Exploring the cardiac response to injury in heart transplant biopsies

Integrating mid-infrared spectroscopy, machine learning, and graphical bias correction for fatty acid prediction in water buffalo milk

BACKGROUND

Buffalo milk, constituting 15% of global production, has higher fatty acids content than Holstein milk. Fourier-transform mid-infrared (FT-MIR) spectroscopy is widely used for dairy analysis, but its application to buffalo milk, with larger fat globules, remains understudied. The ultimate goal of this study is to develop machine learning models based on FT-MIR spectroscopy for predicting fatty acids in buffalo milk and to assess the accuracy of commercial milk analyzers. This research provides a convenient, fast, and environmentally friendly method for detecting the fatty acid composition in buffalo milk.

RESULTS

We employed six machine learning algorithms to establish a detection model for 34 fatty acids in buffalo milk. The predictive models demonstrated robust capabilities for high-content fatty acids [C14:0, C15:0, C16:0, C17:0, C18:0, C18:1, saturated fatty acid (SFA), monounsaturated fatty acid (MUFA)], with errors within a 15% range. Traditional FT6000 detection methods exhibited limitations in measuring SFAs and polyunsaturated fatty acids (PUFA). Implementing a mean difference correction of 0.21 for MUFAs and applying regression equations (SFA × 1.0639 + 0.0705; PUFA × 0.5472 + 0.0047) significantly improved measurement accuracy.

CONCLUSION

This study successfully developed a predictive model for fatty acids in Mediterranean buffalo milk based on FT-MIR spectroscopy. Additionally, a correction was applied to the existing measurement device, FT6000, enabling more accurate measurements of fatty acids in buffalo milk. The findings have practical implications for the food industry, offering a faster and more reliable approach to assess and monitor fatty acid composition in buffalo milk, potentially influencing product development and quality control processes. © 2024 Society of Chemical Industry.

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.

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.

Comparing Plasma Donor-derived Cell-free DNA to Gene Expression in Endomyocardial Biopsies in the Trifecta-Heart Study

BACKGROUND

Plasma donor-derived cell-free DNA (dd-cfDNA) is used to screen for rejection in heart transplants. We launched the Trifecta-Heart study (ClinicalTrials.gov No. NCT04707872), an investigator-initiated, prospective trial, to examine the correlations between genome-wide molecular changes in endomyocardial biopsies (EMBs) and plasma dd-cfDNA. The present report analyzes the correlation of plasma dd-cfDNA with gene expression in EMBs from 4 vanguard centers and compared these correlations with those in 604 kidney transplant biopsies in the Trifecta-Kidney study (ClinicalTrials.gov No. NCT04239703).

METHODS

We analyzed 137 consecutive dd-cfDNA-EMB pairs from 70 patients. Plasma %dd-cfDNA was measured by the Prospera test (Natera Inc), and gene expression in EMBs was assessed by Molecular Microscope Diagnostic System using machine-learning algorithms to interpret rejection and injury states.

RESULTS

Top transcripts correlating with dd-cfDNA were related to genes increased in rejection such as interferon gamma-inducible genes (eg, HLA-DMA ) but also with genes induced by injury and expressed in macrophages (eg, SERPINA1 and HMOX1 ). In gene enrichment analysis, the top dd-cfDNA-correlated genes reflected inflammation and rejection pathways. Dd-cfDNA correlations with rejection genes in EMB were similar to those seen in kidney transplant biopsies, with somewhat stronger correlations for TCMR genes in hearts and ABMR genes in kidneys. However, the correlations with parenchymal injury-induced genes and macrophage genes were much stronger in hearts.

CONCLUSIONS

In this first analysis of Trifecta-Heart study, dd-cfDNA correlates significantly with molecular rejection but also with injury and macrophage infiltration, reflecting the proinflammatory properties of injured cardiomyocytes. The relationship supports the utility of dd-cfDNA in clinical management of heart transplant recipients.

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.

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.

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.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

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.

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.

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.

Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies

Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation of EMBs is affected by substantial interobserver and intraobserver variability, which often leads to inappropriate treatment with immunosuppressive drugs, unnecessary follow-up biopsies and poor transplant outcomes. Here we present a deep learning-based artificial intelligence (AI) system for automated assessment of gigapixel whole-slide images obtained from EMBs, which simultaneously addresses detection, subtyping and grading of allograft rejection. To assess model performance, we curated a large dataset from the United States, as well as independent test cohorts from Turkey and Switzerland, which includes large-scale variability across populations, sample preparations and slide scanning instrumentation. The model detects allograft rejection with an area under the receiver operating characteristic curve (AUC) of 0.962; assesses the cellular and antibody-mediated rejection type with AUCs of 0.958 and 0.874, respectively; detects Quilty B lesions, benign mimics of rejection, with an AUC of 0.939; and differentiates between low-grade and high-grade rejections with an AUC of 0.833. In a human reader study, the AI system showed non-inferior performance to conventional assessment and reduced interobserver variability and assessment time. This robust evaluation of cardiac allograft rejection paves the way for clinical trials to establish the efficacy of AI-assisted EMB assessment and its potential for improving heart transplant outcomes.

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.

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 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).

Transcriptomic heterogeneity of antibody mediated rejection after heart transplant with or without donor specific antibodies

BACKGROUND

Antibody mediated rejection (AMR) is an increasingly studied cause of graft failure after heart transplantation. AMR diagnosis previously required the detection of circulating donor specific antibodies (DSA); however, the most recent criteria only require pathological findings. This classification defined a subset of patients with AMR, yet without known antibodies. Here, we sought to evaluate differences in the transcriptome profile associated with different types of AMR.

METHODS

RNA sequencing was used on endomyocardial biopsies to analyze and compare transcriptomic profiles associated with different subtypes of AMR defined by immunopathological and histopathological findings, as well as the presence or absence of DSA. Gene expression profiles were characterized for each diagnostic group.

RESULTS

The most divergent gene expression profiles were observed between patients with or without DSA. AMR subtypes associated with DSA showed expression of signature genes involved in monocyte activation and response to interferon. There was also substantial difference between the transcriptomic profiles of AMR defined by histopathological and immunopathological findings, the latter being associated with expression of mucin genes. In contrast, there was no differential RNA expression between patients with pAMR1i without DSA and those without AMR. Likewise, no differential expression was observed between patients with pAMR1h with DSA and pAMR2.

CONCLUSIONS

Overall, our studies reveal different expression profiles in endomyocardial biopsies in relation to some key criteria used to diagnose AMR. These findings support the view that the diagnosis of AMR encompasses several phenotypes that may rely on distinct mechanisms of injury.

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.

Novel biomarkers useful in surveillance of graft rejection after heart transplantation

Heart transplantation (HTx) is considered the gold-standard therapy for the treatment of advanced heart failure (HF). The long-term survival in HTx is hindered by graft failure which represents one of the major limitations of the long-term efficacy of HTx. Endomyocardial biopsy (EMB) and the evaluation of donor-specific antibodies (DSA) are currently considered the essential diagnostic tools for surveillance of graft rejection. Recently, new molecular biomarkers (including cell-free DeoxyriboNucleic Acid, exosomes, gene profiling microarray, nanostring, reverse transcriptase multiplex ligation-dependent probe amplification, proteomics and immune profiling by quantitative multiplex immunofluorescence) provide useful information on mechanisms of graft rejection. The ambitious role of a similar change of perspective is aimed at a better and longer graft preservation.

Discovering novel injury features in kidney transplant biopsies associated with TCMR and donor aging

We previously characterized the molecular changes in acute kidney injury (AKI) and chronic kidney disease (CKD) in kidney transplant biopsies, but parenchymal changes selective for specific types of injury could be missed by such analyses. The present study searched for injury changes beyond AKI and CKD related to specific scenarios, including correlations with donor age. We defined injury using previously defined gene sets and classifiers and used principal component analysis to discover new injury dimensions. As expected, Dimension 1 distinguished normal vs. injury, and Dimension 2 separated early AKI from late CKD, correlating with time posttransplant. However, Dimension 3 was novel, distinguishing a set of genes related to epithelial polarity (e.g., PARD3) that were increased in early AKI and decreased in T cell-mediated rejection (TCMR) but not in antibody-mediated rejection. Dimension 3 was increased in kidneys from older donors and was particularly important in survival of early kidneys. Thus high Dimension 3 scores emerge as a previously unknown element in the kidney response-to-injury that affects epithelial polarity genes and is increased in AKI but depressed in TCMR, indicating that in addition to general injury elements, certain injury elements are selective for specific pathologic mechanisms. (ClinicalTrials.gov NCT01299168).

The evolution of patient-specific precision biomarkers to guide personalized heart-transplant care

Introduction

In parallel to the clinical maturation of heart transplantation over the last 50 years, rejection testing has been revolutionized within the systems biology paradigm triggered by the Human Genome Project.

Areas Covered

We have co-developed the first FDA-cleared diagnostic and prognostic leukocyte gene expression profiling biomarker test in transplantation medicine that gained international evidence-based medicine guideline acceptance to rule out moderate/severe acute cellular cardiac allograft rejection without invasive endomyocardial biopsies. This work prompted molecular re-classification of intragraft biology, culminating in the identification of a pattern of intragraft myocyte injury, in addition to acute cellular rejection and antibody-mediated rejection. This insight stimulated research into non-invasive detection of myocardial allograft injury. The addition of a donor-organ specific myocardial injury marker based on donor-derived cell-free DNA further strengthens the non-invasive monitoring concept, combining the clinical use of two complementary non-invasive blood-based measures, host immune activity-related risk of acute rejection as well as cardiac allograft injury.

Expert Opinion

This novel complementary non-invasive heart transplant monitoring strategy based on leukocyte gene expression profiling and donor-derived cell-free DNA that incorporates longitudinal variability measures provides an exciting novel algorithm of heart transplant allograft monitoring. This algorithm's clinical utility will need to be tested in an appropriately designed randomized clinical trial which is in preparation.

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.

Untangling Local Pro-Inflammatory, Reparative, and Regulatory Damage-Associated Molecular-Patterns (DAMPs) Pathways to Improve Transplant Outcomes

Detrimental inflammatory responses after solid organ transplantation are initiated when immune cells sense pathogen-associated molecular patterns (PAMPs) and certain damage-associated molecular patterns (DAMPs) released or exposed during transplant-associated processes, such as ischemia/reperfusion injury (IRI), surgical trauma, and recipient conditioning. These inflammatory responses initiate and propagate anti-alloantigen (AlloAg) responses and targeting DAMPs and PAMPs, or the signaling cascades they activate, reduce alloimmunity, and contribute to improved outcomes after allogeneic solid organ transplantation in experimental studies. However, DAMPs have also been implicated in initiating essential anti-inflammatory and reparative functions of specific immune cells, particularly Treg and macrophages. Interestingly, DAMP signaling is also involved in local and systemic homeostasis. Herein, we describe the emerging literature defining how poor outcomes after transplantation may result, not from just an over-abundance of DAMP-driven inflammation, but instead an inadequate presence of a subset of DAMPs or related molecules needed to repair tissue successfully or re-establish tissue homeostasis. Adverse outcomes may also arise when these homeostatic or reparative signals become dysregulated or hijacked by alloreactive immune cells in transplant niches. A complete understanding of the critical pathways controlling tissue repair and homeostasis, and how alloimmune responses or transplant-related processes disrupt these will lead to new immunotherapeutics that can prevent or reverse the tissue pathology leading to lost grafts due to chronic rejection.

[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.

Investigation of hub genes and immune status in heart transplant rejection using endomyocardial biopsies

T cell‒mediated rejection (TCMR) and antibody‐mediated rejection (ABMR) are severe post‐transplantation complications for heart transplantation (HTx), whose molecular and immunological pathogenesis remains unclear. In the present study, the mRNA microarray data set GSE124897 containing 645 stable, 52 TCMR and 144 ABMR endomyocardial biopsies was obtained to screen for differentially expressed genes (DEGs) between rejected and stable HTx samples and to investigate immune cell infiltration. Functional enrichment analyses indicated roles of the DEGs primarily in immune‐related mechanisms. Protein‐protein interaction networks were then constructed, and ICAM1, CD44, HLA‐A and HLA‐B were identified as hub genes using the maximal clique centrality method. Immune cell infiltration analysis revealed differences in adaptive and innate immune cell populations between TCMR, ABMR and stable HTx samples. Additionally, hub gene expression levels significantly correlated with the degree and composition of immune cell infiltration in HTx rejection samples. Furthermore, drug‐gene interactions were constructed, and 12 FDA‐approved drugs were predicted to target hub genes. Finally, an external GSE2596 data set was used to validate the expression of the hub genes, and ROC curves indicated all four hub genes had promising diagnostic value for HTx rejection. This study provides a comprehensive perspective of molecular and immunological regulatory mechanisms underlying HTx rejection.

The molecular diagnosis of rejection in liver transplant biopsies: First results of the INTERLIVER study

Molecular diagnosis of rejection is emerging in kidney, heart, and lung transplant biopsies and could offer insights for liver transplant biopsies. We measured gene expression by microarrays in 235 liver transplant biopsies from 10 centers. Unsupervised archetypal analysis based on expression of previously annotated rejection-related transcripts identified 4 groups: normal "R1_normal " (N = 129), T cell-mediated rejection (TCMR) "R2_TCMR " (N = 37), early injury "R3_injury " (N = 61), and fibrosis "R4_late " (N = 8). Groups differed in median time posttransplant, for example, R3_injury 99 days vs R4_late 3117 days. R2_TCMR biopsies expressed typical TCMR-related transcripts, for example, intense IFNG-induced effects. R3_injury displayed increased expression of parenchymal injury transcripts (eg, hypoxia-inducible factor EGLN1). R4_late biopsies showed immunoglobulin transcripts and injury-related transcripts. R2_TCMR correlated with histologic rejection although with many discrepancies, and R4_late with fibrosis. R2_TCMR , R3_injury , and R4_late correlated with liver function abnormalities. Supervised classifiers trained on histologic rejection showed less agreement with histology than unsupervised R2_TCMR scores. No confirmed cases of clinical antibody-mediated rejection (ABMR) were present in the population, and strategies that previously revealed ABMR in kidney and heart transplants failed to reveal a liver ABMR phenotype. In conclusion, molecular analysis of liver transplant biopsies detects rejection, has the potential to resolve ambiguities, and could assist with immunosuppressive management.

Single-cell Transcriptomics and Solid Organ Transplantation

Single-cell RNA sequencing (scRNA-seq) allows the measurement of transcriptomes from individual cells providing new insights into complex biological systems. scRNA-seq has enabled the identification of rare cell types, new cell states, and intercellular communication networks that may be masked by traditional bulk transcriptional profiling. Researchers are increasingly using scRNA-seq to comprehensively characterize complex organs in health and disease. The diversity of immune cell types, some present at low frequency, in a transplanted organ undergoing rejection makes scRNA-seq ideally suited to characterize transplant pathologies because it can quantify subtle transcriptional differences between rare cell types. In this review, we discuss single-cell sequencing methods and their application in transplantation to date, current challenges, and future directions. We believe that the remarkably rapid pace of technological development in this field makes it likely that single-cell technologies such as scRNA-seq will have an impact on clinical transplantation within a decade.

Myocardial micro-biopsy procedure for molecular characterization with increased precision and reduced trauma

Endomyocardial biopsy is a valuable tool in cardiac diagnostics but is limited by low diagnostic yield and significant complication risks. Meanwhile, recent developments in transcriptomic and proteomic technologies promise a wealth of biological data from minimal tissue samples. To take advantage of the minimal tissue amount needed for molecular analyses, we have developed a sub-millimeter endovascular biopsy device, considerably smaller than current clinical equipment, and devised a low-input RNA-sequencing protocol for analyzing small tissue samples. In in vivo evaluation in swine, 81% of biopsy attempts (n = 157) were successful. High quality RNA-sequencing data was generated from 91% of the sequenced cardiac micro-biopsy samples (n = 32). Gene expression signatures of samples taken with the novel device were comparable with a conventional device. No major complications were detected either during procedures or during 7 days' follow-up, despite acquiring a relatively large number of biopsies (median 30) in each animal. In conclusion, the novel device coupled with RNA-sequencing provides a feasible method to obtain molecular data from the myocardium. The method is less traumatic and has a higher flexibility compared to conventional methods, enabling safer and more targeted sampling from different parts of the myocardium.

Molecular phenotyping of rejection-related changes in mucosal biopsies from lung transplants

Diagnosing lung transplant rejection currently depends on histologic assessment of transbronchial biopsies (TBB) with limited reproducibility and considerable risk of complications. Mucosal biopsies are safer but not histologically interpretable. Microarray-based diagnostic systems for TBBs and other transplants suggest such systems could assess mucosal biopsies as well. We studied 243 mucosal biopsies from the third bronchial bifurcation (3BMBs) collected from seven centers and classified them using unsupervised machine learning algorithms. Using the expression of a set of rejection-associated transcripts annotated in kidneys and validated in hearts and lung transplant TBBs, the algorithms identified and scored major rejection and injury-related phenotypes in 3BMBs without need for labeled training data. No rejection or injury, rejection, late inflammation, and recent injury phenotypes were thus scored in new 3BMBs. The rejection phenotype correlated with IFNG-inducible transcripts, the hallmarks of rejection. Progressive atrophy-related changes reflected by the late inflammation phenotype in 3BMBs suggest widespread time-dependent airway deterioration, which was especially pronounced after two years posttransplant. Thus molecular assessment of 3BMBs can detect rejection in a previously unusable biopsy format with potential utility in patients with severe lung dysfunction where TBB is not possible and provide unique insights into airway deterioration. ClinicalTrials.gov NCT02812290.

Use of Ventricular Assist Devices and Heart Transplantation for Advanced Heart Failure

There are only 2 treatments for the thousands of patients who progress to the most advanced form of heart failure despite the application of guideline-based medical therapy, use of ventricular assist devices and heart transplantation. There has been a great deal of progress in both of these therapies that have led to improved outcomes including significant improvement in survival and functional capacity. Heart transplantation offers the best short- and long-term survival for patients with end-stage heart failure, and the majority of these recipients achieve relatively limitless functional capacity for their age. However, the chronic shortage of available donors limits the number of recipients in the United States to an only 2500 patients/y or only a fraction of potential candidates. The significant improvement in outcomes now possible with durable ventricular assist devices has led to a significant increase in their use, which now exceeds the volume of heart transplants in the United States, with the greatest growth in use for those not considered to be candidates for heart transplantation, previously referred to as destination therapy. This article will review the substantial progress that has taken place for both of these life-saving treatment options, as well as the future directions.

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.

Does the antibody mediated rejection grading scale have prognostic prediction? Yes, but the picture is still blurry

PURPOSE OF REVIEW

Antibody-mediated rejection (ABMR) is a condition difficult to diagnose and treat, which may significantly impair the outcome of heart transplant recipients. In clinical practice, diagnosis is based on immunopathology grading of endomyocardial biopsies (EMB). Despite its value, the current diagnostic system has several pitfalls that have been addressed in recent literature.

RECENT FINDINGS

Pathology grading of ABMR (pAMR) has a relevant prognostic factor. However, it does not capture several nuances, such as chronic vs. acute ABMR, mixed rejection or microvascular inflammation. Molecular biology-based assays are shedding new light on the mechanisms of ABMR, which could improve the precision of ABMR diagnosis.

SUMMARY

These new findings have the potential to rearrange EMB grading system and to guide more precisely decision-making, but studies validating the therapeutic management based on molecular-pathology coupling are still missing.

Molecular phenotype of kidney transplant indication biopsies with inflammation in scarred areas

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.

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

BACKGROUND

We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA) or 4-archetype (4AA) unsupervised algorithms to estimate rejection. In the present study we examined the stability of machine-learning algorithms in new biopsies, compared 3AA vs 4AA algorithms, assessed supervised binary classifiers trained on histologic or molecular diagnoses, created a report combining many scores into an ensemble of estimates, and examined possible automated sign-outs.

METHODS

We studied 889 EMBs from 454 transplant recipients at 8 centers: the initial cohort (N = 331) and a new cohort (N = 558). Published 3AA algorithms derived in Cohort 331 were tested in Cohort 558, the 3AA and 4AA models were compared, and supervised binary classifiers were created.

RESULTS

A`lgorithms derived in Cohort 331 performed similarly in new biopsies despite differences in case mix. In the combined cohort, the 4AA model, including a parenchymal injury score, retained correlations with histologic rejection and DSA similar to the 3AA model. Supervised molecular classifiers predicted molecular rejection (areas under the curve [AUCs] >0.87) better than histologic rejection (AUCs <0.78), even when trained on histology diagnoses. A report incorporating many AA and binary classifier scores interpreted by 1 expert showed highly significant agreement with histology (p < 0.001), but with many discrepancies, as expected from the known noise in histology. An automated random forest score closely predicted expert diagnoses, confirming potential for automated signouts.

CONCLUSIONS

Molecular algorithms are stable in new populations and can be assembled into an ensemble that combines many supervised and unsupervised estimates of the molecular disease states.

Molecular assessment of rejection and injury in lung transplant biopsies

BACKGROUND

Improved understanding of lung transplant disease states is essential because failure rates are high, often due to chronic lung allograft dysfunction. However, histologic assessment of lung transplant transbronchial biopsies (TBBs) is difficult and often uninterpretable even with 10 pieces.

METHODS

We prospectively studied whether microarray assessment of single TBB pieces could identify disease states and reduce the amount of tissue required for diagnosis. By following strategies successful for heart transplants, we used expression of rejection-associated transcripts (annotated in kidney transplant biopsies) in unsupervised machine learning to identify disease states.

RESULTS

All 242 single-piece TBBs produced reliable transcript measurements. Paired TBB pieces available from 12 patients showed significant similarity but also showed some sampling variance. Alveolar content, as estimated by surfactant transcript expression, was a source of sampling variance. To offset sampling variation, for analysis, we selected 152 single-piece TBBs with high surfactant transcripts. Unsupervised archetypal analysis identified 4 idealized phenotypes (archetypes) and scored biopsies for their similarity to each: normal; T-cell‒mediated rejection (TCMR; T-cell transcripts); antibody-mediated rejection (ABMR)-like (endothelial transcripts); and injury (macrophage transcripts). Molecular TCMR correlated with histologic TCMR. The relationship of molecular scores to histologic ABMR could not be assessed because of the paucity of ABMR in this population.

CONCLUSIONS

Molecular assessment of single-piece TBBs can be used to classify lung transplant biopsies and correlated with rejection histology. Two or 3 pieces for each TBB will probably be needed to offset sampling variance.