Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood samples

RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance

Background

Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD.

Methods

Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA).

Results

The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells.

Conclusions

These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

How long does the mRNA remains stable in untreated whole bovine blood?

BACKGROUND

High quality and quantity of messenger RNA (mRNA) are required for accuracy of gene expression studies and other RNA-based downstream applications. Since RNA is considered a labile macromolecular prone to degradation, which may result in falsely altered gene expression patterns, several commercial stabilizing reagents have been developed aiming to keep RNA stable for long period. However, for studies involving large number of experimental samples, the high costs related to these specific reagents may constitute a barrier.

METHODS AND RESULTS

In this context the present study was designed aiming to evaluate the stability of mRNA in whole bovine blood collected in EDTA tubes during storage at common fridge (4 °C). Whole blood samples were collected from six Holstein calves and submitted to RNA extraction in each different interval: immediately after blood sampling (< 2 h), at 1-day post-sampling (dps), 2 dps, 3 dps, 7 dps and 14dps intervals. RNA integrity and purity were evaluated, and RT-qPCR assays were run using seven different genes (B2M, ACTB, PPIA, GAPDH, YWHAZ, CD4 and IFN-γ) aiming to evaluate the presence of altered gene transcription during storage. All extracted RNA samples presented high purity, while optimal integrity and unaltered gene expression were observed in whole experimental group up to 3 days of storage.

CONCLUSION

Bovine blood RNA remained stable in K3EDTA tubes for 3 days stored at common fridge and can be successfully and accurately used for gene expression studies.

RNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance

BACKGROUND

Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography. Surprisingly, despite well-established clinical indications, up to 40% of the one million invasive cardiac catheterizations return a result of 'no blockage'. The present studies employed RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD.

METHODS

Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by single-molecule sequencing of RNA (RNAseq) to identify transcripts associated with CAD (TRACs) in a discovery group of 96 patients presenting for elective coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs).

RESULTS

Surprisingly, 98% of DEGs/TRACs were down-regulated ~ 1.7-fold in patients with mild to severe CAD (> 20% stenosis). The TRACs were independent of comorbid risk factors for CAD, such as sex, hypertension, and smoking. Bioinformatic analysis identified an enrichment in transcripts such as FoxP1, ICOSLG, IKZF4/Eos, SMYD3, TRIM28, and TCF3/E2A that are likely markers of regulatory T cells (Treg), consistent with known reductions in Tregs in CAD. A validation cohort of 80 patients confirmed the overall pattern (92% down-regulation) and supported many of the Treg-related changes. TRACs were enriched for transcripts associated with stress granules, which sequester RNAs, and ciliary and synaptic transcripts, possibly consistent with changes in the immune synapse of developing T cells.

CONCLUSIONS

These studies identify a novel mRNA signature of a Treg-like defect in CAD patients and provides a blueprint for a diagnostic test for CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Immune monitoring in renal transplantation: The search for biomarkers

It is now widely accepted that in order to improve long-term graft function and survival, a more personalized immunosuppressive treatment of transplant patients according to the individual anti-donor immune response status is needed. This applies to the identification of potentially "high-risk" patients likely to develop acute rejection episodes or display an accelerated decline of graft function, patients who might need immunosuppression intensification, and operationally tolerant patients suitable for immunosuppression minimization or weaning off. Such a patient stratification would benefit from biomarkers, which enable categorization into low and high risk or, ideally, identification of operational tolerant patients. Here, we report on recent developments regarding identification and performance analysis of noninvasive biomarkers such as mRNA and miRNA expression profiles, chemokines, or changes in immune cell subsets in either blood or urine of renal transplant patients. We will also discuss which future steps are needed to accelerate their clinical implementation.

Assessment of Circulating Protein Signatures for Kidney Transplantation in Pediatric Recipients

Identification and use of non-invasive biomarkers for kidney transplantation monitoring is an unmet need. A total of 121 biobanked sera collected from 111 unique kidney transplant (KT) patients (children and adolescent) and 10 age-matched healthy normal controls were used to profile serum proteins using semi-quantitative proteomics. The proteomics data were analyzed to identify panels of serum proteins that were specific to various transplant injuries, which included acute rejection (AR), BK virus nephropathy (BKVN), and chronic allograft nephropathy (CAN). Gene expression data from matching peripheral blood mononuclear cells were interrogated to investigate the association between soluble serum proteins and altered gene expression of corresponding genes in different injury phenotypes. Analysis of the proteomics data identified from different patient phenotypes, with criteria of false discovery rate <0.05 and at least twofold changes in either direction, resulted in a list of 10 proteins that distinguished KT injury from no injury. Similar analyses to identify proteins specific to chronic injury, acute injury, and AR after kidney transplantation identified 22, 6, and 10 proteins, respectively. Elastic-Net logistic regression method was applied on the 137 serum proteins to classify different transplant injuries. This algorithm has identified panels of 10 serum proteins specific for AR, BKVN, and CAN with classification rates 93, 93, and 95%, respectively. The identified proteins could prove to be potential surrogate biomarkers for routine monitoring of the injury status of pediatric KT patients.

Establishing Biomarkers in Transplant Medicine: A Critical Review of Current Approaches

Although the management of kidney transplant recipients has greatly improved over recent decades, the assessment of individual risks remains highly imperfect. Individualized strategies are necessary to recognize and prevent immune complications early and to fine-tune immunosuppression, with the overall goal to improve patient and graft outcomes. This review discusses current biomarkers and their limitations, and recent advancements in the field of noninvasive biomarker discovery. A wealth of noninvasive monitoring tools has been suggested that use easily accessible biological fluids such as urine and blood, allowing frequent and sequential assessments of recipient's immune status. This includes functional cell-based assays and the evaluation of molecular expression on a wide spectrum of platforms. Nevertheless, the translation and validation of exploratory findings and their implementation into standard clinical practice remain challenging. This requires dedicated prospective interventional trials demonstrating that the use of these biomarkers avoids invasive procedures and improves patient or transplant outcomes.

Comparison of whole blood and peripheral blood mononuclear cell gene expression for evaluation of the perioperative inflammatory response in patients with advanced heart failure

BACKGROUND

Heart failure (HF) prevalence is increasing in the United States. Mechanical Circulatory Support (MCS) therapy is an option for Advanced HF (AdHF) patients. Perioperatively, multiorgan dysfunction (MOD) is linked to the effects of device implantation, augmented by preexisting HF. Early recognition of MOD allows for better diagnosis, treatment, and risk prediction. Gene expression profiling (GEP) was used to evaluate clinical phenotypes of peripheral blood mononuclear cells (PBMC) transcriptomes obtained from patients' blood samples. Whole blood (WB) samples are clinically more feasible, but their performance in comparison to PBMC samples has not been determined.

METHODS

We collected blood samples from 31 HF patients (57±15 years old) undergoing cardiothoracic surgery and 7 healthy age-matched controls, between 2010 and 2011, at a single institution. WB and PBMC samples were collected at a single timepoint postoperatively (median day 8 postoperatively) (25-75% IQR 7-14 days) and subjected to Illumina single color Human BeadChip HT12 v4 whole genome expression array analysis. The Sequential Organ Failure Assessment (SOFA) score was used to characterize the severity of MOD into low (≤ 4 points), intermediate (5-11), and high (≥ 12) risk categories correlating with GEP.

RESULTS

Results indicate that the direction of change in GEP of individuals with MOD as compared to controls is similar when determined from PBMC versus WB. The main enriched terms by Gene Ontology (GO) analysis included those involved in the inflammatory response, apoptosis, and other stress response related pathways. The data revealed 35 significant GO categories and 26 pathways overlapping between PBMC and WB. Additionally, class prediction using machine learning tools demonstrated that the subset of significant genes shared by PBMC and WB are sufficient to train as a predictor separating the SOFA groups.

CONCLUSION

GEP analysis of WB has the potential to become a clinical tool for immune-monitoring in patients with MOD.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

Background

Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood.

Methods

Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based).

Results

Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS.

Conclusions

The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols.

The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study

BACKGROUND

Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR.

METHODS AND FINDINGS

We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART) study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set--the Kidney Solid Organ Response Test (kSORT)--was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91-0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88-1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86-0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials.

CONCLUSIONS

The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants. Please see later in the article for the Editors' Summary.

Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion

Background

The molecular profile of circulating blood can reflect physiological and pathological events occurring in other tissues and organs of the body and delivers a comprehensive view of the status of the immune system. Blood has been useful in studying the pathobiology of many diseases. It is accessible and easily collected making it ideally suited to the development of diagnostic biomarker tests. The blood transcriptome has a high complement of globin RNA that could potentially saturate next-generation sequencing platforms, masking lower abundance transcripts. Methods to deplete globin mRNA are available, but their effect has not been comprehensively studied in peripheral whole blood RNA-Seq data. In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples.

Results

We compared technical and biological replicates having undergone globin depletion or not and found that the experimental globin depletion protocol employed removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Differential expression analysis revealed thousands of genes significantly up-regulated as a result of globin depletion. In addition, globin depletion resulted in the down-regulation of genes involved in both iron and zinc metal ion bonding.

Conclusions

Globin depletion appears to meaningfully improve the quality of peripheral whole blood RNA-Seq data, and may improve our ability to detect true biological variation. Some concerns remain, however. Key amongst them the significant reduction in RNA yields following globin depletion. More generally, our investigation of technical and biological variation with and without globin depletion finds that high-throughput sequencing by RNA-Seq is highly reproducible within a large dynamic range of detection and provides an accurate estimation of RNA concentration in peripheral whole blood. High-throughput sequencing is thus a promising technology for whole blood transcriptomics and biomarker discovery.

Alteration of human blood cell transcriptome in uremia

Background

End-stage renal failure is associated with profound changes in physiology and health, but the molecular causation of these pleomorphic effects termed “uremia” is poorly understood. The genomic changes of uremia were explored in a whole genome microarray case-control comparison of 95 subjects with end-stage renal failure (n = 75) or healthy controls (n = 20).

Methods

RNA was separated from blood drawn in PAXgene tubes and gene expression analyzed using Affymetrix Human Genome U133 Plus 2.0 arrays. Quality control and normalization was performed, and statistical significance determined with multiple test corrections (qFDR). Biological interpretation was aided by knowledge mining using NIH DAVID, MetaCore and PubGene

Results

Over 9,000 genes were differentially expressed in uremic subjects compared to normal controls (fold change: -5.3 to +6.8), and more than 65% were lower in uremia. Changes appeared to be regulated through key gene networks involving cMYC, SP1, P53, AP1, NFkB, HNF4 alpha, HIF1A, c-Jun, STAT1, STAT3 and CREB1. Gene set enrichment analysis showed that mRNA processing and transport, protein transport, chaperone functions, the unfolded protein response and genes involved in tumor genesis were prominently lower in uremia, while insulin-like growth factor activity, neuroactive receptor interaction, the complement system, lipoprotein metabolism and lipid transport were higher in uremia. Pathways involving cytoskeletal remodeling, the clathrin-coated endosomal pathway, T-cell receptor signaling and CD28 pathways, and many immune and biological mechanisms were significantly down-regulated, while the ubiquitin pathway and certain others were up-regulated.

Conclusions

End-stage renal failure is associated with profound changes in human gene expression which appears to be mediated through key transcription factors. Dialysis and primary kidney disease had minor effects on gene regulation, but uremia was the dominant influence in the changes observed. This data provides important insight into the changes in cellular biology and function, opportunities for biomarkers of disease progression and therapy, and potential targets for intervention in uremia.

Genome-wide comparison of two RNA-stabilizing reagents for transcriptional profiling of peripheral blood

Peripheral whole blood is relatively easily obtained for monitoring gene expression for biomarker discovery using transcriptomic platforms such as genome-wide microarrays. However, whole blood provides challenges caused by sensitivity for ex vivo incubation and overrepresentation of globin mRNAs. We compared the performance of 2 commercial whole blood preservation methods, TEMPUS (Applied Biosystems, Foster City, CA) and PAXgene (PreAnalytiX, Qiagen BD, Valencia, CA), using 2 RNA amplification protocols and high-density microarrays. Performance of commercial globin mRNA reduction protocol also was studied. Human peripheral blood samples collected with TEMPUS and PAXgene Blood RNA tubes were amplified with the RiboAmp OA 1 Round RNA Amplification Kit (Arcturus; Applied Biosystems) and the Affymetrix (Santa Clara, CA) small sample protocol. Affymetrix globin reduction protocol was applied for total RNA samples. Samples amplified with RiboAmp were hybridized on Illumina Sentrix HumanRef-8 Expression BeadChips (Illumina Inc, San Diego, CA) and subjected to statistical analyses. RiboAmp mRNA amplification did not notably amplify globin mRNA that is overrepresented in RNA isolated by both TEMPUS and PAXgene preservation. Enzymatic depletion of globin transcript reduced the quality of total RNA and is thus not recommendable. Microarray analysis showed acceptable correlation within and between the RNA preservation methods, but altogether 443 transcripts were differentially expressed between RNA samples preserved in TEMPUS and PAXgene tubes. We demonstrated that the 2 tested blood RNA-preservation methods combined with RiboAmp mRNA amplification may be used for microarray experiments without the need for a prior globin RNA reduction. However, because genes involved in immune cell functions and gene regulatory pathways were differentially expressed as a result of the technical bias between the preservation methods, they should not be used in the same analytic setting.

A peripheral blood diagnostic test for acute rejection in renal transplantation

Monitoring of renal graft status through peripheral blood (PB) rather than invasive biopsy is important as it will lessen the risk of infection and other stresses, while reducing the costs of rejection diagnosis. Blood gene biomarker panels were discovered by microarrays at a single center and subsequently validated and cross-validated by QPCR in the NIH SNSO1 randomized study from 12 US pediatric transplant programs. A total of 367 unique human PB samples, each paired with a graft biopsy for centralized, blinded phenotype classification, were analyzed (115 acute rejection (AR), 180 stable and 72 other causes of graft injury). Of the differentially expressed genes by microarray, Q-PCR analysis of a five gene-set (DUSP1, PBEF1, PSEN1, MAPK9 and NKTR) classified AR with high accuracy. A logistic regression model was built on independent training-set (n = 47) and validated on independent test-set (n = 198)samples, discriminating AR from STA with 91% sensitivity and 94% specificity and AR from all other non-AR phenotypes with 91% sensitivity and 90% specificity. The 5-gene set can diagnose AR potentially avoiding the need for invasive renal biopsy. These data support the conduct of a prospective study to validate the clinical predictive utility of this diagnostic tool.

Detection of biomarkers for hepatocellular carcinoma using a hybrid univariate gene selection methods

Background

Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC.

Results

In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes.

Conclusions

To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles.

Recent advances in biomarker discovery in solid organ transplant by proteomics

The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput 'omic' methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field.

Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals

OBJECTIVES

(1) To investigate the effects of globin mRNA depletion in detecting differential gene expression in peripheral blood and (2) to investigate changes in peripheral blood gene expression in atopic asthmatic individuals undergoing allergen inhalation challenge.

METHODS

Asthmatic subjects (20-60 years of age, with stable, mild allergic asthma, n = 9) underwent allergen inhalation challenges. All had an early asthmatic response of ≥20% fall in forced expiratory volume in 1 second. Blood was collected immediately prior to and 2 hours after allergen challenge using PAXgene tubes (n = 4) and EDTA tubes (n = 5). Aliquots of the PAXgene blood samples were subjected to globin reduction (PAX-GR). Transcriptome analysis was performed using Affymetrix GeneChip(®) Human Gene 1.0 ST arrays. Data were preprocessed using factor analysis for robust microarray summarization and analyzed using linear models for microarrays. Pathway analyses were performed using Ingenuity Pathway Analysis.

RESULTS

Globin reduction uncovered probe sets of lower abundance. However, it significantly reduced the ability to detect differentially expressed genes (DEGs) when compared to non-globin-reduced PAXgene samples (PAX-NGR). Combined transcriptional analysis of four PAX-NGR and five EDTA sample pairs identified 1595 DEGs associated with allergen inhalation challenge (false discovery rate ≤ 5%), with the top-ranked network of perturbed biological functions consisting of inflammatory response, cellular movement, and immune cell trafficking.

CONCLUSIONS

While we have demonstrated a diminished ability to detect DEGs after globin reduction, we have nevertheless identified significant changes in the peripheral blood transcriptome of people with mild asthma 2 hours after allergen inhalation challenge.

The coin toss of B cells in rejection and tolerance: danger versus defense

Transplantation is the preferred therapy for the end stage organ disease. Since the introduction of organ transplantation into medical practice in 1953 [1], significant progress has been achieved in patient and graft survival rates due to improvements in surgical techniques and more targeted immunosuppressive medications [2]. Nevertheless, current gaps in the management of the transplant patient stem from an incomplete understanding about the heterogeneity of the injury response in organ transplantation, at different rates and different time points after transplantation, as well as our inability to monitor the immunologic threshold of risk versus safety in each individual patient. Recent advances in immunology/transplantation biology with the advent of high throughput "omic" assays such as gene microarrays, proteomics, metabolomics, antibiomics, chemical genomics and functional imaging with nanoparticles, offers us unique methods to interrogate and decipher the variability and unpredictability of the immune response in organ transplantation (Fig. 1) [3]. Recent studies using these applications [3-8] have uncovered a critical and pivotal role for specific B cell lineages in organ injury [9] and organ acceptance [10,11] (Fig. 2). The availability of specific therapies against some of these defined B cell populations provides for an exciting new field of B cell targeted manipulation that can both abrogate the allospecific injury response, as well as promote allospecific graft accommodation and health.

Toward knowing the whole human: next-generation sequencing for personalized medicine

The sequencing of the human genome, combined with brilliant technical advances in microarrays and computing, opened the genomic era of personalized medicine. The next generation of genomics is now being driven by massively parallel sequencers that are effectively high definition genetic analyzers capable of sequencing an entire human genome 30-times over in approximately a week for several thousand US dollars. Likewise, these next-generation sequencers, sometimes called deep sequencers, can sequence RNA transcriptomes to render unprecedented, high definition views of transcript sequence, SNP haplotypes, rare variants, splicing, exon boundaries and RNA editing. Presently, next-generation sequencing platforms can be grouped into ‘discovery’ platforms, which provide broad sequence coverage, but require days per sample, versus ‘diagnostic’ platforms, which provide a fraction of the coverage, but require only hours for sequencing. As these technologies converge, it will be possible to sequence a human genome in a matter of hours for a few hundred US dollars. While presenting considerable technical challenges in handling the massive data generated, next-generation sequencing platforms offer unparalleled opportunities for biological insights, target discovery and clinical diagnostics to accelerate personalized medicine in the coming years.

Biomarkers in solid organ transplantation: establishing personalized transplantation medicine

Technological advances in molecular and in silico research have enabled significant progress towards personalized transplantation medicine. It is now possible to conduct comprehensive biomarker development studies of transplant organ pathologies, correlating genomic, transcriptomic and proteomic information from donor and recipient with clinical and histological phenotypes. Translation of these advances to the clinical setting will allow assessment of an individual patient's risk of allograft damage or accommodation. Transplantation biomarkers are needed for active monitoring of immunosuppression, to reduce patient morbidity, and to improve long-term allograft function and life expectancy. Here, we highlight recent pre- and post-transplantation biomarkers of acute and chronic allograft damage or adaptation, focusing on peripheral blood-based methodologies for non-invasive application. We then critically discuss current findings with respect to their future application in routine clinical transplantation medicine. Complement-system-associated SNPs present potential biomarkers that may be used to indicate the baseline risk for allograft damage prior to transplantation. The detection of antibodies against novel, non-HLA, MICA antigens, and the expression of cytokine genes and proteins and cytotoxicity-related genes have been correlated with allograft damage and are potential post-transplantation biomarkers indicating allograft damage at the molecular level, although these do not have clinical relevance yet. Several multi-gene expression-based biomarker panels have been identified that accurately predicted graft accommodation in liver transplant recipients and may be developed into a predictive biomarker assay.

Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals

Blood is an ideal tissue for the identification of novel genomic biomarkers for toxicity or efficacy. However, using blood for transcriptomic profiling presents significant technical challenges due to the transcriptomic changes induced by ex vivo handling and the interference of highly abundant globin mRNA. Most whole blood RNA stabilization and isolation methods also require significant volumes of blood, limiting their effective use in small animal species, such as rodents. To overcome these challenges, a QIAzol-based RNA stabilization and isolation method (QSI) was developed to isolate sufficient amounts of high quality total RNA from 25 to 500 μL of rat whole blood. The method was compared to the standard PAXgene Blood RNA System using blood collected from rats exposed to saline or lipopolysaccharide (LPS). The QSI method yielded an average of 54 ng total RNA per μL of rat whole blood with an average RNA Integrity Number (RIN) of 9, a performance comparable with the standard PAXgene method. Total RNA samples were further processed using the NuGEN Ovation Whole Blood Solution system and cDNA was hybridized to Affymetrix Rat Genome 230 2.0 Arrays. The microarray QC parameters using RNA isolated with the QSI method were within the acceptable range for microarray analysis. The transcriptomic profiles were highly correlated with those using RNA isolated with the PAXgene method and were consistent with expected LPS-induced inflammatory responses. The present study demonstrated that the QSI method coupled with NuGEN Ovation Whole Blood Solution system is cost-effective and particularly suitable for transcriptomic profiling of minimal volumes of whole blood, typical of those obtained with small animal species.

Global gene expression analysis of human erythroid progenitors

Understanding the pattern of gene expression during erythropoiesis is crucial for a synthesis of erythroid developmental biology. Here, we isolated 4 distinct populations at successive erythropoietin-dependent stages of erythropoiesis, including the terminal, pyknotic stage. The transcriptome was determined using Affymetrix arrays. First, we demonstrated the importance of using defined cell populations to identify lineage and temporally specific patterns of gene expression. Cells sorted by surface expression profile not only express significantly fewer genes than unsorted cells but also demonstrate significantly greater differences in the expression levels of particular genes between stages than unsorted cells. Second, using standard software, we identified more than 1000 transcripts not previously observed to be differentially expressed during erythroid maturation, 13 of which are highly significantly terminally regulated, including RFXAP and SMARCA4. Third, using matched filtering, we identified 12 transcripts not previously reported to be continuously up-regulated in maturing human primary erythroblasts. Finally, using transcription factor binding site analysis, we identified potential transcription factors that may regulate gene expression during terminal erythropoiesis. Our stringent lists of differentially regulated and continuously expressed transcripts containing many genes with undiscovered functions in erythroblasts are a resource for future functional studies of erythropoiesis. Our Human Erythroid Maturation database is available at https://cellline.molbiol.ox.ac.uk/eryth/index.html. [corrected].

cDNA targets improve whole blood gene expression profiling and enhance detection of pharmocodynamic biomarkers: a quantitative platform analysis

Background

Genome-wide gene expression profiling of whole blood is an attractive method for discovery of biomarkers due to its non-invasiveness, simple clinical site processing and rich biological content. Except for a few successes, this technology has not yet matured enough to reach its full potential of identifying biomarkers useful for clinical prognostic and diagnostic applications or in monitoring patient response to therapeutic intervention. A variety of technical problems have hampered efforts to utilize this technology for identification of biomarkers. One significant hurdle has been the high and variable concentrations of globin transcripts in whole blood total RNA potentially resulting in non-specific probe binding and high background. In this study, we investigated and quantified the power of three whole blood profiling approaches to detect meaningful biological expression patterns.

Methods

To compare and quantify the impact of different mitigation technologies, we used a globin transcript spike-in strategy to synthetically generate a globin-induced signature and then mitigate it with the three different technologies. Biological differences, in globin transcript spiked samples, were modeled by supplementing with either 1% of liver or 1% brain total RNA. In order to demonstrate the biological utility of a robust globin artifact mitigation strategy in biomarker discovery, we treated whole blood ex vivo with suberoylanilide hydroxamic acid (SAHA) and compared the overlap between the obtained signatures and signatures of a known biomarker derived from SAHA-treated cell lines and PBMCs of SAHA-treated patients.

Results

We found cDNA hybridization targets detect at least 20 times more specific differentially expressed signatures (2597) between 1% liver and 1% brain in globin-supplemented samples than the PNA (117) or no treatment (97) method at FDR = 10% and p-value < 3x10-3. In addition, we found that the ex vivo derived gene expression profile was highly concordant with that of the previously identified SAHA pharmacodynamic biomarkers.

Conclusions

We conclude that an amplification method for gene expression profiling employing cDNA targets effectively mitigates the negative impact on data of abundant globin transcripts and greatly improves the ability to identify relevant gene expression based pharmacodynamic biomarkers from whole blood.

Molecular diagnostics in transplantation

The past few decades are characterized by an explosive evolution of genetics and molecular cell biology. Advances in chemistry and engineering have enabled increased data throughput, permitting the study of complete sets of molecules with increasing speed and accuracy using techniques such as genomics, transcriptomics, proteomics, and metabolomics. Prediction of long-term outcomes in transplantation is hampered by the absence of sufficiently robust biomarkers and a lack of adequate insight into the mechanisms of acute and chronic alloimmune injury and the adaptive mechanisms of immunological quiescence that may support transplantation tolerance. Here, we discuss some of the great opportunities that molecular diagnostic tools have to offer both basic scientists and translational researchers for bench-to-bedside clinical application in transplantation medicine, with special focus on genomics and genome-wide association studies, epigenetics (DNA methylation and histone modifications), gene expression studies and transcriptomics (including microRNA and small interfering RNA studies), proteomics and peptidomics, antibodyomics, metabolomics, chemical genomics and functional imaging with nanoparticles. We address the challenges and opportunities associated with the newer high-throughput sequencing technologies, especially in the field of bioinformatics and biostatistics, and demonstrate the importance of integrative approaches. Although this Review focuses on transplantation research and clinical transplantation, the concepts addressed are valid for all translational research.

A genomic approach to human autoimmune diseases

The past decade has seen an explosion in the use of DNA-based microarrays. These techniques permit assessment of RNA abundance on a genome-wide scale. Medical applications emerged in the field of cancer, with studies of both solid tumors and hematological malignancies leading to the development of tests that are now used to personalize therapeutic options. Microarrays have also been used to analyze the blood transcriptome in a wide range of diseases. In human autoimmune diseases, these studies are showing potential for identifying therapeutic targets as well as biomarkers for diagnosis, assessment of disease activity, and response to treatment. More quantitative and sensitive high-throughput RNA profiling methods are starting to be available and will be necessary for transcriptome analyses to become routine tests in the clinical setting. We expect this to crystallize within the coming decade, as these methods become part of the personalized medicine armamentarium.

Deconvoluting the 'omics' for organ transplantation

PURPOSE OF REVIEW

The desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. This article reviews some recent applications of the many evolving 'omic technologies to organ transplantation.

RECENT FINDINGS

With the advancement of many high-throughput 'omic techniques such as genomics, metabolomics, antibiomics, peptidomics, and proteomics, efforts have been made to understand potential mechanisms of specific graft injuries and develop novel biomarkers for acute rejection, chronic rejection, and operational tolerance.

SUMMARY

The translation of potential biomarkers from the laboratory bench to the clinical bedside is not an easy task and will require the concerted effort of the immunologists, molecular biologists, transplantation specialists, geneticists, and experts in bioinformatics. Rigorous prospective validation studies will be needed using large sets of independent patient samples. The appropriate and timely exploitation of evolving 'omic technologies will lay the cornerstone for a new age of translational research for organ transplant monitoring.

Deciphering normal blood gene expression variation--The NOWAC postgenome study

There is growing evidence that gene expression profiling of peripheral blood cells is a valuable tool for assessing gene signatures related to exposure, drug-response, or disease. However, the true promise of this approach can not be estimated until the scientific community has robust baseline data describing variation in gene expression patterns in normal individuals. Using a large representative sample set of postmenopausal women (N = 286) in the Norwegian Women and Cancer (NOWAC) postgenome study, we investigated variability of whole blood gene expression in the general population. In particular, we examined changes in blood gene expression caused by technical variability, normal inter-individual differences, and exposure variables at proportions and levels relevant to real-life situations. We observe that the overall changes in gene expression are subtle, implying the need for careful analytic approaches of the data. In particular, technical variability may not be ignored and subsequent adjustments must be considered in any analysis. Many new candidate genes were identified that are differentially expressed according to inter-individual (i.e. fasting, BMI) and exposure (i.e. smoking) factors, thus establishing that these effects are mirrored in blood. By focusing on the biological implications instead of directly comparing gene lists from several related studies in the literature, our analytic approach was able to identify significant similarities and effects consistent across these reports. This establishes the feasibility of blood gene expression profiling, if they are predicated upon careful experimental design and analysis in order to minimize confounding signals, artifacts of sample preparation and processing, and inter-individual differences.

As a major defence and transport system, blood cells are capable of adjusting gene expression in response to various clinical, biochemical, and pathological conditions. Here, we expand our understanding about the nature and extent of variation in gene expression from blood among healthy individuals. Using a large representative sample of postmenopausal women (N = 286) in the Norwegian Women and Cancer (NOWAC) postgenome study, we investigated blood gene expression changes due to normal inter-individuality (age, body mass index, fasting status), and exposure variables (smoking, hormone therapy, and medication use) at proportions and levels found in real life situations. Host genes were found to vary by inter-individual (i.e. fasting, BMI) and exposure (i.e. smoking) factors, and these gene lists may be used as a basis for further hypothesis development. Our study also establishes the feasibility of blood gene expression profiling for disease prediction, diagnosis, or prognosis, but underscores the necessity of care in study design and analysis to account for inter-individual differences and confounding signals.

Noninvasive diagnosis of acute rejection of renal allografts

PURPOSE OF REVIEW

Acute rejection is an immune process that begins with the recognition of the allograft as nonself and ends in graft destruction. Histological features of the allograft biopsy are currently used for the differential diagnosis of allograft dysfunction. In view of the safety and the opportunity for repetitive sampling, development of noninvasive biomarkers of allograft status is an important objective in transplantation. Herein, we review some of the progress towards the development of noninvasive biomarkers of human allograft status.

RECENT FINDINGS

Urinary cell and peripheral blood cell mRNA profiles have been associated with acute rejection of human renal allografts. Emerging data support the idea that development of noninvasive biomarkers predictive of antibody-mediated rejection is feasible. The demonstration that intragraft microRNA expression predicts renal allograft status suggests that noninvasively ascertained microRNA profiles may be of value.

SUMMARY

We are pleased with the progress to date, and anticipate clinical trials investigating the hypotheses that noninvasively ascertained mRNA profiles will minimize the need for invasive biopsy procedures, predict the development of acute rejection and chronic allograft nephropathy, facilitate preemptive therapy capable of preserving graft function, and facilitate personalization of immunosuppressive therapy for the allograft recipient.

Interpreting the proteome and peptidome in transplantation

Publication of the human proteome has prompted efforts to develop high-throughput techniques that can catalogue and quantify proteins and peptides present in different tissue types. The field of proteomics aims to identify, quantify, analyze, and functionally define a large number of proteins in cellular processes in different disease states on a global scale. Peptidomics, a newer name in the -omics world, measures and identifies naturally occurring low molecular weight peptides, also providing an insight into enzymatic processes and molecular events occurring in the system of interest. One area of major interest is the use of proteomics to identify diagnostic and prognostic biomarkers for different diseases as well as for various clinical phenotypes in organ transplantation that can advance targeted therapy for various forms of graft injury. Outcomes in organ transplantation can be potentially improved by identifying noninvasive biomarkers that will serve as triggers that predate graft injury, and can offer a means to customize patient treatment by differentiating among causes of acute and chronic graft injury. Proteomic and peptidomic strategies can be harnessed for frequent noninvasive measurements in tissue fluids, allowing for serial monitoring of organ disease. In this review, we describe the basic techniques used in proteomic and peptidomic approaches, point out special considerations in using these methods, and discuss their applications in recently published studies in organ transplantation.

Using gene arrays in diagnosis of rejection

PURPOSE OF REVIEW

In the last decade, microarray technology has revolutionized biological research by allowing the screening of tens of thousands of genes simultaneously. This article reviews recent studies in organ transplantation using microarrays and highlights the issues that should be addressed in order to use microarrays in diagnosis of rejection.

RECENT FINDINGS

Microarrays have been useful in identifying potential biomarkers for chronic rejection in peripheral blood mononuclear cells, novel pathways for induction of tolerance, and genes involved in protecting the graft from the host immune system. Microarray analysis of peripheral blood mononuclear cells from chronic antibody-mediated rejection has identified potential noninvasive biomarkers. In a recent study, correlation of pathogenesis-based transcripts with histopathologic lesions is a promising step towards inclusion of microarrays in clinics for organ transplants.

SUMMARY

Despite promising results in diagnosis of histopathologic lesions using microarrays, the low dynamic range of microarrays and large measured expression changes within the probes for the same gene continue to cast doubts on their readiness for diagnosis of rejection. More studies must be performed to resolve these issues. Dominating expression of globin genes in whole blood poses another challenge for identification of noninvasive biomarkers. In addition, studies are also needed to demonstrate effects of different immunosuppression therapies and their outcomes.

In praise of arrays

Microarray technologies have both fascinated and frustrated the transplant community since their introduction roughly a decade ago. Fascination arose from the possibility offered by the technology to gain a profound insight into the cellular response to immunogenic injury and the potential that this genomic signature would be indicative of the biological mechanism by which that stress was induced. Frustrations have arisen primarily from technical factors such as data variance, the requirement for the application of advanced statistical and mathematical analyses, and difficulties associated with actually recognizing signature gene-expression patterns and discerning mechanisms. To aid the understanding of this powerful tool, its versatility, and how it is dramatically changing the molecular approach to biomedical and clinical research, this teaching review describes the technology and its applications, as well as the limitations and evolution of microarrays, in the field of organ transplantation. Finally, it calls upon the attention of the transplant community to integrate into multidisciplinary teams, to take advantage of this technology and its expanding applications in unraveling the complex injury circuits that currently limit transplant survival.

The proteogenomic path towards biomarker discovery

The desire for biomarkers for diagnosis and prognosis of diseases has never been greater. With the availability of genome data and an increased availability of proteome data, the discovery of biomarkers has become increasingly feasible. However, the task is daunting and requires collaborations among researchers working in the fields of transplantation, immunology, genetics, molecular biology, biostatistics and bioinformatics. With the advancement of high throughput omic techniques such as genomics and proteomics (collectively known as proteogenomics), efforts have been made to develop diagnostic tools from new and to-be discovered biomarkers. Yet biomarker validation, particularly in organ transplantation, remains challenging because of the lack of a true gold standard for diagnostic categories and analytical bottlenecks that face high-throughput data deconvolution. Even though microarray technique is relatively mature, proteomics is still growing with regards to data normalization and analysis methods. Study design, sample selection and rigorous data analysis are the critical issues for biomarker discovery using high-throughput proteogenomic technologies that combine the use and strengths of both genomics and proteomics. In this review, we look into the current status and latest developments in the field of biomarker discovery using genomics and proteomics related to organ transplantation, with an emphasis on the evolution of proteomic technologies.

Hematopoietic Lineage Transcriptome Stability and Representation in PAXgene Collected Peripheral Blood Utilising SPIA Single-Stranded cDNA Probes for Microarray

Peripheral blood as a surrogate tissue for transcriptome profiling holds great promise for the discovery of diagnostic and prognostic disease biomarkers, particularly when target tissues of disease are not readily available. To maximize the reliability of gene expression data generated from clinical blood samples, both the sample collection and the microarray probe generation methods should be optimized to provide stabilized, reproducible and representative gene expression profiles faithfully representing the transcriptional profiles of the constituent blood cell types present in the circulation. Given the increasing innovation in this field in recent years, we investigated a combination of methodological advances in both RNA stabilisation and microarray probe generation with the goal of achieving robust, reliable and representative transcriptional profiles from whole blood. To assess the whole blood profiles, the transcriptomes of purified blood cell types were measured and compared with the global transcriptomes measured in whole blood. The results demonstrate that a combination of PAXgene() RNA stabilising technology and single-stranded cDNA probe generation afforded by the NuGEN Ovation RNA amplification system V2() enables an approach that yields faithful representation of specific hematopoietic cell lineage transcriptomes in whole blood without the necessity for prior sample fractionation, cell enrichment or globin reduction. Storage stability assessments of the PAXgene() blood samples also advocate a short, fixed room temperature storage time for all PAXgene() blood samples collected for the purposes of global transcriptional profiling in clinical studies.

Gene expression analyses in breast cancer epidemiology: the Norwegian Women and Cancer postgenome cohort study

Introduction

The introduction of high-throughput technologies, also called -omics technologies, into epidemiology has raised the need for high-quality observational studies to reduce several sources of error and bias.

Methods

The Norwegian Women and Cancer (NOWAC) postgenome cohort study consists of approximately 50,000 women born between 1943 and 1957 who gave blood samples between 2003 and 2006 and filled out a two-page questionnaire. Blood was collected in such a way that RNA is preserved and can be used for gene expression analyses. The women are part of the NOWAC study consisting of 172,471 women 30 to 70 years of age at recruitment from 1991 to 2006 who answered one to three questionnaires on diet, medication use, and lifestyle. In collaboration with the Norwegian Breast Cancer Group, every NOWAC participant born between 1943 and 1957 who is admitted to a collaborating hospital for a diagnostic biopsy or for surgery of breast cancer will be asked to donate a tumor biopsy and two blood samples. In parallel, at least three controls are approached for each breast cancer case in order to obtain blood samples from at least two controls per case. The controls are drawn at random from NOWAC matched by time of follow-up and age. In addition, 400 normal breast tissues as well as blood samples will be collected among healthy women participating at the Norwegian Mammography Screening program at the Breast Imaging Center at the University Hospital of North-Norway, Tromsø.

Results

The NOWAC postgenome cohort offers a unique opportunity (a) to study blood-derived gene expression profiles as a diagnostic test for breast cancer in a nested case-control design with adjustment for confounding factors related to different exposures, (b) to improve the reliability and accuracy of this approach by adjusting for an individual's genotype (for example, variants in genes coding for hormone and drug-metabolizing and detoxifying enzymes), (c) to study gene expression profiles from peripheral blood as surrogate tissue to biomonitor defined exposure (for example, hormone) and its association with disease risk (that is, breast cancer), and (d) to study gene variants (single nucleotide polymorphisms and copy number variations) and environmental exposure (endogenous and exogenous hormones) and their influence on the incidence of different molecular subtypes of breast cancer.

Conclusion

The NOWAC postgenome cohort combining a valid epidemiological approach with richness of biological samples should make an important contribution to the study of the etiology and system biology of breast cancer.