Genomic analysis reveals poor separation of human cardiomyopathies of ischemic and nonischemic etiologies

Unraveling the Etiology of Dilated Cardiomyopathy through Differential miRNA-mRNA Interactome

Dilated cardiomyopathy (DCM) encompasses various acquired or genetic diseases sharing a common phenotype. The understanding of pathogenetic mechanisms and the determination of the functional effects of each etiology may allow for tailoring different therapeutic strategies. MicroRNAs (miRNAs) have emerged as key regulators in cardiovascular diseases, including DCM. However, their specific roles in different DCM etiologies remain elusive. Here, we applied mRNA-seq and miRNA-seq to identify the gene and miRNA signature from myocardial biopsies from four patients with DCM caused by volume overload (VCM) and four with ischemic DCM (ICM). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used for differentially expressed genes (DEGs). The miRNA-mRNA interactions were identified by Pearson correlation analysis and miRNA target-prediction programs. mRNA-seq and miRNA-seq were validated by qRT-PCR and miRNA-mRNA interactions were validated by luciferase assays. We found 112 mRNAs and five miRNAs dysregulated in VCM vs. ICM. DEGs were positively enriched for pathways related to the extracellular matrix (ECM), mitochondrial respiration, cardiac muscle contraction, and fatty acid metabolism in VCM vs. ICM and negatively enriched for immune-response-related pathways, JAK-STAT, and NF-kappa B signaling. We identified four pairs of negatively correlated miRNA-mRNA: miR-218-5p-DDX6, miR-218-5p-TTC39C, miR-218-5p-SEMA4A, and miR-494-3p-SGMS2. Our study revealed novel miRNA-mRNA interaction networks and signaling pathways for VCM and ICM, providing novel insights into the development of these DCM etiologies.

Time-ordered dysregulated ceRNA networks reveal disease progression and diagnostic biomarkers in ischemic and dilated cardiomyopathy

Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) are the two main causes of heart failure (HF). Despite similar clinical characteristics and common “HF pathways”, ICM and DCM are expected to have different personalized treatment strategies. The underlying mechanisms of ICM and DCM have yet to be fully elucidated. The present study developed a novel computational method for identifying dysregulated long noncoding RNA (lncRNA)–microRNA (miRNA)–mRNA competing endogenous RNA (ceRNA) triplets. Time-ordered dysregulated ceRNA networks were subsequently constructed to reveal the possible disease progression of ICM and DCM based on the method. Biological functional analysis indicated that ICM and DCM had similar features during myocardial remodeling, whereas their characteristics differed during progression. Specifically, disturbance of myocardial energy metabolism may be the main characteristic during DCM progression, whereas early inflammation and response to oxygen are the characteristics that may be specific to ICM. In addition, several panels of diagnostic biomarkers for differentiating non-heart failure (NF) and ICM (NF-ICM), NF-DCM, and ICM-DCM were identified. Our study reveals biological differences during ICM and DCM progression and provides potential diagnostic biomarkers for ICM and DCM.

CRISPLD1: a novel conserved target in the transition to human heart failure

Heart failure is a major health problem worldwide with a significant morbidity and mortality rate. Although studied extensively in animal models, data from patients at the compensated disease stage are lacking. We sampled myocardium biopsies from aortic stenosis patients with compensated hypertrophy and moderate heart failure and used transcriptomics to study the transition to failure. Sequencing and comparative analysis of analogous samples of mice with transverse aortic constriction identified 25 candidate genes with similar regulation in response to pressure overload, reflecting highly conserved molecular processes. The gene cysteine-rich secretory protein LCCL domain containing 1 (CRISPLD1) is upregulated in the transition to failure in human and mouse and its function is unknown. Homology to ion channel regulatory toxins suggests a role in Ca²⁺ cycling. CRISPR/Cas9-mediated loss-of-function leads to dysregulated Ca²⁺ handling in human-induced pluripotent stem cell-derived cardiomyocytes. The downregulation of prohypertrophic, proapoptotic and Ca²⁺-signaling pathways upon CRISPLD1-KO and its upregulation in the transition to failure implicates a contribution to adverse remodeling. These findings provide new pathophysiological data on Ca²⁺ regulation in the transition to failure and novel candidate genes with promising potential for therapeutic interventions.

Transcriptome signature of ventricular arrhythmia in dilated cardiomyopathy reveals increased fibrosis and activated TP53

AIMS

One-third of DCM patients experience ventricular tachycardia (VT), but a clear biological basis for this has not been established. The purpose of this study was to identify transcriptome signatures and enriched pathways in the hearts of dilated cardiomyopathy (DCM) patients with VT.

METHODS AND RESULTS

We used RNA-sequencing in explanted heart tissue from 49 samples: 19 DCM patients with VT, 16 DCM patients without VT, and 14 non-failing controls. We compared each DCM cohort to the controls and identified the genes that were differentially expressed in DCM patients with VT but not without VT. Differentially expressed genes were evaluated using pathway analysis, and pathways of interest were investigated by qRT-PCR validation, Western blot, and microscopy. There were 590 genes differentially expressed in DCM patients with VT that are not differentially expressed in patients without VT. These genes were enriched for genes in the TGFß1 and TP53 signaling pathways. Increased fibrosis and activated TP53 signaling was demonstrated in heart tissue of DCM patients with VT.

CONCLUSIONS

Our study supports that distinct biological mechanisms distinguish ventricular arrhythmia in DCM patients.

Transcriptome analysis of human heart failure reveals dysregulated cell adhesion in dilated cardiomyopathy and activated immune pathways in ischemic heart failure

Background

Current heart failure (HF) treatment is based on targeting symptoms and left ventricle dysfunction severity, relying on a common HF pathway paradigm to justify common treatments for HF patients. This common strategy may belie an incomplete understanding of heterogeneous underlying mechanisms and could be a barrier to more precise treatments. We hypothesized we could use RNA-sequencing (RNA-seq) in human heart tissue to delineate HF etiology-specific gene expression signatures.

Results

RNA-seq from 64 human left ventricular samples: 37 dilated (DCM), 13 ischemic (ICM), and 14 non-failing (NF). Using a multi-analytic approach including covariate adjustment for age and sex, differentially expressed genes (DEGs) were identified characterizing HF and disease-specific expression. Pathway analysis investigated enrichment for biologically relevant pathways and functions. DCM vs NF and ICM vs NF had shared HF-DEGs that were enriched for the fetal gene program and mitochondrial dysfunction. DCM-specific DEGs were enriched for cell-cell and cell-matrix adhesion pathways. ICM-specific DEGs were enriched for cytoskeletal and immune pathway activation. Using the ICM and DCM DEG signatures from our data we were able to correctly classify the phenotypes of 24/31 ICM and 32/36 DCM samples from publicly available replication datasets.

Conclusions

Our results demonstrate the commonality of mitochondrial dysfunction in end-stage HF but more importantly reveal key etiology-specific signatures. Dysfunctional cell-cell and cell-matrix adhesion signatures typified DCM whereas signals related to immune and fibrotic responses were seen in ICM. These findings suggest that transcriptome signatures may distinguish end-stage heart failure, shedding light on underlying biological differences between ICM and DCM.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5213-9) contains supplementary material, which is available to authorized users.

Epigenomic and transcriptomic approaches in the post-genomic era: path to novel targets for diagnosis and therapy of the ischaemic heart? Position Paper of the European Society of Cardiology Working Group on Cellular Biology of the Heart

Despite advances in myocardial reperfusion therapies, acute myocardial ischaemia/reperfusion injury and consequent ischaemic heart failure represent the number one cause of morbidity and mortality in industrialized societies. Although different therapeutic interventions have been shown beneficial in preclinical settings, an effective cardioprotective or regenerative therapy has yet to be successfully introduced in the clinical arena. Given the complex pathophysiology of the ischaemic heart, large scale, unbiased, global approaches capable of identifying multiple branches of the signalling networks activated in the ischaemic/reperfused heart might be more successful in the search for novel diagnostic or therapeutic targets. High-throughput techniques allow high-resolution, genome-wide investigation of genetic variants, epigenetic modifications, and associated gene expression profiles. Platforms such as proteomics and metabolomics (not described here in detail) also offer simultaneous readouts of hundreds of proteins and metabolites. Isolated omics analyses usually provide Big Data requiring large data storage, advanced computational resources and complex bioinformatics tools. The possibility of integrating different omics approaches gives new hope to better understand the molecular circuitry activated by myocardial ischaemia, putting it in the context of the human ‘diseasome’. Since modifications of cardiac gene expression have been consistently linked to pathophysiology of the ischaemic heart, the integration of epigenomic and transcriptomic data seems a promising approach to identify crucial disease networks. Thus, the scope of this Position Paper will be to highlight potentials and limitations of these approaches, and to provide recommendations to optimize the search for novel diagnostic or therapeutic targets for acute ischaemia/reperfusion injury and ischaemic heart failure in the post-genomic era.

Right ventricular protein expression profile in end-stage heart failure

Little is known about the right ventricular (RV) proteome in human heart failure (HF), including possible differences compared to the left ventricular (LV) proteome. We used 2-dimensional differential in-gel electrophoresis (pH: 4-7, 10-150 kDa), followed by liquid chromatography tandem mass spectrometry, to compare the RV and LV proteomes in 12 explanted human hearts. We used Western blotting and multiple-reaction monitoring for protein verification and RNA sequencing for messenger RNA and protein expression correlation. In all 12 hearts, the right ventricles (RVs) demonstrated differential expression of 11 proteins relative to the left ventricles (LVs), including lesser expression of CRYM, TPM1, CLU, TXNL1, and COQ9 and greater expression of TNNI3, SAAI, ERP29, ACTN2, HSPB2, and NDUFS3. Principal-components analysis did not suggest RV-versus-LV proteome partitioning. In the nonischemic RVs (n = 6), 7 proteins were differentially expressed relative to the ischemic RVs (n = 6), including increased expression of CRYM, B7Z964, desmin, ANXA5, and MIME and decreased expression of SERPINA1 and ANT3. Principal-components analysis demonstrated partitioning of the nonischemic and ischemic RV proteomes, and gene ontology analysis identified differences in hemostasis and atherosclerosis-associated networks. There were no proteomic differences between RVs with echocardiographic dysfunction (n = 8) and those with normal function (n = 4). Messenger RNA and protein expression did not correlate consistently, suggesting a major role for RV posttranscriptional protein expression regulation. Differences in contractile, cytoskeletal, metabolic, signaling, and survival pathways exist between the RV and the LV in HF and may be related to the underlying HF etiology and differential posttranscriptional regulation.

The transcriptomic profile of peripheral blood nuclear cells in dogs with heart failure

Background

In recent years advances have been made in the investigative methods of molecular background of canine heart disease. Studies have been conducted to identify specific genes which, when pathologically expressed, could lead to the dysfunction of the canine heart or are correlated with heart failure. For this purpose genome wide microarray experiments on tissues from failing hearts have been performed. In the presented study a whole genome microarray analysis was used for the first time to describe the transcription profile of peripheral blood nuclear cells in dogs with heart failure. Dogs with recognized heart disease were classified according the ISACHC (International Small Animal Cardiac Health Council) classification scheme as class 1 (asymptomatic) - 13 dogs, class 2 (mild to moderate heart failure) - 13 dogs and class 3 (severe heart failure) - 12 dogs. The control group consisted of 14 healthy dogs. The clinical picture of the animals included: animal history, clinical examination, echocardiographic examination and where applicable electrocardiographic and radiographic examinations.

Results

In the present study we identified four sets of differentially expressed genes, namely heart-failure-specific genes and ISACHC1-specific genes, ISACHC2-sepcific genes and ISACHC-3 specific genes. The most important set consisted of genes differentially expressed in all dogs with heart failure, despite the ISACHC stage. We identified 71 heart-failure-specific genes which were involved in two statistically significant receptor signalling pathways, namely angiotensinR - > CREB/ELK-SRF/TP53 signalling and ephrinR - > actin signalling. The number of ISACHC1-specific genes was 83; ISACHC2-specific genes - 1247 and ISACHC3-specific - 200.

Conclusions

The transcriptomic profile of peripheral blood nuclear cells in dogs with heart failure seems to reflect the presence of clinical signs of the disease in patients based on the observation that the largest number of differentially expressed genes was identified in ISACHC 2 group of patients. This group consists of dogs just starting to show clinical signs of heart failure. A set of genes was also found to have changed expression in all dogs with heart failure, despite the stage of the disease.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-509) contains supplementary material, which is available to authorized users.

Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure?

Coronary artery disease (CAD) is one of the leading causes of death in the developed countries. Myocardial infarction (MI) is an acute episode of CAD that results in myocardial injury and subsequent heart failure (HF). In the acute phase of MI several risk factors for future cardiovascular events have been found. The molecular mechanisms of these disorders are still unknown, but altered gene expression may play an important role in the development and progression of cardiovascular diseases. High-throughput techniques should greatly facilitate the elucidation of the mechanisms and provide novel insights into the pathophysiology of cardiovascular diseases. In this review we focus on the perspectives of gene-expression profiling conducted on cardiac tissues and blood for the determination of novel diagnostic and prognostic markers and therapeutic targets.

A kinase interacting protein (AKIP1) is a key regulator of cardiac stress

cAMP-dependent protein kinase (PKA) regulates a myriad of functions in the heart, including cardiac contractility, myocardial metabolism,and gene expression. However, a molecular integrator of the PKA response in the heart is unknown. Here, we show that the PKA adaptor A-kinase interacting protein 1 (AKIP1) is up-regulated in cardiac myocytes in response to oxidant stress. Mice with cardiac gene transfer of AKIP1 have enhanced protection to ischemic stress. We hypothesized that this adaptation to stress was mitochondrial dependent. AKIP1 interacted with the mitochondrial localized apoptosis inducing factor (AIF) under both normal and oxidant stress. When cardiac myocytes or whole hearts are exposed to oxidant and ischemic stress, levels of both AKIP1 and AIF were enhanced. AKIP1 is preferentially localized to interfibrillary mitochondria and up-regulated in this cardiac mitochondrial subpopulation on ischemic injury. Mitochondria isolated from AKIP1 gene transferred hearts showed increased mitochondrial localization of AKIP1, decreased reactive oxygen species generation, enhanced calcium tolerance, decreased mitochondrial cytochrome C release,and enhance phosphorylation of mitochondrial PKA substrates on ischemic stress. These observations highlight AKIP1 as a critical molecular regulator and a therapeutic control point for stress adaptation in the heart.

Myocardial transcriptome analysis of human arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy primarily of the right ventricle characterized through fibrofatty replacement of cardiomyocytes. The genetic etiology in ARVC patients is most commonly caused by dominant inheritance and high genetic heterogeneity. Though histological examinations of ARVC-affected human myocardium reveals fibrolipomatous replacement, the molecular mechanisms leading to loss of cardiomyocytes are largely unknown. We therefore analyzed the transcriptomes of six ARVC hearts and compared our findings to six nonfailing donor hearts (NF). To characterize the ARVC-specific transcriptome, we compared our findings to samples from seven patients with idiopathic dilated cardiomyopathy (DCM). The myocardial DCM and ARVC samples were prepared from hearts explanted during an orthotopic heart transplantation representing myocardium from end-stage heart failure patients (NYHA IV). From each heart, left (LV) and right ventricular (RV) myocardial samples were analyzed by Affymetrix HG-U133 Plus 2.0 arrays, adding up to six sample groups. Unsupervised cluster analyses of the groups revealed a clear separation of NF and cardiomyopathy samples. However, in contrast to the other samples, the analyses revealed no distinct expression pattern in LV and RV of myocardial ARVC samples. We further identified differentially expressed transcripts using t-tests and found transcripts separating diseased and NF ventricular myocardium. Of note, in failing myocardium only ~15-16% of the genes are commonly regulated compared with NF samples. In addition both cardiomyopathies are clearly distinct on the transcriptome level. Comparison of the expression patterns between the failing RV and LV using a paired t-test revealed a lack of major differences between LV and RV gene expression in ARVC hearts. Our study is the first analysis of specific ARVC-related RV and LV gene expression patterns in terminal failing human hearts.

Reciprocal transcriptional regulation of metabolic and signaling pathways correlates with disease severity in heart failure

BACKGROUND

Systolic heart failure (HF) is a complex systemic syndrome that can result from a wide variety of clinical conditions and gene mutations. Despite phenotypic similarities, characterized by ventricular dilatation and reduced contractility, the extent of common and divergent gene expression between different forms of HF remains a matter of intense debate.

METHODS AND RESULTS

Using a meta-analysis of 28 experimental (mouse, rat, dog) and human HF microarray studies, we demonstrate that gene expression changes are characterized by a coordinated and reciprocal regulation of major metabolic and signaling pathways. In response to a wide variety of stressors in animal models of HF, including ischemia, pressure overload, tachypacing, chronic isoproterenol infusion, Chagas disease, and transgenic mouse models, major metabolic pathways are invariably downregulated, whereas cell signaling pathways are upregulated. In contrast to this uniform transcriptional pattern that recapitulates a fetal gene expression program in experimental animal models of HF, human HF microarray studies displayed a greater heterogeneity, with some studies even showing upregulation of metabolic and downregulation of signaling pathways in end-stage human hearts. These discrepant results between animal and human studies are due to a number of factors, prominently cardiac disease and variable exposure to cold cardioplegic solution in nonfailing human samples, which can downregulate transcripts involved in oxidative phosphorylation (OXPHOS), thus mimicking gene expression patterns observed in failing samples. Additionally, β-blockers and ACE inhibitor use in end-stage human HF was associated with higher levels of myocardial OXPHOS transcripts, thus partially reversing the fetal gene expression pattern. In human failing samples, downregulation of metabolism was associated with hemodynamic markers of disease severity.

CONCLUSIONS

Irrespective of the etiology, gene expression in failing myocardium is characterized by downregulation of metabolic transcripts and concomitant upregulation of cell signaling pathways. Gene expression changes along this metabolic-signaling axis in mammalian myocardium are a consistent feature in the heterogeneous transcriptional response observed in phenotypically similar models of HF.

Gene expression profiling in peripheral blood nuclear cells in patients with refractory ischaemic end-stage heart failure

Functional analysis of up- and down-regulated genes might reveal whether peripheral blood cells may be considered as a material of diagnostic or prognostic value in patients with end-stage heart failure (HF). The aim of the present study was to compare the transcriptomic profile of peripheral blood nuclear cells from 6 male patients with ischaemic end-stage HF with those of 6 male patients with asymptomatic cardiac dysfunction. The expression of genes in peripheral blood nuclear cells in both groups of patients was measured using whole-genome oligonucleotide microarrays utilizing 35 035 oligonucleotide probes. Microarray analyses revealed 130 down-regulated genes and 15 up-regulated genes in the patients with end-stage HF. Some of the down-regulated genes belonged to the pathways that other studies have shown to be down-regulated in cardiomyopathy. We also identified up-regulated genes that have been correlated with HF severity (CXCL16) and genes involved in the regulation of expression of platelet activation factor receptor (PTAFR, RBPSUH, MCC, and PSMA7). In conclusion, the identification of genes that are differentially expressed in peripheral blood nuclear cells of patients with HF supports the suggestion that this diagnostic approach may be useful in searching for the molecular predisposition for development of severe refractory HF in patients with post-infarction asymptomatic abnormalities and remodelling of the left ventricle. These results need further investigation and validation.

Cardiovascular translational medicine (III). Genomics and proteomics in heart failure research

Heart failure is a complex syndrome and is one of the main causes of morbidity and mortality in developed countries. Despite considerable research effort in recent years, heart failure prevention and treatment strategies still suffer significant limitations. New theoretical and technical approaches are, therefore, required. It is in this context that the "omic" sciences have a role to play in heart failure. The incorporation of "omic" methodologies into the study of human disease has substantially changed biological approaches to disease and has given an enormous impetus to the search for new disease mechanisms, as well as for novel biomarkers and therapeutic targets. The application of genomics, proteomics and metabonomics to heart failure research could increase our understanding of the origin and development of the different processes contributing to this syndrome, thereby enabling the establishment of specific diagnostic profiles and therapeutic templates that could help improve the poor prognosis associated with heart failure. This brief review contains a short description of the fundamental principles of the "omic" sciences and an evaluation of how these new techniques are currently contributing to research into human heart failure. The focus is mainly on the analysis of gene expression microarrays in the field of genomics and on studies using two-dimensional electrophoresis with mass spectrometry in the area of proteomics.

Global gene expression analysis in nonfailing and failing myocardium pre- and postpulsatile and nonpulsatile ventricular assist device support

Mechanical unloading by ventricular assist devices (VAD) leads to significant gene expression changes often summarized as reverse remodeling. However, little is known on individual transcriptome changes during VAD support and its relationship to nonfailing hearts (NF). In addition no data are available for the transcriptome regulation during nonpulsatile VAD support. Therefore we analyzed the gene expression patterns of 30 paired samples from VAD-supported (including 8 nonpulsatile VADs) and 8 nonfailing control hearts (NF) using the first total human genome array available. Transmural myocardial samples were collected for RNA isolation. RNA was isolated by commercial methods and processed according to chip-manufacturer recommendations. cRNA were hybridized on Affymetrix HG-U133 Plus 2.0 arrays, providing coverage of the whole human genome Array. Data were analyzed using Microarray Analysis Suite 5.0 (Affymetrix) and clustered by Expressionist software (Genedata). We found 352 transcripts were differentially regulated between samples from VAD implantation and NF, whereas 510 were significantly regulated between VAD transplantation and NF (paired t-test P < 0.001, fold change ≥1.6). Remarkably, only a minor fraction of 111 transcripts was regulated in heart failure (HF) and during VAD support. Unsupervised hierarchical clustering of paired VAD and NF samples revealed separation of HF and NF samples; however, individual differentiation of VAD implantation and VAD transplantation was not accomplished. Clustering of pulsatile and nonpulsatile VAD did not lead to robust separation of gene expression patterns. During VAD support myocardial gene expression changes do not indicate reversal of the HF phenotype but reveal a distinct HF-related pattern. Transcriptome analysis of pulsatile and nonpulsatile VAD-supported hearts did not provide evidence for a pump mode-specific transcriptome pattern.

Basic Mechanisms Mediating Cardiomyopathy and Heart Failure in Aging

Biological aging represents the major risk factor for the development of heart failure (HF), malignancies, and neurodegenerative diseases. While risk factors such as lifestyle patterns, genetic traits, blood lipid levels, and diabetes can contribute to its development, advancing age remains the most determinant predictor of cardiac disease. Several parameters of left ventricular function may be affected with aging, including increased duration of systole, decreased sympathetic stimulation, and increased left ventricle ejection time, while compliance decreases. In addition, changes in cardiac phenotype with diastolic dysfunction, reduced contractility, left ventricular hypertrophy, and HF, all increase in incidence with age. Given the limited capacity that the heart has for regeneration, reversing or slowing the progression of these abnormalities poses a major challenge. In this chapter, we present a discussion on the molecular and cellular mechanisms involved in the pathogenesis of cardiomyopathies and HF in aging and the potential involvement of specific genes identified as primary mediators of these diseases.

Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases

Background

Identification of molecular classifiers from genome-wide gene expression analysis is an important practice for the investigation of biological systems in the post-genomic era - and one with great potential for near-term clinical impact. The 'Top-Scoring Pair' (TSP) classification method identifies pairs of genes whose relative expression correlates strongly with phenotype. In this study, we sought to assess the effectiveness of the TSP approach in the identification of diagnostic classifiers for a number of human diseases including bacterial and viral infection, cardiomyopathy, diabetes, Crohn's disease, and transformed ulcerative colitis. We examined transcriptional profiles from both solid tissues and blood-borne leukocytes.

Results

The algorithm identified multiple predictive gene pairs for each phenotype, with cross-validation accuracy ranging from 70 to nearly 100 percent, and high sensitivity and specificity observed in most classification tasks. Performance compared favourably with that of pre-existing transcription-based classifiers, and in some cases was comparable to the accuracy of current clinical diagnostic procedures. Several diseases of solid tissues could be reliably diagnosed through classifiers based on the blood-borne leukocyte transcriptome. The TSP classifier thus represents a simple yet robust method to differentiate between diverse phenotypic states based on gene expression profiles.

Conclusion

Two-transcript classifiers have the potential to reliably classify diverse human diseases, through analysis of both local diseased tissue and the immunological response assayed through blood-borne leukocytes. The experimental simplicity of this method results in measurements that can be easily translated to clinical practice.