An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms

Precision diagnostics in transplanted organs using microarray-assessed gene expression: concepts and technical methods of the Molecular Microscope® Diagnostic System (MMDx)

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.

Redefining the molecular rejection states in 3230 heart transplant biopsies: Relationships to parenchymal injury and graft survival

The first-generation Molecular Microscope (MMDx) system for heart transplant endomyocardial biopsies used expression of rejection-associated transcripts (RATs) to diagnose not only T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) but also acute injury. However, the ideal system should detect rejection without being influenced by injury, to permit analysis of the relationship between rejection and parenchymal injury. To achieve this, we developed a new rejection classification in an expanded cohort of 3230 biopsies: 1641 from INTERHEART (ClinicalTrials.gov NCT02670408), plus 1589 service biopsies added to improve the power of the machine learning algorithms. The new system used 6 rejection classifiers instead of RATs and generated 7 rejection archetypes: No rejection, 48%; Minor, 24%; TCMR1, 2.3%; TCMR2, 2.7%; TCMR/mixed, 2.7%; early-stage ABMR, 3.9%; and fully developed ABMR, 16%. Using rejection classifiers eliminated cross-reactions with acute injury, permitting separate assessment of rejection and injury. TCMR was associated with severe-recent injury and late atrophy-fibrosis and rarely had normal parenchyma. ABMR was better tolerated, seldom producing severe injury, but in later biopsies was often associated with atrophy-fibrosis, indicating long-term risk. Graft survival and left ventricular ejection fraction were reduced not only in hearts with TCMR but also in hearts with severe-recent injury and atrophy-fibrosis, even without rejection.

Exploring personalized treatment for cardiac graft rejection based on a four-archetype analysis model and bioinformatics analysis

Heart transplantation is the gold standard for treating patients with advanced heart failure. Although improvements in immunosuppressive therapies have significantly reduced the frequency of cardiac graft rejection, the incidences of T cell-mediated rejection (TCMR) and antibody-mediated rejection remain almost unchanged. A four-archetype analysis (4AA) model, developed by Philip F. Halloran, illustrated this problem well. It provided a new dimension to improve the accuracy of diagnoses and an independent system for recalibrating the histology guidelines. However, this model was based on the invasive method of endocardial biopsy, which undoubtedly increased the postoperative risk of heart transplant patients. Currently, little is known regarding the associated genes and specific functions of the different phenotypes. We performed bioinformatics analysis (using machine-learning methods and the WGCNA algorithm) to screen for hub-specific genes related to different phenotypes, based Gene Expression Omnibus accession number GSE124897. More immune cell infiltration was observed with the ABMR, TCMR, and injury phenotypes than with the stable phenotype. Hub-specific genes for each of the four archetypes were verified successfully using an external test set (accession number GSE2596). Logistic-regression models based on TCMR-specific hub genes and common hub genes were constructed with accurate diagnostic utility (area under the curve > 0.95). RELA, NFKB1, and SOX14 were identified as transcription factors important for TCMR/injury phenotypes and common genes, respectively. Additionally, 11 Food and Drug Administration-approved drugs were chosen from the DrugBank Database for each four-archetype model. Tyrosine kinase inhibitors may be a promising new option for transplant rejection treatment. KRAS signaling in cardiac transplant rejection is worth further investigation. Our results showed that heart transplant rejection subtypes can be accurately diagnosed by detecting expression of the corresponding specific genes, thereby enabling precise treatment or medication.

Molecular states associated with dysfunction and graft loss in heart transplants

BACKGROUND

We explored the changes in gene expression correlating with dysfunction and graft failure in endomyocardial biopsies.

METHODS

Genome-wide microarrays (19,462 genes) were used to define mRNA changes correlating with dysfunction (left ventricular ejection fraction [LVEF] ≤ 55) and risk of graft loss within 3 years postbiopsy. LVEF data was available for 1,013 biopsies and survival data for 779 patients (74 losses). Molecular classifiers were built for predicting dysfunction (LVEF ≤ 55) and postbiopsy 3-year survival.

RESULTS

Dysfunction is correlated with dedifferentiation-decreased expression of normal heart transcripts, for example, solute carriers, along with increased expression of inflammation genes. Many genes with reduced expression in dysfunction were matrix genes such as fibulin 1 and decorin. Gene ontology (GO) categories suggested matrix remodeling and inflammation, not rejection. Genes associated with the risk of failure postbiopsy overlapped dysfunction genes but also included genes affecting microcirculation, for example, arginase 2, which reduces NO production, and endothelin 1. GO terms also reflected increased glycolysis and response to hypoxia, but decreased VEGF and angiogenesis pathways. T cell-mediated rejection was associated with reduced survival and antibody-mediated rejection with relatively good survival, but the main determinants of survival were features of parenchymal injury. Both dysfunction and graft loss were correlated with increased biopsy expression of BNP (gene NPPB). Survival probability classifiers divided hearts into risk quintiles, with actuarial 3-year postbiopsy survival >95% for the highest versus 50% for the lowest.

CONCLUSIONS

Dysfunction in transplanted hearts reflects dedifferentiation, decreased matrix genes, injury, and inflammation. The risk of short-term loss includes these changes but is also associated with microcirculation abnormalities, glycolysis, and response to hypoxia.

Caveats in Interpretation of Molecular Diagnostics in Heart Allografts

Histologic separation of injury, T cell-mediated rejection, or antibody-mediated rejection in allograft heart biopsies is difficult. A critical review of publications was performed to evaluate the caveats of using molecular diagnostics (MDX) to distinguish between these entities. Typically, only 1 to 2 fragments of unknown histologic appearance are evaluated. Archetype and molecular classifier analyses use gene lists derived from histologic labels and associated reproducibility issues influence the accuracy of the derived MDX classes. Archetypes A1, A2, and A3 archetypes created by bioinformatics were renamed no rejection, T cell-mediated rejection, and antibody-mediated rejection despite as little as 40% concordance with histologic diagnoses and overlapping archetype scores. Additional archetypes S4 and minor injury were created using arbitrary cutoffs based on visual examination of principal component analysis plots. Therapeutic implications of the numerous discrepancies with histology remain unexplored. Many MDX-derived observations are ambiguous and open to alternate logical explanations. Better molecular methods and more rigorous validation studies are needed to advance the field. Ideally, these methods should analyze all available biopsy fragments to minimize sampling issues. It is also desirable to incorporate spatial transcriptomics into the workflow, so that gene expression data can be directly compared with the underlying histology lesions.

The utilization of molecular microscope in management of heart transplant recipients in the era of noninvasive monitoring

INTRODUCTION

Monitoring for graft rejection is a fundamental tenet of post-transplant follow-up. In heart transplantation (HT) in particular, rejection has been traditionally assessed with endomyocardial biopsy (EMB). EMB has potential complications and noted limitations, including interobserver variability in interpretation. Additional tests, such as basic cardiac biomarkers, cardiac imaging, gene expression profiling (GEP) scores, donor-derived cell-free DNA (dd-cfDNA) and the novel molecular microscope diagnostic system (MMDx) have become critical tools in rejection surveillance beyond standard EMB.

METHODS

This paper describes an illustrative case followed by a review of MMDx within the context of other noninvasive screening modalities for rejection.

CONCLUSIONS

We suggest MMDx be used to assist with early detection of rejection in cases of discordance between EMB and other noninvasive studies.

Rejection! Or is it? Correlation among molecular microscope diagnostic system, histopathology and clinical judgement following heart transplantation

PURPOSE

Little is known about clinical decision making among discordant findings concerning for rejection with endomyocardial biopsy (EMBx) and Molecular Microscope Diagnostic System (MMDx) in patients following heart transplantation.

METHODS

Two hundred and twenty-eight corresponding EMBx and MMDx specimens from 135 adult heart transplant patients were retrospectively reviewed. Rejection was classified as t-cell mediated rejection ≥2R and/or antibody mediated rejection ≥1. Clinical decision making among concordant and discordant cases of EMBx and MMDx results were reviewed.

RESULTS

Patient characteristics were comparable between concordant and discordant patient groups (median age 60 yrs., 76% male, and 71% White). A total of 167/228 specimens (73%) were concordant for no rejection with 98% agreement in clinical decision making and 25/228 (11%) concordant for rejection with 64% agreement in clinical decision making. Among the 36/228 (16%) discordant samples, clinical decision-making agreed on treatment for rejection in five of the MMDx samples and three of the EMBx samples.

CONCLUSIONS

MMDx can be an additional tool to diagnose rejection not detected by the traditional EMBx and influence clinical decision making in guiding appropriate treatment. Ongoing investigation into the clinical utility of MMDx is warranted to determine the significance of discordant findings among diagnostic modalities when assessing for rejection.

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgical treatment of patients with severe facial disfigurements. While conventional reconstructive strategies were previously considered the goldstandard for patients with devastating facial trauma, FVCA has demonstrated promising short- and long-term outcomes. Yet, there remain several obstacles that complicate the integration of FVCA procedures into the standard workflow for facial trauma patients. Artificial intelligence (AI) has been shown to provide targeted and resource-effective solutions for persisting clinical challenges in various specialties. However, there is a paucity of studies elucidating the combination of FVCA and AI to overcome such hurdles. Here, we delineate the application possibilities of AI in the field of FVCA and discuss the use of AI technology for FVCA outcome simulation, diagnosis and prediction of rejection episodes, and malignancy screening. This line of research may serve as a fundament for future studies linking these two revolutionary biotechnologies.

Immune Regulation of the Liver Through the PCSK9/CD36 Pathway During Heart Transplant Rejection

BACKGROUND

PCSK9 (proprotein convertase subtilisin/kexin 9), which is mainly secreted by the liver, is not only a therapeutic target for hyperlipidemia and cardiovascular disease, but also has been implicated in the immune regulation of infections and tumors. However, the role of PCSK9 and the liver in heart transplant rejection (HTR) and the underlying mechanisms remain unclear.

METHODS

We assessed serum PCSK9 expression in both murine and human recipients during HTR and investigated the effect of PCSK9 ablation on HTR by using global knockout mice and a neutralizing antibody. Moreover, we performed multiorgan histological and transcriptome analyses, and multiomics and single-cell RNA-sequencing studies of the liver during HTR, as well. We further used hepatocyte-specific Pcsk9 knockout mice to investigate whether the liver regulated HTR through PCSK9. Last, we explored the regulatory effect of the PCSK9/CD36 pathway on the phenotype and function of macrophages in vitro and in vivo.

RESULTS

Here, we report that murine and human recipients have high serum PCSK9 levels during HTR. PCSK9 ablation prolonged cardiac allograft survival and attenuated the infiltration of inflammatory cells in the graft and the expansion of alloreactive T cells in the spleen. Next, we demonstrated that PCSK9 was mainly produced and significantly upregulated in the recipient liver, which also showed a series of signaling changes, including changes in the TNF-α (tumor necrosis factor α) and IFN-γ (interferon γ) signaling pathways and the bile acid and fatty acid metabolism pathways. We found mechanistically that TNF-α and IFN-γ synergistically promoted PCSK9 expression in hepatocytes through the transcription factor SREBP2 (sterol regulatory element binding protein 2). Moreover, in vitro and in vivo studies indicated that PCSK9 inhibited CD36 expression and fatty acid uptake by macrophages and strengthened the proinflammatory phenotype, which facilitated their ability to promote proliferation and IFN-γ production by donor-reactive T cells. Last, we found that the protective effect of PCSK9 ablation against HTR is dependent on the CD36 pathway in the recipient.

CONCLUSIONS

This study reveals a novel mechanism for immune regulation by the liver through the PCSK9/CD36 pathway during HTR, which influences the phenotype and function of macrophages and suggests that the modulation of this pathway may be a potential therapeutic target to prevent HTR.

The evolving use of biomarkers in heart transplantation: Consensus of an expert panel

In heart transplantation, the use of biomarkers to detect the risk of rejection has been evolving. In this setting, it is becoming less clear as to what is the most reliable test or combination of tests to detect rejection and assess the state of the alloimmune response. Therefore, a virtual expert panel was organized in heart and kidney transplantation to evaluate emerging diagnostics and how they may be best utilized to monitor and manage transplant patients. This manuscript covers the heart content of the conference and is a work product of the American Society of Transplantation's Thoracic and Critical Care Community of Practice. This paper reviews currently available and emerging diagnostic assays and defines the unmet needs for biomarkers in heart transplantation. Highlights of the in-depth discussions among conference participants that led to development of consensus statements are included. This conference should serve as a platform to further build consensus within the heart transplant community regarding the optimal framework to implement biomarkers into management protocols and to improve biomarker development, validation and clinical utility. Ultimately, these biomarkers and novel diagnostics should improve outcomes and optimize quality of life for our transplant patients.

The Molecular Microscope Diagnostic System: Assessment of Rejection and Injury in Heart Transplant Biopsies

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.

Revisiting transplant immunology through the lens of single-cell technologies

Solid organ transplantation (SOT) is the standard of care for end-stage organ disease. The most frequent complication of SOT involves allograft rejection, which may occur via T cell- and/or antibody-mediated mechanisms. Diagnosis of rejection in the clinical setting requires an invasive biopsy as there are currently no reliable biomarkers to detect rejection episodes. Likewise, it is virtually impossible to identify patients who exhibit operational tolerance and may be candidates for reduced or complete withdrawal of immunosuppression. Emerging single-cell technologies, including cytometry by time-of-flight (CyTOF), imaging mass cytometry, and single-cell RNA sequencing, represent a new opportunity for deep characterization of pathogenic immune populations involved in both allograft rejection and tolerance in clinical samples. These techniques enable examination of both individual cellular phenotypes and cell-to-cell interactions, ultimately providing new insights into the complex pathophysiology of allograft rejection. However, working with these large, highly dimensional datasets requires expertise in advanced data processing and analysis using computational biology techniques. Machine learning algorithms represent an optimal strategy to analyze and create predictive models using these complex datasets and will likely be essential for future clinical application of patient level results based on single-cell data. Herein, we review the existing literature on single-cell techniques in the context of SOT.

The MMDx® diagnostic system: A critical re-appraisal of its knowledge gaps and a call for rigorous validation studies

Transcriptomics generates pathogenetic insights not obtainable by histology, but translation of these insights into diagnostic tests is not a trivial task. This opinion-piece critically appraises declarative MMDx statements, such as the infallibility of machine learning algorithms, measurements of gene expression with >99% precision, and "unambiguous reclassifications" of contentious biopsies such as those with borderline change, polyomavirus nephropathy, chronic active T-cell or mixed rejection, isolated intimal arteritis, and renal medullary pathology. It is shown that molecular diagnoses that do not agree with histology cannot be attributed primarily to pathology reading errors. Neither can all molecular calls derived from arbitrary binary thresholds be automatically accepted as the ground truth. Important other sources of discrepancies between clinico-pathologic and molecular calls include: (a) organ being studied, (b) disease definition, (c) clinical histologic, and gene expression heterogeneity within the same diagnostic label, (d) size and composition of comparator groups, (e) molecular noise, (f) variability in output of different machine learning algorithms, and (g) the nonavailability of a molecular classifier for chronic active TCMR. Carefully designed clinical trials are needed to determine which of the proposed indications of MMDx provide incremental value over existing standard of care protocols.

Single-Cell RNA sequencing reveals immune cell dynamics and local intercellular communication in acute murine cardiac allograft rejection

Rationale: Transplant rejection is a major impediment to long-term allograft survival, in which the actions of immune cells are of fundamental importance. However, the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection are not completely clear.

Methods: Here we performed single-cell RNA sequencing on CD45⁺ immune cells isolated from cardiac grafts and spleens in a model of murine heterotopic heart transplantation. Moreover, we applied unsupervised clustering, functional enrichment analysis, cell trajectory construction and intercellular communication analysis to explore the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection at single-cell level. The effect of CXCR3 antagonist and neutralizing antibody against its ligand on allograft rejection and T cell function was evaluated in murine heart transplantation model.

Results: We presented the immune cell landscape of acute murine cardiac allograft rejection at single-cell resolution, and uncovered the functional characteristics and differentiation trajectory of several alloreactive cell subpopulations, including Mki67^hi CTLs, Ccl5^hi CTLs, activated Tregs and alloreactive B cells. We demonstrated local intercellular communication and revealed the upregulation of CXCR3 and its ligands in cardiac allografts. Finally, CXCR3 blockade significantly suppressed acute cardiac allograft rejection and inhibited the alloreactive T cell function.

Conclusions: These results provide a new insight into the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection, and suggest CXCR3 pathway may serve as a potential therapeutic target for transplant rejection.

A Review of Biomarkers of Cardiac Allograft Rejection: Toward an Integrated Diagnosis of Rejection

Despite major advances in immunosuppression, allograft rejection remains an important complication after heart transplantation, and it is associated with increased morbidity and mortality. The gold standard invasive strategy to monitor and diagnose cardiac allograft rejection, based on the pathologic evaluation of endomyocardial biopsies, suffers from many limitations including the low prevalence of rejection, sample bias, high inter-observer variability, and international working formulations based on arbitrary cut-offs that simplify the landscape of rejection. The development of innovative diagnostic and prognostic strategies—integrating conventional histology, molecular profiling of allograft biopsy, and the discovery of new tissue or circulating biomarkers—is one of the major challenges of translational medicine in solid organ transplantation, and particularly in heart transplantation. Major advances in the field of biomarkers of rejection have paved the way for a paradigm shift in the monitoring and diagnosis of cardiac allograft rejection. We review the recent developments in the field, including non-invasive biomarkers to minimize the number of protocol endomyocardial biopsies and tissue biomarkers as companion tools of pathology to refine the diagnosis of cardiac rejection. Finally, we discuss the potential role of these biomarkers to provide an integrated bio-histomolecular diagnosis of cardiac allograft rejection.

Assessing the Relationship Between Molecular Rejection and Parenchymal Injury in Heart Transplant Biopsies

BACKGROUND

The INTERHEART study (ClinicalTrials.gov #NCT02670408) used genome-wide microarrays to detect rejection in endomyocardial biopsies; however, many heart transplants with no rejection have late dysfunction and impaired survival. We used the microarray measurements to develop a molecular classification of parenchymal injury.

METHODS

In 1320 endomyocardial biopsies from 645 patients previously studied for rejection-associated transcripts, we measured the expression of 10 injury-induced transcript sets: 5 induced by recent injury; 2 reflecting macrophage infiltration; 2 normal heart transcript sets; and immunoglobulin transcripts, which correlate with time. We used archetypal clustering to assign injury groups.

RESULTS

Injury transcript sets correlated with impaired function. Archetypal clustering based on the expression of injury transcript sets assigned each biopsy to 1 of 5 injury groups: 87 Severe-injury, 221 Late-injury, and 3 with lesser degrees of injury, 376 No-injury, 526 Mild-injury, and 110 Moderate-injury. Severe-injury had extensive loss of normal transcripts (dedifferentiation) and increase in macrophage and injury-induced transcripts. Late-injury was characterized by high immunoglobulin transcript expression. In Severe- and Late-injury, function was depressed, and short-term graft failure was increased, even in hearts with no rejection. T cell-mediated rejection almost always had parenchymal injury, and 85% had Severe- or Late-injury. In contrast, early antibody-mediated rejection (ABMR) had little injury, but late ABMR often had the Late-injury state.

CONCLUSION

Characterizing heart transplants for their injury state provides new understanding of dysfunction and outcomes and demonstrates the differential impact of T cell-mediated rejection versus ABMR on the parenchyma. Slow deterioration from ABMR emerges as a major contributor to late dysfunction.

The promise of machine learning applications in solid organ transplantation

Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly selected patients. Alongside the tremendous progress in the last several decades, new challenges have emerged. The growing disparity between organ demand and supply requires optimal patient/donor selection and matching. Improvements in long-term graft and patient survival require data-driven diagnosis and management of post-transplant complications. The growing abundance of clinical, genetic, radiologic, and metabolic data in transplantation has led to increasing interest in applying machine-learning (ML) tools that can uncover hidden patterns in large datasets. ML algorithms have been applied in predictive modeling of waitlist mortality, donor–recipient matching, survival prediction, post-transplant complications diagnosis, and prediction, aiming to optimize immunosuppression and management. In this review, we provide insight into the various applications of ML in transplant medicine, why these were used to evaluate a specific clinical question, and the potential of ML to transform the care of transplant recipients. 36 articles were selected after a comprehensive search of the following databases: Ovid MEDLINE; Ovid MEDLINE Epub Ahead of Print and In-Process & Other Non-Indexed Citations; Ovid Embase; Cochrane Database of Systematic Reviews (Ovid); and Cochrane Central Register of Controlled Trials (Ovid). In summary, these studies showed that ML techniques hold great potential to improve the outcome of transplant recipients. Future work is required to improve the interpretability of these algorithms, ensure generalizability through larger-scale external validation, and establishment of infrastructure to permit clinical integration.

Cardiovascular Magnetic Resonance for Rejection Surveillance After Cardiac Transplantation

BACKGROUND

Endomyocardial biopsy (EMB) is the gold standard method for surveillance of acute cardiac allograft rejection (ACAR) despite its invasive nature. Cardiovascular magnetic resonance (CMR)-based myocardial tissue characterization allows detection of myocarditis. The feasibility of CMR-based surveillance for ACAR-induced myocarditis in the first year after heart transplantation is currently undescribed.

METHODS

CMR-based multiparametric mapping was initially assessed in a prospective cross-sectional fashion to establish agreement between CMR- and EMB-based ACAR and to determine CMR cutoff values between rejection grades. A prospective randomized noninferiority pilot study was then undertaken in adult orthotopic heart transplant recipients who were randomized at 4 weeks after orthotopic heart transplantation to either CMR- or EMB-based rejection surveillance. Clinical end points were assessed at 52 weeks.

RESULTS

Four hundred one CMR studies and 354 EMB procedures were performed in 106 participants. Forty heart transplant recipients were randomized. CMR-based multiparametric assessment was highly reproducible and reliable at detecting ACAR (area under the curve, 0.92; sensitivity, 93%; specificity, 92%; negative predictive value, 99%) with greater specificity and negative predictive value than either T1 or T2 parametric CMR mapping alone. High-grade rejection occurred in similar numbers of patients in each randomized group (CMR, n=7; EMB, n=8; P=0.74). Despite similarities in immunosuppression requirements, kidney function, and mortality between groups, the rates of hospitalization (9 of 20 [45%] versus 18 of 20 [90%]; odds ratio, 0.091; P=0.006) and infection (7 of 20 [35%] versus 14 of 20 [70%]; odds ratio, 0.192; P=0,019) were lower in the CMR group. On 15 occasions (6%), patients who were randomized to the CMR arm underwent EMB for clarification or logistic reasons, representing a 94% reduction in the requirement for EMB-based surveillance.

CONCLUSIONS

A noninvasive CMR-based surveillance strategy for ACAR in the first year after orthotopic heart transplantation is feasible compared with EMB-based surveillance.

REGISTRATION

HREC/13/SVH/66 and HREC/17/SVH/80.

AUSTRALIAN NEW ZEALAND CLINICAL TRIALS REGISTRY

ACTRN12618000672257.

Transcripts associated with chronic lung allograft dysfunction in transbronchial biopsies of lung transplants

Transplanted lungs suffer worse outcomes than other organ transplants with many developing chronic lung allograft dysfunction (CLAD), diagnosed by physiologic changes. Histology of transbronchial biopsies (TBB) yields little insight, and the molecular basis of CLAD is not defined. We hypothesized that gene expression in TBBs would reveal the nature of CLAD and distinguish CLAD from changes due simply to time posttransplant. Whole-genome mRNA profiling was performed with microarrays in 498 prospectively collected TBBs from the INTERLUNG study, 90 diagnosed as CLAD. Time was associated with increased expression of inflammation genes, for example, CD1E and immunoglobulins. After correcting for time, CLAD manifested not as inflammation but as parenchymal response-to-wounding, with increased expression of genes such as HIF1A, SERPINE2, and IGF1 that are increased in many injury and disease states and cancers, associated with development, angiogenesis, and epithelial response-to-wounding in pathway analysis. Fibrillar collagen genes were increased in CLAD, indicating matrix changes, and normal transcripts were decreased-dedifferentiation. Gene-based classifiers predicted CLAD with AUC 0.70 (no time-correction) and 0.87 (time-corrected). CLAD related gene sets and classifiers were strongly prognostic for graft failure and correlated with CLAD stage. Thus, in TBBs, molecular changes indicate that CLAD primarily reflects severe parenchymal injury-induced changes and dedifferentiation.

The molecular phenotypes of injury, steatohepatitis, and fibrosis in liver transplant biopsies in the INTERLIVER study

To extend previous molecular analyses of rejection in liver transplant biopsies in the INTERLIVER study (ClinicalTrials.gov #NCT03193151), the present study aimed to define the gene expression selective for parenchymal injury, fibrosis, and steatohepatitis. We analyzed genome-wide microarray measurements from 337 liver transplant biopsies from 13 centers. We examined expression of genes previously annotated as increased in injury and fibrosis using principal component analysis (PCA). PC1 reflected parenchymal injury and related inflammation in the early posttransplant period, slowly regressing over many months. PC2 separated early injury from late fibrosis. Positive PC3 identified a distinct mildly inflamed state correlating with histologic steatohepatitis. Injury PCs correlated with liver function and histologic abnormalities. A classifier trained on histologic steatohepatitis predicted histologic steatohepatitis with cross-validated AUC = 0.83, and was associated with pathways reflecting metabolic abnormalities distinct from fibrosis. PC2 predicted histologic fibrosis (AUC = 0.80), as did a molecular fibrosis classifier (AUC = 0.74). The fibrosis classifier correlated with matrix remodeling pathways with minimal overlap with those selective for steatohepatitis, although some biopsies had both. Genome-wide assessment of liver transplant biopsies can not only detect molecular changes induced by rejection but also those correlating with parenchymal injury, steatohepatitis, and fibrosis, offering potential insights into disease mechanisms for primary diseases.

Noninvasive methods to reduce cardiac complications postheart transplant

PURPOSE OF REVIEW

Long-term success of heart transplantation is limited by allograft rejection and cardiac allograft vasculopathy (CAV). Classic management has relied on frequent invasive testing to screen for early features of rejection and CAV to allow for early treatment. In this review, we discuss new developments in the screening and prevention of allograft rejection and CAV.

RECENT FINDINGS

Newer noninvasive screening techniques show excellent sensitivity and specificity for the detection of clinically significant rejection. New biomarkers and treatment targets continue to be identified and await further studies regarding their utility in preventing allograft vasculopathy.

SUMMARY

Noninvasive imaging and biomarker testing continue to show promise as alternatives to invasive testing for allograft rejection. Continued validation of their effectiveness may lead to new surveillance protocols with reduced frequency of invasive testing. Furthermore, these noninvasive methods will allow for more personalized strategies to reduce the complications of long-term immunosuppression whereas continuing the decline in the overall rate of allograft rejection.

Cardiac Allograft Injuries: A Review of Approaches to a Common Dilemma, With Emphasis on Emerging Techniques

Clinical features of allograft injury are often unreliable, and context within the transplant journey is key. In the setting of post-transplant allograft dysfunction, the choice of initial investigation depends on clinical assessment and history. One of the major considerations is the time post transplantation in helping to decide a likely cause for allograft injury. Immediately post transplantation, it is important to consider donor factors (including donor demographics as well as immunological match), ischaemic times, surgical issues as well as early rejection. Clinical suspicion needs to remain high with variable presentations, including haemodynamic instability, arrhythmia, as well as left ventricular dysfunction. Symptoms of allograft dysfunction may include dyspnoea, exertional intolerance, dizziness / lightheadedness, palpitations, as well as right or left heart failure. In the coming weeks and months, endomyocardial biopsy and blood-based biomarkers may be helpful including high sensitivity troponin and donor-derived cell-free DNA. Molecular markers for rejection are hopeful, and may also be useful in non-ischaemic causes of allograft dysfunction. Screening remains important late post heart transplant due to variety of signs associated with rejection (early) and lack of typical anginal symptoms (later). New imaging modalities - especially cardiac magnetic resonance imaging, have been shown to be useful for assessing cause of allograft dysfunction including ischemia, infarction and rejection.

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.

The Impact of Inflammation on the Immune Responses to Transplantation: Tolerance or Rejection?

Transplantation (Tx) remains the optimal therapy for end-stage disease (ESD) of various solid organs. Although alloimmune events remain the leading cause of long-term allograft loss, many patients develop innate and adaptive immune responses leading to graft tolerance. The focus of this review is to provide an overview of selected aspects of the effects of inflammation on this delicate balance following solid organ transplantation. Initially, we discuss the inflammatory mediators detectable in an ESD patient. Then, the specific inflammatory mediators found post-Tx are elucidated. We examine the reciprocal relationship between donor-derived passenger leukocytes (PLs) and those of the recipient, with additional emphasis on extracellular vesicles, specifically exosomes, and we examine their role in determining the balance between tolerance and rejection. The concept of recipient antigen-presenting cell "cross-dressing" by donor exosomes is detailed. Immunological consequences of the changes undergone by cell surface antigens, including HLA molecules in donor and host immune cells activated by proinflammatory cytokines, are examined. Inflammation-mediated donor endothelial cell (EC) activation is discussed along with the effect of donor-recipient EC chimerism. Finally, as an example of a specific inflammatory mediator, a detailed analysis is provided on the dynamic role of Interleukin-6 (IL-6) and its receptor post-Tx, especially given the potential for therapeutic interdiction of this axis with monoclonal antibodies. We aim to provide a holistic as well as a reductionist perspective of the inflammation-impacted immune events that precede and follow Tx. The objective is to differentiate tolerogenic inflammation from that enhancing rejection, for potential therapeutic modifications. (Words 247).

Many heart transplant biopsies currently diagnosed as no rejection have mild molecular antibody-mediated rejection-related changes

BACKGROUND

The Molecular Microscope (MMDx) system classifies heart transplant endomyocardial biopsies as No-rejection (NR), Early-injury, T cell-mediated (TCMR), antibody-mediated (ABMR), mixed, and possible rejection (possible TCMR, possible ABMR). Rejection-like gene expression patterns in NR biopsies have not been described. We extended the MMDx methodology, using a larger data set, to define a new "Minor" category characterized by low-level inflammation in non-rejecting biopsies.

METHODS

Using MMDx criteria from a previous study, molecular rejection was assessed in 1,320 biopsies (645 patients) using microarray expression of rejection-associated transcripts (RATs). Of these biopsies, 819 were NR. A new archetypal analysis model in the 1,320 data set split the NRs into NR-Normal (N = 462) and NR-Minor (N = 359).

RESULTS

Compared to NR-Normal, NR-Minor were more often histologic TCMR1R, with a higher prevalence of donor-specific antibody (DSA). DSA positivity increased in a gradient: NR-Normal 24%; NR-Minor 34%; possible ABMR 42%; ABMR 66%. The top 20 transcripts distinguishing NR-Minor from NR-Normal were all ABMR-related and/or IFNG-inducible, and also exhibited a gradient of increasing expression from NR-Normal through ABMR. In random forest analysis, TCMR and Early-injury were associated with reduced LVEF and increased graft loss, but NR-Minor and ABMR scores were not. Surprisingly, hearts with MMDx ABMR showed comparatively little graft loss.

CONCLUSIONS

Many heart transplants currently diagnosed as NR by histologic or molecular assessment have minor increases in ABMR-related and IFNG-inducible transcripts, associated with DSA positivity and mild histologic inflammation. These results suggest that low-level ABMR-related molecular stress may be operating in many more hearts than previously estimated. (ClinicalTrials.gov #NCT02670408).

Molecular Diagnosis of Rejection in Heart Transplantation

Despite the overall success of heart transplantation as a definitive treatment for endstage heart failure, cardiac allograft rejection remains an important cause of morbidity and mortality. Endomyocardial biopsy has been the standard of care for rejection monitoring, but is associated with several diagnostic limitations and serious procedural complications. The use of molecular diagnostics has emerged over the past decade as a tool to potentially circumvent some of these limitations. We present an update on novel molecular approaches to detecting transplant rejection, focusing on 4 categories: microarray technology, gene expression profiling, cell-free DNA and microRNA.

Bradycardia in Recent Heart Transplant: Will the Microscope Illuminate the True Answer?CME

Transplant recipients are at risk of developing rejection that may cause significant morbidity and mortality following transplantation The clinical presentation of rejection may be atypical, leading to difficulties in diagnosis and management especially in cases with a nondiagnostic biopsy specimen. The emergence of artificial intelligence may aid in clinical decision making when traditional techniques are inconclusive.

The Molecular Microscope (MMDXR ) interpretation of thoracic and abdominal allograft biopsies: Putting things in perspective for the clinician

The Molecular Microscope System (MMDX^R ) has significant potential to enhance biopsy interpretation. However, discussions of MMDx do not acknowledge the basic accuracy of histology readings, and the ability of pathology as a stand-alone tool to guide patient management. MMDx overstates its ability to automatically correct for problems in biopsy readings. Assertions of accuracy approaching 99% are not supported by "real world" data. The high rate of discrepancies between MMDx® and standard biopsy readings can be attributed to the summation of many factors other than histology interpretation, including molecular noise, assay thresholding, limited sensitivity of microarray technology for low expression genes, errors in classifier development, narrow data interpretation, and lack of spatial context. It is not widely recognized that molecular signatures are not disease-specific and are affected by the stage of disease as well as the extent of tissue injury. The effect of sampling error on MMDx performance is significantly under-estimated, particularly in heart and lung biopsies. Therefore, MMDx reports should always be interpreted in the context of conventional biopsy readings. The clinical picture and conventional biopsy reading should be allowed to over-ride the molecular interpretation when there is concern that confounding factors are at play.

Idiosyncratic Drug-Induced Liver Injury (DILI) and Herb-Induced Liver Injury (HILI): Diagnostic Algorithm Based on the Quantitative Roussel Uclaf Causality Assessment Method (RUCAM)

Causality assessment in liver injury induced by drugs and herbs remains a debated issue, requiring innovation and thorough understanding based on detailed information. Artificial intelligence (AI) principles recommend the use of algorithms for solving complex processes and are included in the diagnostic algorithm of Roussel Uclaf Causality Assessment Method (RUCAM) to help assess causality in suspected cases of idiosyncratic drug-induced liver injury (DILI) and herb-induced liver injury (HILI). From 1993 until the middle of 2020, a total of 95,865 DILI and HILI cases were assessed by RUCAM, outperforming by case numbers any other causality assessment method. The success of RUCAM can be traced back to its quantitative features with specific data elements that are individually scored leading to a final causality grading. RUCAM is objective, user friendly, transparent, and liver injury specific, with an updated version that should be used in future DILI and HILI cases. Support of RUCAM was also provided by scientists from China, not affiliated to any network, in the results of a scientometric evaluation of the global knowledge base of DILI. They highlighted the original RUCAM of 1993 and their authors as a publication quoted the greatest number of times and ranked first in the category of the top 10 references related to DILI. In conclusion, for stakeholders involved in DILI and HILI, RUCAM seems to be an effective diagnostic algorithm in line with AI principles.

Tissue-specific endothelial cell heterogeneity contributes to unequal inflammatory responses

Endothelial cells (EC) coordinate vascular homeostasis and inflammation. In organ transplantation, EC are a direct alloimmune target. We posited that tissue specific heterogeneity of vascular EC may partly underlie the disparate organ-specific alloimmune risk. We examined the vascular endothelial response to inflammation across six primary endothelial beds from four major transplanted organs: the heart, lung, kidney and liver. First, we reanalyzed a public dataset of cardiac allograft rejection and found that endothelial inflammatory response genes were elevated in human cardiac allograft biopsies undergoing rejection compared with stable grafts. Next, the inducible inflammatory phenotypes of EC from heart, lung, kidney, and liver were characterized in vitro, focused on expression of adhesion molecules and chemokines, and recruitment of allogeneic peripheral blood mononuclear immune cells. Large vessel cardiac EC most highly upregulated VCAM-1, particularly compared with hepatic EC, supported greater leukocyte adhesion and had distinct chemokine profiles after stimulation with cytokines and complement. Differentially expressed gene candidates that are known regulators of cytokine signaling and inflammatory programming were verified in publicly available datasets of organ-specific endothelial transcriptomes. In summary, differential baseline expression of immune regulating genes may contribute to differential vascular inflammatory responses depending on organ.

[Pathology of heart transplantation: Where are we now?]

Pathology is still the gold standard for the diagnosis of rejection in heart transplantation. During the last decade, molecular pathology has emerged as a powerful tool for the understanding of the processes implicated in allograft rejection. Transcriptomic analysis of the allograft may also help the pathologist for diagnosis and accurate classification of rejection. This review will describe the recent advances and perspectives of molecular pathology in the field of heart transplantation.

The XVth Banff Conference on Allograft Pathology the Banff Workshop Heart Report: Improving the diagnostic yield from endomyocardial biopsies and Quilty effect revisited

The XVth Banff Conference on Allograft Pathology meeting was held on September 23-27, 2019, in Pittsburgh, Pennsylvania, USA. During this meeting, two main topics in cardiac transplant pathology were addressed: (a) Improvement of endomyocardial biopsy (EMB) accuracy for the diagnosis of rejection and other significant injury patterns, and (b) the orphaned lesion known as Quilty effect or nodular endocardial infiltrates. Molecular technologies have evolved in recent years, deciphering pathophysiology of cardiac rejection. Diagnostically, it is time to integrate the histopathology of EMBs and molecular data. The goal is to incorporate molecular pathology, performed on the same paraffin block as a companion test for histopathology, to yield more accurate and objective EMB interpretation. Application of digital image analysis from hematoxylin and eosin (H&E) stain to multiplex labeling is another means of extracting additional information from EMBs. New concepts have emerged exploring the multifaceted significance of myocardial injury, minimal rejection patterns supported by molecular profiles, and lesions of arteriolitis/vasculitis in the setting of T cell-mediated rejection (TCMR) and antibody-mediated rejection (AMR). The orphaned lesion known as Quilty effect or nodular endocardial infiltrates. A state-of-the-art session with historical aspects and current dilemmas was reviewed, and possible pathogenesis proposed, based on advances in immunology to explain conflicting data. The Quilty effect will be the subject of a multicenter project to explore whether it functions as a tertiary lymphoid organ.

Antibody-medicated rejection after heart transplantation: diagnosis and clinical implications

PURPOSE OF REVIEW

The present article will review the diagnosis of antibody-mediated rejection in heart transplant recipients and further explore the clinical implications.

RECENT FINDINGS

Improved diagnostic techniques have led to increased recognition of antibody-mediated rejection and better understanding of the long-term consequences in heart transplant recipients. Endomyocardial biopsy remains the gold standard for the diagnosis of antibody-medicated ejection; however, several advances in molecular testing have emerged, including the use of gene expression profiling, messenger RNA, and microRNA. Routine surveillance of donor-specific antibodies identifies recipients at high risk for graft compromise. Additionally, new monoclonal antibody therapies have broadened our repertoire in the treatment of rejection.

SUMMARY

Advances in molecular testing for antibody-mediated rejection may improve the associated long-term complication, while minimizing risk to the patient.

Canadian Cardiovascular Society/Canadian Cardiac Transplant Network Position Statement on Heart Transplantation: Patient Eligibility, Selection, and Post-Transplantation Care

Significant practice-changing developments have occurred in the care of heart transplantation candidates and recipients over the past decade. This Canadian Cardiovascular Society/Canadian Cardiac Transplant Network Position Statement provides evidence-based, expert panel recommendations with values and preferences, and practical tips on: (1) patient selection criteria; (2) selected patient populations; and (3) post transplantation surveillance. The recommendations were developed through systematic review of the literature and using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. The evolving areas of importance addressed include transplant recipient age, frailty assessment, pulmonary hypertension evaluation, cannabis use, combined heart and other solid organ transplantation, adult congenital heart disease, cardiac amyloidosis, high sensitization, and post-transplantation management of antibodies to human leukocyte antigen, rejection, cardiac allograft vasculopathy, and long-term noncardiac care. Attention is also given to Canadian-specific management strategies including the prioritization of highly sensitized transplant candidates (status 4S) and heart organ allocation algorithms. The focus topics in this position statement highlight the increased complexity of patients who undergo evaluation for heart transplantation as well as improved patient selection, and advances in post-transplantation management and surveillance that have led to better long-term outcomes for heart transplant recipients.

Molecular T-cell‒mediated rejection in transbronchial and mucosal lung transplant biopsies is associated with future risk of graft loss

BACKGROUND

We previously developed molecular assessment systems for lung transplant transbronchial biopsies (TBBs) with high surfactant and bronchial mucosal biopsies, identifying T-cell‒mediated rejection (TCMR) on the basis of the expression of rejection-associated transcripts, but the relationship of rejection to graft loss is unknown. This study aimed to develop molecular assessments for TBBs and mucosal biopsies and to establish the impact of molecular TCMR on graft survival.

METHODS

We used microarrays and machine learning to assign TCMR scores to an expanded cohort of 457 TBBs (367 high surfactant plus 90 low surfactant) and 314 mucosal biopsies. We tested the score agreement between TBB-TBB, mucosal-mucosal, and TBB-mucosal biopsy pairs in the same patient. We also assessed the association of molecular TCMR scores with graft loss (death or retransplantation) and compared it with the prognostic associations for histology and donor-specific antibodies.

RESULTS

The molecular TCMR scores assigned in all the TBBs performed similarly to those in high-surfactant TBBs, indicating that variation in alveolation in TBBs does not prevent the detection of TCMR. Mucosal biopsy pieces showed less piece-to-piece variation than TBBs. TCMR scores in TBBs agreed with those in mucosal biopsies. In both TBBs and mucosal biopsies, molecular TCMR was associated with graft loss, whereas histologic rejection and donor-specific antibodies were not.

CONCLUSIONS

Molecular TCMR can be detected in TBBs regardless of surfactant and in mucosal biopsies, which show less variability in the sampled tissue than TBBs. On the basis of these findings, molecular TCMR appears to be an important predictor of the risk of future graft failure.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02812290.

B cells as antigen-presenting cells in transplantation rejection and tolerance

Transplantation of fully allogeneic organs into immunocompetent recipients invariably elicits T cell and B cell responses that lead to the production of donor-specific antibodies (DSA). When immunosuppression is inadequate donor-specific T cell and B cell responses escape, leading to T cell-mediated rejection (TCMR), antibody mediated (ABMR) rejection, or mixed rejection (MR) exhibiting features of both TCMR and ABMR. Current literature suggests that ABMR is a major cause of late graft loss, and that new therapies to curtail the donor-specific humoral response are necessary. The majority of research into B cell responses elicited by allogeneic allografts in both preclinical models and clinical studies, has focused on the function of B cells as antibody-secreting cells and the pathogenic effects of DSA as mediators of ABMR. However, it has long been recognized that the DSA response to allografts is T cell-dependent, and that B cells engage in cognate interactions with T cells that provide "help" and promote B cell differentiation into antibody-secreting cells (ASCs). This review focusses the function of B cells as antigen-presenting cells (APCs) to T cells in lymphoid organs, how they may be critical APCs to T cell in the allograft, and the functional consequences of these interactions.

Multi-gene technical assessment of qPCR and NanoString n-Counter analysis platforms in cynomolgus monkey cardiac allograft recipients

Quantitative gene expression profiling of cardiac allografts characterizes the phenotype of the alloimmune response, yields information regarding differential effects that may be associated with various anti-rejection drug regimens, and generates testable hypotheses regarding the pathogenesis of the chronic rejection lesions typically observed in non-human primate heart transplant models. The goal of this study was to assess interplatform performance and variability between the relatively novel NanoString nCounter Analysis System, ΔΔCT (relative) RT-qPCR, and standard curve (absolute) RT-qPCR utilizing cynomolgus monkey cardiac allografts. Methods for RNA isolation and preamplification were also systematically evaluated and effective methods are proposed. In this study, we demonstrate strong correlation between the two RT-qPCR methods, but variable and, at times, weak correlation between RT-qPCR and NanoString. NanoString fold change results demonstrate less sensitivity to small changes in gene expression than RT-qPCR. These findings appear to be driven by technical aspects of each platform that influence the conditions under which each technique is ideal. Collectively, our data contribute to the general effort to optimally utilize gene expression profiling techniques, not only for transplanted tissues, but for many other applications where accurate rank-order of gene expression versus precise quantification of absolute gene transcript number may be relatively valuable.