a cohort study of 7,623 patients transplanted between 2005 and 2016 at four major transplant UK centres. The diagnosis of glomerulonephritis (GN) in the allograft was extracted from histology reports aided by the use of text-mining software. The incidence of the four most common GN post-transplantation was calculated, and the risk factors for disease and allograft outcomes were analyzed. Results In total, 214 patients (2.8%) presented with PTGN. IgA nephropathy (IgAN), focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and membranoproliferative/mesangiocapillary GN (MPGN/MCGN) were the four most common forms of post-transplant GN. Living donation, HLA DR match, mixed race, and other ethnic minority groups were associated with an increased risk of developing a PTGN. Patients with PTGN showed a similar allograft survival to those without in the first 8 years of post-transplantation, but the results suggest that they do less well after that timepoint. IgAN was associated with the best allograft survival and FSGS with the worst allograft survival. Conclusions PTGN has an important impact on long-term allograft survival. Significant challenges can be encountered when attempting to analyze large-scale data involving unstructured or complex data points, and the use of computational analysis can assist.

Naomi Simmonds

Papers

A 2018 Reference Guide to the Banff Classification of Renal Allograft Pathology.

Molecular assessment of antibody-mediated rejection in human pancreas allograft biopsies.

A rare case of nephrotic syndrome and Tangier disease.

Incidence, Risk Factors, and Effect on Allograft Survival of Glomerulonephritis Post-transplantation in a United Kingdom Population: Cohort Study