Comprehensive Analysis of Transcript Changes Associated With Allograft Rejection: Combining Universal and Selective Features

Plasma immune signatures can predict rejection-free survival in the first year after pediatric liver transplantation

BACKGROUND & AIMS

After pediatric liver transplantation (pLT), children undergo life-long immunosuppression since reliable biomarkers for the assessment of rejection probability are scarce. In the multicentre (n=7) prospective clinical cohort "ChilSFree" study, we aimed to characterize longitudinal dynamics of soluble and cellular immune mediators during the first year after pLT and identify early biomarkers associated with outcome.

METHODS

Using paired Luminex-based multiplex technique and flow cytometry, we characterized longitudinal dynamics of soluble immune mediators (SIM, n=50) and immune cells in the blood of 244 patients at 8 visits over one year: before, 7/14/21/28 days, 3/6/12 months after pLT.

RESULTS

The unsupervised clustering of patients based on SIM profiles revealed 6 unique SIM signatures associated with clinical outcome. From 3 signatures linked to improved outcome, one was associated with one-year-long rejection-free survival and stable graft function and was characterized by low levels of pro-inflammatory (CXCL8/9/10/12, CCL7, SCGF-β, sICAM-1), high levels of regenerative (SCF, TNF-β), and pro-apoptotic (TRAIL) SIM (all, p<0.001, fold change >100). Of note, this SIM signature appeared two weeks after pLT and remained stable over the entire year, pointing towards its potential as a novel early biomarker for minimizing or weaning immunosuppression. In the blood of these patients, a higher frequency of CD56bright NK cells (p<0.01), a known hallmark also associated with operationally tolerant pLT patients, was detected. The concordance of the model for prediction of rejection based on identified SIM signatures was 0.715, and 0.795, in combination with living-related transplantation as co-variate, respectively.

CONCLUSIONS

SIM blood signatures may enable the non-invasive and early assessment of rejection risks in the first year after pLT, paving the way to improved therapeutic options.

Biomarkers from subcutaneous engineered tissues predict acute rejection of organ allografts

Invasive graft biopsies assess the efficacy of immunosuppression through lagging indicators of transplant rejection. We report on a microporous scaffold implant as a minimally invasive immunological niche to assay rejection before graft injury. Adoptive transfer of T cells into Rag2-/- mice with mismatched allografts induced acute cellular allograft rejection (ACAR), with subsequent validation in wild-type animals. Following murine heart or skin transplantation, scaffold implants accumulate predominantly innate immune cells. The scaffold enables frequent biopsy, and gene expression analyses identified biomarkers of ACAR before clinical signs of graft injury. This gene signature distinguishes ACAR and immunodeficient respiratory infection before injury onset, indicating the specificity of the biomarkers to differentiate ACAR from other inflammatory insult. Overall, this implantable scaffold enables remote evaluation of the early risk of rejection, which could potentially be used to reduce the frequency of routine graft biopsy, reduce toxicities by personalizing immunosuppression, and prolong transplant life.

Exploring kidney allograft rejection: A proof-of-concept study using spatial transcriptomics

In this proof-of-concept study, spatial transcriptomics combined with public single-cell ribonucleic acid-sequencing data were used to explore the potential of this technology to study kidney allograft rejection. We aimed to map gene expression patterns within diverse pathologic states by examining biopsies classified across nonrejection, T cell-mediated acute rejection, interstitial fibrosis, and tubular atrophy. Our results revealed distinct immune cell signatures, including those of T and B lymphocytes, monocytes, mast cells, and plasma cells, and their spatial organization within the renal interstitium. We also mapped chemokine receptors and ligands to study immune cell migration and recruitment. Finally, our analysis demonstrated differential spatial enrichment of transcription signatures associated with kidney allograft rejection across various biopsy regions. Interstitium regions displayed higher enrichment scores for rejection-associated gene expression patterns than tubular areas, which had negative scores. This implies that these signatures are primarily driven by processes unfolding in the renal interstitium. Overall, this study highlights the value of spatial transcriptomics for revealing cellular heterogeneity and immune signatures in renal transplant biopsies and demonstrates its potential for studying the molecular and cellular mechanisms associated with rejection. However, certain limitations must be borne in mind regarding the development and future applications of this technology.

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.

Development and Validation of a Multiclass Model Defining Molecular Archetypes of Kidney Transplant Rejection: A Large Cohort Study of the Banff Human Organ Transplant Gene Expression Panel

Gene expression profiling from formalin-fixed paraffin-embedded (FFPE) renal allograft biopsies is a promising approach for feasibly providing a molecular diagnosis of rejection. However, large-scale studies evaluating the performance of models using NanoString platform data to define molecular archetypes of rejection are lacking. We tested a diverse retrospective cohort of over 1400 FFPE biopsy specimens, rescored according to Banff 2019 criteria and representing 10 of 11 United Network of Organ Sharing regions, using the Banff Human Organ Transplant panel from NanoString and developed a multiclass model from the gene expression data to assign relative probabilities of 4 molecular archetypes: No Rejection, Antibody-Mediated Rejection, T Cell-Mediated Rejection, and Mixed Rejection. Using Least Absolute Shrinkage and Selection Operator regularized regression with 10-fold cross-validation fitted to 1050 biopsies in the discovery cohort and technically validated on an additional 345 biopsies, our model achieved overall accuracy of 85% in the discovery cohort and 80% in the validation cohort, with ≥75% positive predictive value for each class, except for the Mixed Rejection class in the validation cohort (positive predictive value, 53%). This study represents the technical validation of the first model built from a large and diverse sample of diagnostic FFPE biopsy specimens to define and classify molecular archetypes of histologically defined diagnoses as derived from Banff Human Organ Transplant panel gene expression profiling data.

Rejection markers in kidney transplantation: do new technologies help children?

Recent insights in allorecognition and graft rejection mechanisms revealed a more complex picture than originally considered, involving multiple pathways of both adaptive and innate immune response, supplied by efficient inflammatory synergies. Current pillars of transplant monitoring are serum creatinine, proteinuria, and drug blood levels, which are considered as traditional markers, due to consolidated experience, low cost, and widespread availability. The most diffuse immunological biomarkers are donor-specific antibodies, which are included in routine post-transplant monitoring in many centers, although with some reproducibility issues and interpretation difficulties. Confirmed abnormalities in these traditional biomarkers raise the suspicion for rejection and guide the indication for graft biopsy, which is still considered the gold standard for rejection monitoring. Rapidly evolving new "omic" technologies have led to the identification of several novel biomarkers, which may change the landscape of transplant monitoring should their potential be confirmed. Among them, urinary chemokines and measurement of cell-free DNA of donor origin are perhaps the most promising. However, at the moment, these approaches remain highly expensive and cost-prohibitive in most settings, with limited clinical applicability; approachable costs upon technology investments would speed their integration. In addition, transcriptomics, metabolomics, proteomics, and the study of blood and urinary extracellular vesicles have the potential for early identification of subclinical rejection with high sensitivity and specificity, good reproducibility, and for gaining predictive value in an affordable cost setting. In the near future, information derived from these new biomarkers is expected to integrate traditional tools in routine use, allowing identification of rejection prior to clinical manifestations and timely therapeutic intervention. This review will discuss traditional, novel, and invasive and non-invasive biomarkers, underlining their strengths, limitations, and present or future applications in children.

Utility of Banff Human Organ Transplant Gene Panel in Human Kidney Transplant Biopsies

BACKGROUND

Microarray transcript analysis of human renal transplantation biopsies has successfully identified the many patterns of graft rejection. To evaluate an alternative, this report tests whether gene expression from the Banff Human Organ Transplant (B-HOT) probe set panel, derived from validated microarrays, can identify the relevant allograft diagnoses directly from archival human renal transplant formalin-fixed paraffin-embedded biopsies. To test this hypothesis, principal components (PCs) of gene expressions were used to identify allograft diagnoses, to classify diagnoses, and to determine whether the PC data were rich enough to identify diagnostic subtypes by clustering, which are all needed if the B-HOT panel can substitute for microarrays.

METHODS

RNA was isolated from routine, archival formalin-fixed paraffin-embedded tissue renal biopsy cores with both rejection and nonrejection diagnoses. The B-HOT panel expression of 770 genes was analyzed by PCs, which were then tested to determine their ability to identify diagnoses.

RESULTS

PCs of microarray gene sets identified the Banff categories of renal allograft diagnoses, modeled well the aggregate diagnoses, showing a similar correspondence with the pathologic diagnoses as microarrays. Clustering of the PCs identified diagnostic subtypes including non-chronic antibody-mediated rejection with high endothelial expression. PCs of cell types and pathways identified new mechanistic patterns including differential expression of B and plasma cells.

CONCLUSIONS

Using PCs of gene expression from the B-Hot panel confirms the utility of the B-HOT panel to identify allograft diagnoses and is similar to microarrays. The B-HOT panel will accelerate and expand transcript analysis and will be useful for longitudinal and outcome studies.

A Simple Molecular Tool for the Assessment of Kidney Transplant Biopsies

BACKGROUND

The Banff Classification for Allograft Pathology recommendations for the diagnosis of kidney transplant rejection includes molecular assessment of the transplant biopsy. However, implementation of molecular tools in clinical practice is still limited, partly due to the required expertise and financial investment. The reverse transcriptase multiplex ligation-dependent probe amplification (RT-MLPA) assay is a simple, rapid, and inexpensive assay that permits simultaneous evaluation of a restricted gene panel using paraffin-embedded tissue blocks. The aim of this study was to develop and validate a RT-MLPA assay for diagnosis and classification of rejection.

METHODS

A retrospective cohort of 220 kidney transplant biopsies from two centers, which included 52 antibody-mediated rejection, 51 T-cell-mediated rejection, and 117 no-rejection controls, was assessed. A 17-gene panel was identified on the basis of relevant pathophysiological pathways. A support vector machine classifier was developed. A subset of 109 biopsies was also assessed using the Nanostring Banff Human Organ Transplant panel to compare the two assays.

RESULTS

The support vector machine classifier train and test accuracy scores were 0.84 and 0.83, respectively. In the test cohort, the F1 score for antibody-mediated rejection, T-cell-mediated rejection, and control were 0.88, 0.86, and 0.69, respectively. Using receiver-operating characteristic curves, the area under the curve for class predictions was 0.96, 0.89, and 0.91, respectively, with a weighted average at 0.94. Classifiers' performances were highest for antibody-mediated rejection diagnosis with 94% correct predictions, compared with 88% correct predictions for control biopsies and 60% for T-cell-mediated rejection biopsies. Gene expression levels assessed by RT-MLPA and Nanostring were correlated: r = 0.68, P < 0.001. Equivalent gene expression profiles were obtained with both assays in 81% of the samples.

CONCLUSIONS

The 17-gene panel RT-MLPA assay, developed here for formalin-fixed paraffin-embedded kidney transplant biopsies, classified kidney transplant rejection with an overall accurate prediction ratio of 0.83.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_04_10_CJN10100822.mp3.

The molecular features of chronic lung allograft dysfunction in lung transplant airway mucosa

BACKGROUND

Many lung transplants fail due to chronic lung allograft dysfunction (CLAD). We recently showed that transbronchial biopsies (TBBs) from CLAD patients manifest severe parenchymal injury and dedifferentiation, distinct from time-dependent changes. The present study explored time-selective and CLAD-selective transcripts in mucosal biopsies from the third bronchial bifurcation (3BMBs), compared to those in TBBs.

METHODS

We used genome-wide microarray measurements in 324 3BMBs to identify CLAD-selective changes as well as time-dependent changes and develop a CLAD classifier. CLAD-selective transcripts were identified with linear models for microarray data (limma) and were used to build an ensemble of 12 classifiers to predict CLAD. Hazard models and random forests were then used to predict the risk of graft loss using the CLAD classifier, transcript sets associated with rejection, injury, and time.

RESULTS

T cell-mediated rejection and donor-specific antibody were increased in CLAD 3BMBs but most had no rejection. Like TBBs, 3BMBs showed a time-dependent increase in transcripts expressed in inflammatory cells that was not associated with CLAD or survival. Also like TBBs, the CLAD-selective transcripts in 3BMBs reflected severe parenchymal injury and dedifferentiation, not inflammation or rejection. While 3BMBs and TBBs did not overlap in their top 20 CLAD-selective transcripts, many CLAD-selective transcripts were significantly increased in both for example LOXL1, an enzyme controlling matrix remodeling. In Cox models for one-year survival, the 3BMB CLAD-selective transcripts and CLAD classifier predicted graft loss and correlated with CLAD stage. Many 3BMB CLAD-selective transcripts were also increased by injury in kidney transplants and correlated with decreased kidney survival, including LOXL1.

CONCLUSIONS

Mucosal and transbronchial biopsies from CLAD patients reveal a diffuse molecular injury and dedifferentiation state that impacts prognosis and correlates with the physiologic disturbances. CLAD state in lung transplants shares features with failing kidney transplants, indicating elements shared by the injury responses of distressed organs.

Banff Human Organ Transplant Transcripts Correlate with Renal Allograft Pathology and Outcome: Importance of Capillaritis and Subpathologic Rejection

BACKGROUND

To seek insights into the pathogenesis of chronic active antibody-mediated rejection (CAMR), we performed mRNA analysis and correlated transcripts with pathologic component scores and graft outcomes.

METHODS

We utilized the NanoString nCounter platform and the Banff Human Organ Transplant gene panel to quantify transcripts on 326 archived renal allograft biopsy samples. This system allowed correlation of transcripts with Banff pathology scores from the same tissue block and correlation with long-term outcomes.

RESULTS

The only pathology score that correlated with AMR pathways in CAMR was peritubular capillaritis (ptc). C4d, cg, g, v, i, t, or ci scores did not correlate. DSA-negative CAMR had lower AMR pathway scores than DSA-positive CAMR. Transcript analysis in non-CAMR biopsies yielded evidence of increased risk of later CAMR. Among 108 patients without histologic CAMR, 23 developed overt biopsy-documented CAMR within 5 years and as a group had higher AMR pathway scores (P=3.4 × 10-5). Random forest analysis correlated 3-year graft loss with elevated damage, innate immunity, and macrophage pathway scores in CAMR and TCMR. Graft failure in CAMR was associated with TCMR transcripts but not with AMR transcripts, and graft failure in TCMR was associated with AMR transcripts but not with TCMR transcripts.

CONCLUSIONS

Peritubular capillary inflammation and DSA are the primary drivers of AMR transcript elevation. Transcripts revealed subpathological evidence of AMR, which often preceded histologic CAMR and subpathological evidence of TCMR that predicted graft loss in CAMR.

Impact of Glomerulitis on Long-term Outcomes After Kidney Transplantation

The Banff classification scheme provides a framework for interpreting transplant kidney biopsies and has undergone various updates in the past 2 decades especially related to antibody-mediated rejection. The clinical significance of early glomerulitis seen within 4 mo on protocol biopsies has received limited attention. We hypothesized that early glomerulitis seen on protocol biopsies will lead to significant adverse outcomes as assessed by histopathology and allograft outcome.

Circulating Donor-Specific Anti-HLA Antibodies Associate With Immune Activation Independent of Kidney Transplant Histopathological Findings

Despite the critical role of cytokines in allograft rejection, the relation of peripheral blood cytokine profiles to clinical kidney transplant rejection has not been fully elucidated. We assessed 28 cytokines through multiplex assay in 293 blood samples from kidney transplant recipients at time of graft dysfunction. Unsupervised hierarchical clustering identified a subset of patients with increased pro-inflammatory cytokine levels. This patient subset was hallmarked by a high prevalence (75%) of donor-specific anti-human leukocyte antigen antibodies (HLA-DSA) and histological rejection (70%) and had worse graft survival compared to the group with low cytokine levels (HLA-DSA in 1.7% and rejection in 33.7%). Thirty percent of patients with high pro-inflammatory cytokine levels and HLA-DSA did not have histological rejection. Exploring the cellular origin of these cytokines, we found a corresponding expression in endothelial cells, monocytes, and natural killer cells in single-cell RNASeq data from kidney transplant biopsies. Finally, we confirmed secretion of these cytokines in HLA-DSA-mediated cross talk between endothelial cells, NK cells, and monocytes. In conclusion, blood pro-inflammatory cytokines are increased in kidney transplant patients with HLA-DSA, even in the absence of histology of rejection. These observations challenge the concept that histology is the gold standard for identification of ongoing allo-immune activation after transplantation.

Can Gene Expression Analysis in Zero-Time Biopsies Predict Kidney Transplant Rejection?

Zero-time biopsies are taken to determine the quality of the donor organ at the time of transplantation. Histological analyses alone have so far not been able to identify parameters that allow the prediction of subsequent rejection episodes or graft survival. This study investigated whether gene expression analyses of zero-time biopsies might support this prediction. Using a well-characterized cohort of 26 zero-time biopsies from renal transplant patients that include 4 living donor (LD) and 22 deceased donor (DD) biopsies that later developed no rejection (Ctrl, n = 7), delayed graft function (DGF, n = 4), cellular (T-cell mediated rejection; TCMR, n = 8), or antibody-mediated rejection (ABMR, n = 7), we analyzed gene expression profiles for different types of subsequent renal transplant complication. To this end, RNA was isolated from formalin-fixed, paraffin-embedded (FFPE) sections and gene expression profiles were quantified. Results were correlated with transplant data and B-cell, and plasma cell infiltration was assessed by immunofluorescence microscopy. Both principal component analysis and clustering analysis of gene expression data revealed marked separation between LDs and DDs. Differential expression analysis identified 185 significant differentially expressed genes (adjusted p < 0.05). The expression of 68% of these genes significantly correlated with cold ischemia time (CIT). Furthermore, immunoglobulins were differentially expressed in zero-time biopsies from transplants later developing rejection (TCMR + ABMR) compared to non-rejected (Ctrl + DGF) transplants. In addition, immunoglobulin expression did not correlate with CIT but was increased in transplants with previous acute renal failure (ARF). In conclusion, gene expression profiles in zero-time biopsies derived from LDs are markedly different from those of DDs. Pre-transplant ARF increased immunoglobulin expression, which might be involved in triggering later rejection events. However, these findings must be confirmed in larger cohorts and the role of early immunoglobulin upregulation in zero-biopsies needs further clarification.

SLAMF8 Participates in Acute Renal Transplant Rejection via TLR4 Pathway on Pro-Inflammatory Macrophages

Background

Acute rejection (AR) in kidney transplantation is an established risk factor that reduces the survival rate of allografts. Despite standard immunosuppression, molecules with regulatory control in the immune pathway of AR can be used as important targets for therapeutic operations to prevent rejection.

Methods

We downloaded the microarray data of 15 AR patients and 37 non-acute rejection (NAR) patients from Gene Expression Omnibus (GEO). Gene network was constructed, and genes were classified into different modules using weighted gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cytoscape were applied for the hub genes in the most related module to AR. Different cell types were explored by xCell online database and single-cell RNA sequencing. We also validated the SLAMF8 and TLR4 levels in Raw264.7 and human kidney tissues of TCMR.

Results

A total of 1,561 differentially expressed genes were filtered. WGCNA was constructed, and genes were classified into 12 modules. Among them, the green module was most closely associated with AR. These genes were significantly enriched in 20 pathway terms, such as cytokine–cytokine receptor interaction, chemokine signaling pathway, and other important regulatory processes. Intersection with GS > 0.4, MM > 0.9, the top 10 MCC values and DEGs in the green module, and six hub genes (DOCK2, NCKAP1L, IL2RG, SLAMF8, CD180, and PTPRE) were identified. Their expression levels were all confirmed to be significantly elevated in AR patients in GEO, Nephroseq, and quantitative real-time PCR (qRT-PCR). Single-cell RNA sequencing showed that AR patient had a higher percentage of native T, CD1C+_B DC, NKT, NK, and monocytes in peripheral blood mononuclear cells (PBMCs). Xcell enrichment scores of 20 cell types were significantly different (p<0.01), mostly immune cells, such as B cells, CD4+ Tem, CD8+ T cells, CD8+ Tcm, macrophages, M1, and monocytes. GSEA suggests that highly expressed six hub genes are correlated with allograft rejection, interferon γ response, interferon α response, and inflammatory response. In addition, SLAMF8 is highly expressed in human kidney tissues of TCMR and in M1 phenotype macrophages of Raw264.7 cell line WGCNA accompanied by high expression of TLR4.

Conclusion

This study demonstrates six hub genes and functionally enriched pathways related to AR. SLAMF8 is involved in the M1 macrophages via TLR4, which contributed to AR process.

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.

Acute and Chronic Changes in Gene Expression After CMV DNAemia in Kidney Transplant Recipients

Cytomegalovirus (CMV) viremia continues to cause significant morbidity and mortality in kidney transplant patients with clinical complications including organ rejection and death. Whole blood gene expression dynamics in CMV viremic patients from onset of DNAemia through convalescence has not been well studied to date in humans. To evaluate how CMV infection impacts whole blood leukocyte gene expression over time, we evaluated a matched cohort of 62 kidney transplant recipients with and without CMV DNAemia using blood samples collected at multiple time points during the 12-month period after transplant. While transcriptomic differences were minimal at baseline between DNAemic and non-DNAemic patients, hundreds of genes were differentially expressed at the long-term timepoint, including genes enriching for pathways important for macrophages, interferon, and IL-8 signaling. Amongst patients with CMV DNAemia, the greatest amount of transcriptomic change occurred between baseline and 1-week post-DNAemia, with increase in pathways for interferon signaling and cytotoxic T cell function. Time-course gene set analysis of these differentially expressed genes revealed that most of the enriched pathways had a significant time-trend. While many pathways that were significantly down- or upregulated at 1 week returned to baseline-like levels, we noted that several pathways important in adaptive and innate cell function remained upregulated at the long-term timepoint after resolution of CMV DNAemia. Differential expression analysis and time-course gene set analysis revealed the dynamics of genes and pathways involved in the immune response to CMV DNAemia in kidney transplant patients. Understanding transcriptional changes caused by CMV DNAemia may identify the mechanism behind patient vulnerability to CMV reactivation and increased risk of rejection in transplant recipients and suggest protective strategies to counter the negative immunologic impact of CMV. These findings provide a framework to identify immune correlates for risk assessment and guiding need for extending antiviral prophylaxis.

Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.

Donor-Specific Antibody Is Associated with Increased Expression of Rejection Transcripts in Renal Transplant Biopsies Classified as No Rejection

BACKGROUND

Donor -specific HLA antibody (DSA) is present in many kidney transplant patients whose biopsies are classified as no rejection (NR). We explored whether in some NR kidneys DSA has subtle effects not currently being recognized.

METHODS

We used microarrays to examine the relationship between standard-of-care DSA and rejection-related transcript increases in 1679 kidney transplant indication biopsies in the INTERCOMEX study (ClinicalTrials.gov NCT01299168), focusing on biopsies classified as NR by automatically assigned archetypal clustering. DSA testing results were available for 835 NR biopsies and were positive in 271 (32%).

RESULTS

DSA positivity in NR biopsies was associated with mildly increased expression of antibody-mediated rejection (ABMR)-related transcripts, particularly IFNG-inducible and NK cell transcripts. We developed a machine learning DSA probability (DSA_Prob) classifier based on transcript expression in biopsies from DSA-positive versus DSA-negative patients, assigning scores using 10-fold cross-validation. This DSA_Prob classifier was very similar to a previously described "ABMR probability" classifier trained on histologic ABMR in transcript associations and prediction of molecular or histologic ABMR. Plotting the biopsies using Uniform Manifold Approximation and Projection revealed a gradient of increasing molecular ABMR-like transcript expression in NR biopsies, associated with increased DSA (P<2 × 10^-16). In biopsies with no molecular or histologic rejection, increased DSA_Prob or ABMR probability scores were associated with increased risk of kidney failure over 3 years.

CONCLUSIONS

Many biopsies currently considered to have no molecular or histologic rejection have mild increases in expression of ABMR-related transcripts, associated with increasing frequency of DSA. Thus, mild molecular ABMR-related pathology is more common than previously realized.

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).

Beyond the Biopsy: Monitoring Immune Status in Kidney Recipients

Improved long-term kidney allograft survival is largely related to better outcomes at 12 months, in association with declining acute rejection rates and more efficacious immunosuppression. Finding the right balance between under- and overimmunosuppression or rejection versus immunosuppression toxicity remains one of transplant's holy grails. In the absence of precise measures of immunosuppression burden, transplant clinicians rely on nonspecific, noninvasive tests and kidney allograft biopsy generally performed for cause. This review appraises recent advances of conventional monitoring strategies and critically examines the plethora of emerging tests utilizing tissue, urine, and blood samples to improve upon the diagnostic precision of allograft surveillance.

Multiplex gene analysis reveals T-cell and antibody-mediated rejection-specific upregulation of complement in renal transplants

In renal transplantation, complement is involved in ischemia reperfusion injury, graft rejection and dysfunction. However, it is still unclear how induction of complement and its activation are initiated. Using allograft biopsies of a well-characterized cohort of 28 renal transplant patients with no rejection (Ctrl), delayed graft function (DGF), acute T-cell-mediated (TCMR) or antibody-mediated rejection (ABMR) we analyzed differences in complement reaction. For that mRNA was isolated from FFPE sections, quantified with a multiplex gene expression panel and correlated with transplant conditions and follow-up of patients. Additionally, inflammatory cells were quantified by multiplex immunohistochemistry. In allograft biopsies with TCMR and ABMR gene expression of C1QB was 2-4 fold elevated compared to Ctrl. In TCMR biopsies, mRNA counts of several complement-related genes including C1S, C3, CFB and complement regulators CFH, CR1 and SERPING1 were significantly increased compared to Ctrl. Interestingly, expression levels of about 75% of the analyzed complement related genes correlated with cold ischemia time (CIT) and markers of inflammation. In conclusion, this study suggest an important role of complement in transplant pathology which seems to be at least in part triggered by CIT. Multiplex mRNA analysis might be a useful method to refine diagnosis and explore new pathways involved in rejection.

Integrative Analysis of Prognostic Biomarkers for Acute Rejection in Kidney Transplant Recipients

BACKGROUND

Noninvasive biomarkers may predict adverse events such as acute rejection after kidney transplantation and may be preferable to existing methods because of superior accuracy and convenience. It is uncertain how these biomarkers, often derived from a single study, perform across different cohorts of recipients.

METHODS

Using a cross-validation framework that evaluates the performance of biomarkers, the aim of this study was to devise an integrated gene signature set that predicts acute rejection in kidney transplant recipients. Inclusion criteria were publicly available datasets of gene signatures that reported acute rejection episodes after kidney transplantation. We tested the predictive probability for acute rejection using gene signatures within individual datasets and validated the set using other datasets. Eight eligible studies of 1454 participants, with a total of 512 acute rejections episodes were included.

RESULTS

All sets of gene signatures had good positive and negative predictive values (79%-96%) for acute rejection within their own cohorts, but the predictability reduced to <50% when tested in other independent datasets. By integrating signature sets with high specificity scores across all studies, a set of 150 genes (included CXCL6, CXCL11, OLFM4, and PSG9) which are known to be associated with immune responses, had reasonable predictive values (varied between 69% and 90%).

CONCLUSIONS

A set of gene signatures for acute rejection derived from a specific cohort of kidney transplant recipients do not appear to provide adequate prediction in an independent cohort of transplant recipients. However, the integration of gene signature sets with high specificity scores may improve the prediction performance of these markers.

B-cell Deficiency Attenuates Transplant Glomerulopathy in a Rat Model of Chronic Active Antibody-mediated Rejection

BACKGROUND

Transplant glomerulopathy (TG) is a pathological feature of chronic active antibody-mediated rejection (cAMR) and is associated with renal allograft failure. The specific role of B cells in the pathogenesis of TG is unclear.

METHODS

We used a minor mismatched rat kidney transplant model with B cell-deficient recipients, generated by clustered regularly interspaced short palindromic repeats/Cas9 technology, to investigate the impact of B-cell depletion on the pathogenesis of TG. We hypothesized that B-cell deficiency would prevent TG in the rat kidney transplant model of cAMR. Treatment groups included syngeneic, allogeneic, sensitized allogeneic, and B cell-deficient allogeneic transplant recipients.

RESULTS

B cell-deficient recipients demonstrated reduced TG lesions, decreased microvascular inflammation, reduced allograft infiltrating macrophages, and reduced interferon gamma transcripts within the allograft. Allograft transcript levels of interferon gamma, monocyte chemoattractant protein-1, and interleukin-1β correlated with numbers of intragraft macrophages. B cell-deficient recipients lacked circulating donor-specific antibodies and had an increased splenic regulatory T-cell population.

CONCLUSIONS

In this model of cAMR, B-cell depletion attenuated the development of TG with effects on T cell and innate immunity.

Renal allograft DARCness in subclinical acute and chronic active ABMR

Gene expression profiling of renal allograft biopsies revealed the Duffy antigen receptor for chemokines (DARC) as being strikingly upregulated in antibody‐mediated rejection (ABMR). DARC has previously been shown to be associated with endothelial injury. This study aimed at assessing the value of DARC immunohistochemistry as diagnostic marker in ABMR. The study was performed on 82 prospectively collected biopsies of a clinically well‐defined population (BORTEJECT trial, NCT01873157) of DSA‐positive patients with gene expression data available for all biopsies. Diagnostic histologic assessment of biopsies was performed according to the Banff diagnostic scheme. DARC expression was focally accentuated, on peritubular capillaries (PTC) mostly in areas of interstitial fibrosis and/or inflammation. DARC positivity was associated with diagnosis of ABMR and correlated with DARC gene expression levels detected by microarray analysis. Still, as previously described, a substantial number of biopsies without signs of rejection showed DARC‐positive PTC. We did not observe significantly reduced graft survival in cases showing histologic signs of ABMR and being DARC‐positive, as compared to DARC‐negative ABMR. In summary, the upregulation of DARC, detected by immunohistochemistry, is associated with but not specific for ABMR. We did not observe reduced graft survival in DARC‐positive patients.

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.

Key driver genes as potential therapeutic targets in renal allograft rejection

Acute rejection (AR) in renal transplantation is an established risk factor for reduced allograft survival. Molecules with regulatory control among immune pathways of AR that are inadequately suppressed, despite standard-of-care immunosuppression, could serve as important targets for therapeutic manipulation to prevent rejection. Here, an integrative, network-based computational strategy incorporating gene expression and genotype data of human renal allograft biopsy tissue was applied, to identify the master regulators - the key driver genes (KDGs) - within dysregulated AR pathways. A 982-meta-gene signature with differential expression in AR versus non-AR was identified from a meta-analysis of microarray data from 735 human kidney allograft biopsy samples across 7 data sets. Fourteen KDGs were derived from this signature. Interrogation of 2 publicly available databases identified compounds with predicted efficacy against individual KDGs or a key driver-based gene set, respectively, which could be repurposed for AR prevention. Minocycline, a tetracycline antibiotic, was chosen for experimental validation in a murine cardiac allograft model of AR. Minocycline attenuated the inflammatory profile of AR compared with controls and when coadministered with immunosuppression prolonged graft survival. This study demonstrates that a network-based strategy, using expression and genotype data to predict KDGs, assists target prioritization for therapeutics in renal allograft 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.

Kidney Biopsy Findings in Patients with COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) is thought to cause kidney injury by a variety of mechanisms. To date, pathologic analyses have been limited to patient reports and autopsy series.

METHODS

We evaluated biopsy samples of native and allograft kidneys from patients with COVID-19 at a single center in New York City between March and June of 2020. We also used immunohistochemistry, in situ hybridization, and electron microscopy to examine this tissue for presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

RESULTS

The study group included 17 patients with COVID-19 (12 men, 12 black; median age of 54 years). Sixteen patients had comorbidities, including hypertension, obesity, diabetes, malignancy, or a kidney or heart allograft. Nine patients developed COVID-19 pneumonia. Fifteen patients (88%) presented with AKI; nine had nephrotic-range proteinuria. Among 14 patients with a native kidney biopsy, 5 were diagnosed with collapsing glomerulopathy, 1 was diagnosed with minimal change disease, 2 were diagnosed with membranous glomerulopathy, 1 was diagnosed with crescentic transformation of lupus nephritis, 1 was diagnosed with anti-GBM nephritis, and 4 were diagnosed with isolated acute tubular injury. The three allograft specimens showed grade 2A acute T cell-mediated rejection, cortical infarction, or acute tubular injury. Genotyping of three patients with collapsing glomerulopathy and the patient with minimal change disease revealed that all four patients had APOL1 high-risk gene variants. We found no definitive evidence of SARS-CoV-2 in kidney cells. Biopsy diagnosis informed treatment and prognosis in all patients.

CONCLUSIONS

Patients with COVID-19 develop a wide spectrum of glomerular and tubular diseases. Our findings provide evidence against direct viral infection of the kidneys as the major pathomechanism for COVID-19-related kidney injury and implicate cytokine-mediated effects and heightened adaptive immune responses.

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.

Transcriptome Analysis in Renal Transplant Biopsies Not Fulfilling Rejection Criteria

The clinical significance of renal transplant biopsies displaying borderline changes suspicious for T-cell mediated rejection (TCMR) or interstitial fibrosis and tubular atrophy (IFTA) with interstitial inflammation has not been well defined. Molecular profiling to evaluate renal transplant biopsies using microarrays has been shown to be an objective measurement that adds precision to conventional histology. We review the contribution of transcriptomic analysis in surveillance and indication biopsies with borderline changes and IFTA associated with variable degrees of inflammation. Transcriptome analysis applied to biopsies with borderline changes allows to distinguish patients with rejection from those in whom mild inflammation mainly represents a response to injury. Biopsies with IFTA and inflammation occurring in unscarred tissue display a molecular pattern similar to TCMR while biopsies with IFTA and inflammation in scarred tissue, apart from T-cell activation, also express B cell, immunoglobulin and mast cell-related genes. Additionally, patients at risk for IFTA progression can be identified by genes mainly reflecting fibroblast dysregulation and immune activation. At present, it is not well established whether the expression of rejection gene transcripts in patients with fibrosis and inflammation is the consequence of an alloimmune response, tissue damage or a combination of both.

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.

High Dimensional Renal Profiling: Towards a Better Understanding or Renal Transplant Immune Suppression

PURPOSE OF REVIEW

The goal of this review is to discuss new approaches to avoid CNI/CCS toxicities with a focus on new biologics and new methods to understand transplant rejection at the single-cell level.

RECENT FINDINGS

Recently developed biologics hold significant promise as the next wave of therapeutics designed to promote CNI/CCS-free long-term allograft acceptance. Indeed, belatacept, soluble CTLA4-Ig, is largely devoid of CNI-like toxicities, although it is accompanied by an increased frequency of acute rejection. Besides belatacept, other biologics hold promise as CNI-free immune suppressive approaches. Finally, powerful new single cell approaches can enable characterization of cellular populations that drive rejection within the rejecting allograft.

SUMMARY

We propose that the incorporated single cell profiling into studies investigating new biologics in transplantation, could be tailored to each patient, correlated with potential biomarkers in the blood and urine, and provide a platform where therapeutic targets can be rationally defined, mechanistically-based, and exploited.

Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers

We previously reported a system for assessing rejection in kidney transplant biopsies using microarray-based gene expression data, the Molecular Microscope^® Diagnostic System (MMDx). The present study was designed to optimize the accuracy and stability of MMDx diagnoses by replacing single machine learning classifiers with ensembles of diverse classifier methods. We also examined the use of automated report sign-outs and the agreement between multiple human interpreters of the molecular results. Ensembles generated diagnoses that were both more accurate than the best individual classifiers, and nearly as stable as the best, consistent with expectations from the machine learning literature. Human experts had ≈93% agreement (balanced accuracy) signing out the reports, and random forest-based automated sign-outs showed similar levels of agreement with the human experts (92% and 94% for predicting the expert MMDx sign-outs for T cell-mediated (TCMR) and antibody-mediated rejection (ABMR), respectively). In most cases disagreements, whether between experts or between experts and automated sign-outs, were in biopsies near diagnostic thresholds. Considerable disagreement with histology persisted. The balanced accuracies of MMDx sign-outs for histology diagnoses of TCMR and ABMR were 73% and 78%, respectively. Disagreement with histology is largely due to the known noise in histology assessments (ClinicalTrials.gov NCT01299168).

WNT pathway signaling is associated with microvascular injury and predicts kidney transplant failure

Microvascular injury is associated with accelerated kidney transplant dysfunction and allograft failure. Molecular pathology can identify new mechanisms of microvascular injury while improving on the diagnostic and prognostic capabilities of traditional histology. We conducted a case-control study of archived kidney biopsy specimens stored up to 10 years with microvascular injury (n = 50) compared with biopsy specimens without histologic injury (n = 45) from patients of similar age, race, and sex. We measured WNT gene expression with a multiplex quantification platform by using digital barcoding, given the importance of WNT reactivation to the response to wounding in the kidney microvasculature and other compartments. Of 210 genes from a commercial WNT panel, 71 were associated with microvascular injury and 79 were associated with allograft failure, with considerable overlap of genes between each set. Molecular pathology identified 46 biopsy specimens with molecular evidence of microvascular injury; 18 (39%) were either C4d negative, donor-specific antibody negative, or had no microvascular injury by histology. The majority of cases with molecular evidence of microvascular injury had poor long-term outcomes. We identified novel WNT pathway genes associated with microvascular injury and allograft failure in residual clinical biopsy specimens obtained up to 10 years earlier. Further mechanistic studies may identify the WNT pathway as a new diagnostic and therapeutic target.

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.

Exploring the cardiac response to injury in heart transplant biopsies

BACKGROUND

Because injury is universal in organ transplantation, heart transplant endomyocardial biopsies present an opportunity to explore response to injury in heart parenchyma. Histology has limited ability to assess injury, potentially confusing it with rejection, whereas molecular changes have potential to distinguish injury from rejection. Building on previous studies of transcripts associated with T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR), we explored transcripts reflecting injury.

METHODS

Microarray data from 889 prospectively collected endomyocardial biopsies from 454 transplant recipients at 14 centers were subjected to unsupervised principal component analysis and archetypal analysis to detect variation not explained by rejection. The resulting principal component and archetype scores were then examined for their transcript, transcript set, and pathway associations and compared to the histology diagnoses and left ventricular function.

RESULTS

Rejection was reflected by principal components PC1 and PC2, and by archetype scores S2TCMR, and S3ABMR, with S1normal indicating normalness. PC3 and a new archetype score, S4injury, identified unexplained variation correlating with expression of transcripts inducible in injury models, many expressed in macrophages and associated with inflammation in pathway analysis. S4injury scores were high in recent transplants, reflecting donation-implantation injury, and both S4injury and S2TCMR were associated with reduced left ventricular ejection fraction.

CONCLUSION

Assessment of injury is necessary for accurate estimates of rejection and for understanding heart transplant phenotypes. Biopsies with molecular injury but no molecular rejection were often misdiagnosed rejection by histology.TRAIL REGISTRATION. ClinicalTrials.gov NCT02670408FUNDING. Roche Organ Transplant Research Foundation, the University of Alberta Hospital Foundation, and Alberta Health Services.

Exploration of the therapeutic aspects of Lck: A kinase target in inflammatory mediated pathological conditions

Lck, a non-receptor src family kinase, plays a vital role in various cellular processes such as cell cycle control, cell adhesion, motility, proliferation and differentiation. As a 56 KDa protein, Lck phosphorylates tyrosine residues of various proteins such as ZAP-70, ITK and protein kinase C. The structure of Lck is comprised of three domains, one SH3 in tandem with a SH2 domain at the amino terminal and the kinase domain at the carboxy terminal. Physiologically, Lck is involved in the development, function and differentiation of T-cells. Additionally, Lck regulates neurite outgrowth and maintains long-term synaptic plasticity in neurons. Given a major role of Lck in cytokine production and T cell signaling, alteration in expression and activity of Lck may result in various diseased conditions like cancer, asthma, diabetes, rheumatoid arthritis, psoriasis, inflammatory bowel diseases such as Crohn's disease and ulcerative colitis, atherosclerosis etc. This article provides evidence and information establishing Lck as one of the therapeutic targets in various inflammation mediated pathophysiological conditions.

Molecular profiling of subclinical inflammatory lesions in long-term surviving adult liver transplant recipients

BACKGROUND & AIMS

Subclinical inflammatory changes are commonly described in long-term transplant recipients undergoing protocol liver biopsies. The pathogenesis of these lesions remains unclear. The aim of this study was to identify the key molecular pathways driving progressive subclinical inflammatory liver allograft damage.

METHODS

All liver recipients followed at Hospital Clínic Barcelona who were >10 years post-transplant were screened for participation in the study. Patients with recurrence of underlying liver disease, biliary or vascular complications, chronic rejection, and abnormal liver function tests were excluded. Sixty-seven patients agreed to participate and underwent blood and serological tests, transient elastography and a liver biopsy. Transcriptome profiling was performed on RNA extracted from 49 out of the 67 biopsies employing a whole genome next generation sequencing platform. Patients were followed for a median of 6.8 years following the index liver biopsy.

RESULTS

Median time since transplantation to liver biopsy was 13 years (10-22). The most frequently observed histological abnormality was portal inflammation with different degrees of fibrosis, present in 45 biopsies (67%). Two modules of 102 and 425 co-expressed genes were significantly correlated with portal inflammation, interface hepatitis and portal fibrosis. These modules were enriched in molecular pathways known to be associated with T cell mediated rejection. Liver allografts showing the highest expression levels for the two modules recapitulated the transcriptional profile of biopsies with clinically apparent rejection and developed progressive damage over time, as assessed by non-invasive markers of fibrosis.

CONCLUSIONS

A large proportion of adult liver transplant recipients who survive long-term exhibit subclinical histological abnormalities. The transcriptomic profile of these patients' liver tissue closely resembles that of T cell mediated rejection and may result in progressive allograft damage.

LAY SUMMARY

A large proportion of adult liver transplant recipients who survive for a long time exhibit subclinical histological abnormalities. The expression profile (a measurement of the activity of genes) of liver tissue from a large fraction of these patients closely resembles the profile of T cell mediated rejection. Liver allografts showing the highest expression levels of rejection-related genes developed progressive damage over time.

LCK as a Potential Therapeutic Target for Acute Rejection after Kidney Transplantation: A Bioinformatics Clue

Objectives

We aim to identify the key biomarker of acute rejection (AR) after kidney transplantation via bioinformatics methods.

Methods

The gene expression data GSE75693 of 30 samples with stable kidney transplantation recipients and 15 AR samples were downloaded and analyzed by the limma package to identify differentially expressed genes (DEGs). Then, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were done to explore the biological functions and potential important pathways of DEGs. Finally, protein-protein interactions (PPIs) and literature mining were applied to construct the cocitation network and to select the hub protein.

Results

A total of 437 upregulated genes and 353 downregulated genes were selected according to P < 0.01 and |log₂(fold change)| > 1.0. DEGs of AR are mainly located on membranes and impact the activation of receptors in immune responses. In the PPI network, Src kinase, lymphocyte kinase (LCK), CD3G, B2M, interferon-γ, CD3D, tumor necrosis factor, VAV1, and CD3E in the T cell receptor signaling pathway were selected as important factors, and LCK was identified as the hub protein.

Conclusion

LCK, via acting on T-cell receptor, might be a potential therapeutic target for AR after kidney transplantation.

Review: The transcripts associated with organ allograft rejection

The molecular mechanisms operating in human organ transplant rejection are best inferred from the mRNAs expressed in biopsies because the corresponding proteins often have low expression and short half-lives, while small non-coding RNAs lack specificity. Associations should be characterized in a population that rigorously identifies T cell-mediated (TCMR) and antibody-mediated rejection (ABMR). This is best achieved in kidney transplant biopsies, but the results are generalizable to heart, lung, or liver transplants. Associations can be universal (all rejection), TCMR-selective, or ABMR-selective, with universal being strongest and ABMR-selective weakest. Top universal transcripts are IFNG-inducible (eg, CXCL11 IDO1, WARS) or shared by effector T cells (ETCs) and NK cells (eg, KLRD1, CCL4). TCMR-selective transcripts are expressed in activated ETCs (eg, CTLA4, IFNG), activated (eg, ADAMDEC1), or IFNG-induced macrophages (eg, ANKRD22). ABMR-selective transcripts are expressed in NK cells (eg, FGFBP2, GNLY) and endothelial cells (eg, ROBO4, DARC). Transcript associations are highly reproducible between biopsy sets when the same rejection definitions, case mix, algorithm, and technology are applied, but exact ranks will vary. Previously published rejection-associated transcripts resemble universal and TCMR-selective transcripts due to incomplete representation of ABMR. Rejection-associated transcripts are never completely rejection-specific because they are shared with the stereotyped response-to-injury and innate immunity.

A molecular biopsy test based on arteriolar under-hyalinosis reflects increased probability of rejection related to under-immunosuppression

Calcineurin inhibitor immunosuppressive drugs induce changes such as arteriolar hyalinosis (ah) in kidney transplants, raising the possibility that molecular changes in biopsies related to histologic ah can provide information about drug exposure. We hypothesized that molecular changes associated with less-than-expected hyalinosis might highlight a subpopulation of patients with under-immunosuppression/nonadherence at intermediate times of biopsy posttransplant (TxBx). Using gene expression data from 562 indication biopsies, we developed a molecular classifier for predicting the expected ah lesions (Mah ) at a particular TxBx. Mah -scores increased linearly with log(TxBx), but some biopsies had lower scores than expected for TxBx. The deviation of individual Mah -scores below the predicted regression line of Mah -scores vs TxBx is defined as "low hyalinosis index." Low hyalinosis indices were frequent in biopsies between 3 months and 3 years posttransplant, particularly among biopsies lacking histologic hyalinosis (ah0), and were associated with T cell-mediated rejection and a subset of recent-onset antibody-mediated rejection without glomerular double contours. In patients with medical records available for review, low hyalinosis indices were frequently associated with physician-recorded concerns about nonadherence (suspected or proven). We conclude that the Mah classifier and hyalinosis index identify indication biopsies with rejection for which the possibility of patient nonadherence should be considered.