The molecular mechanisms operating in human organ transplant rejection are best inferred from the mRNAs expressed in biopsies because the corresponding proteins often have low expression and short ...half‐lives, while small non‐coding RNAs lack specificity. Associations should be characterized in a population that rigorously identifies T cell‐mediated (TCMR) and antibody‐mediated rejection (ABMR). This is best achieved in kidney transplant biopsies, but the results are generalizable to heart, lung, or liver transplants. Associations can be universal (all rejection), TCMR‐selective, or ABMR‐selective, with universal being strongest and ABMR‐selective weakest. Top universal transcripts are IFNG‐inducible (eg, CXCL11 IDO1, WARS) or shared by effector T cells (ETCs) and NK cells (eg, KLRD1, CCL4). TCMR‐selective transcripts are expressed in activated ETCs (eg, CTLA4, IFNG), activated (eg, ADAMDEC1), or IFNG‐induced macrophages (eg, ANKRD22). ABMR‐selective transcripts are expressed in NK cells (eg, FGFBP2, GNLY) and endothelial cells (eg, ROBO4, DARC). Transcript associations are highly reproducible between biopsy sets when the same rejection definitions, case mix, algorithm, and technology are applied, but exact ranks will vary. Previously published rejection‐associated transcripts resemble universal and TCMR‐selective transcripts due to incomplete representation of ABMR. Rejection‐associated transcripts are never completely rejection‐specific because they are shared with the stereotyped response‐to‐injury and innate immunity
The transcripts most strongly associated with organ graft rejection in biopsies include those selective for T cell–mediated rejection or antibody‐mediated rejection, and those expressed in both, including IFNG‐induced transcripts and transcripts shared by effector T cells and NK cells, but exact rankings will reflect the composition of the biopsy population.
In kidney transplant biopsies, inflammation in areas of atrophy‐fibrosis (i‐IFTA) is associated with increased risk of failure, presumably because inflammation is evoked by recent parenchymal injury ...from rejection or other insults, but some cases also have rejection. The present study explored the frequency of rejection in i‐IFTA, by using histology Banff 2015 and a microarray‐based molecular diagnostic system (MMDx). In unselected indication biopsies (108 i‐IFTA, 73 uninflamed IFTA i0‐IFTA, and 53 no IFTA), i‐IFTA biopsies occurred later, showed more scarring, and had more antibody‐mediated rejection (ABMR) based on histology (28%) and MMDx (45%). T cell–mediated rejection (TCMR) was infrequent in i‐IFTA based on histology (8%) and MMDx (16%). Twelve i‐IFTA biopsies (11%) had molecular TCMR not diagnosed by histology, although 6 were called borderline and almost all had histologic TCMR lesions. The prominent feature of i‐IFTA biopsies was molecular injury (eg, acute kidney injury AKI transcripts). In multivariate analysis of biopsies >1 year posttransplant, the strongest associations with graft loss were AKI transcripts and histologic atrophy‐scarring; i‐IFTA was not significant when molecular AKI was included. We conclude that i‐IFTA in indication biopsies reflects recent/ongoing parenchymal injury, often with concomitant ABMR but few with TCMR. Thus, the application of Banff i‐IFTA in the population of late biopsies needs to be reconsidered.
Molecular analysis of indication kidney transplant biopsies with inflammation in areas of scarring (i‐IFTA) reveals extensive recent or ongoing parenchymal injury, often with concomitant antibody‐mediated rejection, but usually without T cell– mediated rejection, suggesting Banff 2017 terminology classifying such biopsies as chronic active TCMR should be revisited.
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.
In a population of kidney transplant indication biopsies with a molecular diagnosis of antibody‐mediated rejection, those without compared to those with donor‐specific antibody typically occur earlier, are less active, and are more often C4d‐negative but have similar graft loss risk and, according to genome‐wide analyses, involve the same mechanisms.
This review outlines the molecular disease states in kidney transplant biopsies as documented in the development of the Molecular Microscope Diagnostic System (MMDx). These states include T ...cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), recent parenchymal injury, and irreversible atrophy-fibrosis. The MMDx project, initiated through a Genome Canada grant, is a collaboration involving many centers. MMDx uses genome-wide microarrays to measure transcript expression, interprets the results using ensembles of machine learning algorithms, and generates a report. Experimental studies in mouse models and cell lines were extensively used to annotate molecular features and interpret the biopsy results. Over time, MMDx revealed unexpected aspects of the disease states: for example, AMR is usually C4d-negative and often DSA-negative, and subtle "Minor" AMR-like states are frequent. Parenchymal injury correlates with both reduced glomerular filtration rate and increased risk of graft loss. In kidneys with rejection, injury features, not rejection activity, are the strongest predictors of graft survival. Both TCMR and AMR produce injury, but TCMR induces immediate nephron injury and accelerates atrophy-fibrosis, whereas AMR induces microcirculation and glomerular damage that slowly leads to nephron failure and atrophy-fibrosis. Plasma donor-derived cell-free DNA levels correlate strongly with AMR activity, acute kidney injury, and in a complex way with TCMR activity. Thus, the MMDx project has documented the molecular processes that underlie the clinical and histologic states in kidney transplants, and provides a diagnostic tool that can be used to calibrate biomarkers, optimize histology interpretation, and guide clinical trials.
We previously reported a system for assessing rejection in kidney transplant biopsies using microarray‐based gene expression data, the Molecular Microscope® Diagnostic System (MMDx). The present ...study was designed to optimize the accuracy and stability of MMDx diagnoses by replacing single machine learning classifiers with ensembles of diverse classifier methods. We also examined the use of automated report sign‐outs and the agreement between multiple human interpreters of the molecular results. Ensembles generated diagnoses that were both more accurate than the best individual classifiers, and nearly as stable as the best, consistent with expectations from the machine learning literature. Human experts had ≈93% agreement (balanced accuracy) signing out the reports, and random forest‐based automated sign‐outs showed similar levels of agreement with the human experts (92% and 94% for predicting the expert MMDx sign‐outs for T cell–mediated (TCMR) and antibody‐mediated rejection (ABMR), respectively). In most cases disagreements, whether between experts or between experts and automated sign‐outs, were in biopsies near diagnostic thresholds. Considerable disagreement with histology persisted. The balanced accuracies of MMDx sign‐outs for histology diagnoses of TCMR and ABMR were 73% and 78%, respectively. Disagreement with histology is largely due to the known noise in histology assessments (ClinicalTrials.gov NCT01299168).
The authors find that using ensembles of machine learning classifiers rather than single classifiers, gene sets, or single genes optimizes the precision and accuracy of molecular kidney transplant biopsy interpretation, but many discrepancies with histology persist, largely because of the irreducible noise in histology.
This review describes the development of the Molecular Microscope Diagnostic System (MMDx) for heart transplant endomyocardial biopsies (EMBs). MMDx-Heart uses microarrays to measure biopsy-based ...gene expression and ensembles of machine learning algorithms to interpret the results and compare each new biopsy to a large reference set of earlier biopsies. MMDx assesses T cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), recent parenchymal injury, and atrophy-fibrosis, continually "learning" from new biopsies. Rejection-associated transcripts mapped in kidney transplants and experimental systems were used to identify TCMR, AMR, and recent injury-induced inflammation. Rejection and injury emerged as gradients of intensity, rather than binary classes. AMR was one-third donor-specific antibody (DSA)-negative, and many EMBs first considered to have no rejection displayed minor AMR-like changes, with increased probability of DSA positivity and subtle inflammation. Rejection-associated transcript-based algorithms now classify EMBs as "Normal," "Minor AMR changes," "AMR," "possible AMR," "TCMR," "possible TCMR," and "recent injury." Additionally, MMDx uses injury-associated transcript sets to assess the degree of parenchymal injury and atrophy-fibrosis in every biopsy and study the effect of rejection on the parenchyma. TCMR directly injures the parenchyma whereas AMR usually induces microcirculation stress but relatively little initial parenchymal damage, although slowly inducing parenchymal atrophy-fibrosis. Function (left ventricular ejection fraction) and short-term risk of failure are strongly determined by parenchymal injury. These discoveries can guide molecular diagnostic applications, either as a central MMDx system or adapted to other platforms. MMDx can also help calibrate noninvasive blood-based biomarkers to avoid unnecessary biopsies and monitor response to therapy.
The relationship between the donor-derived cell-free DNA fraction (dd-cfDNA%) in plasma in kidney transplant recipients at time of indication biopsy and gene expression in the biopsied allograft has ...not been defined.
In the prospective, multicenter Trifecta study, we collected tissue from 300 biopsies from 289 kidney transplant recipients to compare genome-wide gene expression in biopsies with dd-cfDNA(%) in corresponding plasma samples drawn just before biopsy. Rejection was assessed with the microarray-based Molecular Microscope Diagnostic System using automatically assigned rejection archetypes and molecular report sign-outs, and histology assessments that followed Banff guidelines.
The median time of biopsy post-transplantation was 455 days (5 days to 32 years), with a case mix similar to that of previous studies: 180 (60%) no rejection, 89 (30%) antibody-mediated rejection (ABMR), and 31 (10%) T cell-mediated rejection (TCMR) and mixed. In genome-wide mRNA measurements, all 20 top probe sets correlating with dd-cfDNA(%) were previously annotated for association with ABMR and all types of rejection, either natural killer (NK) cell-expressed (
.,
,
,
, and
) or IFN-γ-inducible (
.,
,
,
, and
). Among gene set and classifier scores, dd-cfDNA(%) correlated very strongly with ABMR and all types of rejection, reasonably strongly with active TCMR, and weakly with inactive TCMR, kidney injury, and atrophy fibrosis. Active ABMR, mixed, and active TCMR had the highest dd-cfDNA(%), whereas dd-cfDNA(%) was lower in late-stage ABMR and less-active TCMR. By multivariate random forests and logistic regression, molecular rejection variables predicted dd-cfDNA(%) better than histologic variables.
The dd-cfDNA(%) at time of indication biopsy strongly correlates with active molecular rejection and has the potential to reduce unnecessary biopsies.
NCT04239703.
There is a major unmet need for improved accuracy and precision in the assessment of transplant rejection and tissue injury. Diagnoses relying on histologic and visual assessments demonstrate ...significant variation between expert observers (as represented by low kappa values) and have limited ability to assess many biological processes that produce little histologic changes, for example, acute injury. Consensus rules and guidelines for histologic diagnosis are useful but may have errors. Risks of over- or under-treatment can be serious: many therapies for transplant rejection or primary diseases are expensive and carry risk for significant adverse effects. Improved diagnostic methods could alleviate healthcare costs by reducing treatment errors, increase treatment efficacy, and serve as useful endpoints for clinical trials of new agents that can improve outcomes. Molecular diagnostic assessments using microarrays combined with machine learning algorithms for interpretation have shown promise for increasing diagnostic precision via probabilistic assessments, recalibrating standard of care diagnostic methods, clarifying ambiguous cases, and identifying potentially missed cases of rejection. This review describes the development and application of the Molecular Microscope® Diagnostic System (MMDx), and discusses the history and reasoning behind many common methods, statistical practices, and computational decisions employed to ensure that MMDx scores are as accurate and precise as possible. MMDx provides insights on disease processes and highly reproducible results from a comparatively small amount of tissue and constitutes a general approach that is useful in many areas of medicine, including kidney, heart, lung, and liver transplants, with the possibility of extrapolating lessons for understanding native organ disease states.
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