Molecular diagnosis of ABMR with or without donor-specific antibody in kidney transplant biopsies: Differences in timing and intensity but similar mechanisms and outcomes.

We studied the clinical, histologic, and molecular features distinguishing DSA-negative from DSA-positive molecularly defined antibody-mediated rejection (mABMR). We analyzed mABMR biopsies with available DSA assessments from the INTERCOMEX study: 148 DSA-negative versus 248 DSA-positive, compared with 864 no rejection (excluding TCMR and Mixed). DSA-positivity varied with mABMR stage: early-stage (EABMR) 56%; fully developed (FABMR) 70%; and late-stage (LABMR) 58%. DSA-negative patients with mABMR were usually sensitized, 60% being HLA antibody-positive. Compared with DSA-positive mABMR, DSA-negative mABMR was more often C4d-negative; earlier by 1.5 years (average 2.4 vs. 3.9 years); and had lower ABMR activity and earlier stage in molecular and histology features. However, the top ABMR-associated transcripts were identical in DSA-negative versus DSA-positive mABMR, for example, NK-associated (e.g., KLRD1 and GZMB) and IFNG-inducible (e.g., PLA1A). Genome-wide class comparison between DSA-negative and DSA-positive mABMR showed no significant differences in transcript expression except those related to lower intensity and earlier time of DSA-negative ABMR. Three-year graft loss in DSA-negative mABMR was the same as DSA-positive mABMR, even after adjusting for ABMR stage. Thus, compared with DSA-positive mABMR, DSA-negative mABMR is on average earlier, less active, and more often C4d-negative but has similar graft loss, and genome-wide analysis suggests that it involves the same mechanisms. SUMMARY SENTENCE: In 398 kidney transplant biopsies with molecular antibody-mediated rejection, the 150 DSA-negative cases are earlier, less intense, and mostly C4d-negative, but use identical molecular mechanisms and have the same risk of graft loss as the 248 DSA-positive cases.

The Biology and Molecular Basis of Organ Transplant Rejection.

Allograft rejection is defined as tissue injury in a transplanted allogeneic organ produced by the effector mechanisms of the adaptive alloimmune response. Effector T lymphocytes and IgG alloantibodies cause two different types of rejection that can occur either individually or simultaneously: T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR). In TCMR, cognate effector T cells infiltrate the graft and orchestrate an interstitial inflammatory response in the kidney interstitium in which effector T cells engage antigen-presenting myeloid cells, activating the T cells, antigen-presenting cells, and macrophages. The result is intense expression of IFNG and IFNG-induced molecules, expression of effector T cell molecules and macrophage molecules and checkpoints, and deterioration of parenchymal function. The diagnostic lesions of TCMR follow, i.e. interstitial inflammation, parenchymal deterioration, and intimal arteritis. In ABMR, HLA IgG alloantibodies produced by plasma cells bind to the donor antigens on graft microcirculation, leading to complement activation, margination, and activation of NK cells and neutrophils and monocytes, and endothelial injury, sometimes with intimal arteritis. TCMR becomes infrequent after 5-10 years post-transplant, probably reflecting adaptive mechanisms such as checkpoints, but ABMR can present even decades post-transplant. Some rejection is triggered by inadequate immunosuppression and non-adherence, challenging the clinician to target effective immunosuppression even decades post-transplant.

Using Regression Equations to Enhance Interpretation of Histology Lesions of Kidney Transplant Rejection.

BACKGROUND: The Banff system for histologic diagnosis of rejection in kidney transplant biopsies uses guidelines to assess designated features-lesions, donor-specific antibody (DSA), and C4d staining. We explored whether using regression equations to interpret the features as well as current guidelines could establish the relative importance of each feature and improve histologic interpretation. METHODS: We developed logistic regression equations using the designated features to predict antibody-mediated rejection (AMR/mixed) and T-cell-mediated rejection (TCMR/mixed) in 1679 indication biopsies from the INTERCOMEX study ( ClinicalTrials.gov NCT01299168). Equations were trained on molecular diagnoses independent of the designated features. RESULTS: In regression and random forests, the important features predicting molecular rejection were as follows: for AMR, ptc and g, followed by cg; for TCMR, t > i. V-lesions were relatively unimportant. C4d and DSA were also relatively unimportant for predicting AMR: by AUC, the model excluding them (0.853) was nearly as good as the model including them (0.860). Including time posttransplant slightly but significantly improved all models. By AUC, regression predicted molecular AMR and TCMR better than Banff histologic diagnoses. More importantly, in biopsies called "no rejection" by Banff guidelines, regression equations based on histology features identified histologic and molecular rejection-related changes in some biopsies and improved survival predictions. Thus, regression can screen for missed rejection. CONCLUSIONS: Using lesion-based regression equations in addition to Banff histology guidelines defines the relative important of histology features for identifying rejection, allows screening for potential missed diagnoses, and permits early estimates of AMR when C4d and DSA are not available.

Global coverage of health information systems for kidney disease: availability, challenges, and opportunities for development.

Development and planning of health care services requires robust health information systems to define the burden of disease, inform policy development, and identify opportunities to improve service provision. The global coverage of kidney disease health information systems has not been well reported, despite their potential to enhance care. As part of the Global Kidney Health Atlas, a cross-sectional survey conducted by the International Society of Nephrology, data were collected from 117 United Nations member states on the coverage and scope of kidney disease health information systems and surveillance practices. Dialysis and transplant registries were more common in high-income countries. Few countries reported having nondialysis chronic kidney disease and acute kidney injury registries. Although 62% of countries overall could estimate their prevalence of chronic kidney disease, less than 24% of low-income countries had access to the same data. Almost all countries offered chronic kidney disease testing to patients with diabetes and hypertension, but few to high-risk ethnic groups. Two-thirds of countries were unable to determine their burden of acute kidney injury. Given the substantial heterogeneity in the availability of health information systems, especially in low-income countries and across nondialysis chronic kidney disease and acute kidney injury, a global framework for prioritizing development of these systems in areas of greatest need is warranted.