Peripheral Blood Gene Expression Analysis Research Articles

Predictive signature of murine and human host response to typical and atypical pneumonia

BackgroundPneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection.MethodsWe used...

Use of peripheral blood transcriptomic biomarkers to distinguish high-grade cervical squamous intraepithelial lesions from low-grade lesions.

It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the ‘Rho GTPase cycle’, ‘mitochondrial protein import’, ‘oncogenic MAPK signaling’, ‘integrin cell surface interaction’ and ‘signaling by BRAF and RAF fusions’. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

A host gene expression approach for identifying triggers of asthma exacerbations.

RationaleAsthma exacerbations often occur due to infectious triggers, but determining whether infection is present and whether it is bacterial or viral remains clinically challenging. A diagnostic strategy that clarifies these uncertainties could enable personalized asthma treatment and mitigate antibiotic overuse.ObjectivesTo explore the performance of validated peripheral blood gene expression signatures in discriminating bacterial, viral, and noninfectious triggers in subjects with asthma exacerbations.MethodsSubjects with suspected asthma exacerbations of various etiologies were retrospectively selected for peripheral blood gene expression analysis from a pool of subjects previously enrolled in emergency departments with acute respiratory illness. RT-PCR quantified 87 gene targets, selected from microarray-based studies, followed by logistic regression modeling to define bacterial, viral, or noninfectious class. The model-predicted class was compared to clinical adjudication and procalcitonin.ResultsOf 46 subjects enrolled, 7 were clinically adjudicated as bacterial, 18 as viral, and 21 as noninfectious. Model prediction was congruent with clinical adjudication in 15/18 viral and 13/21 noninfectious cases, but only 1/7 bacterial cases. None of the adjudicated bacterial cases had confirmatory microbiology; the precise etiology in this group was uncertain. Procalcitonin classified only one subject in the cohort as bacterial. 47.8% of subjects received antibiotics.ConclusionsOur model classified asthma exacerbations by the underlying bacterial, viral, and noninfectious host response. Compared to clinical adjudication, the majority of discordances occurred in the bacterial group, due to either imperfect adjudication or model misclassification. Bacterial infection was identified infrequently by all classification schemes, but nearly half of subjects were prescribed antibiotics. A gene expression-based approach may offer useful diagnostic information in this population and guide appropriate antibiotic use.

Expression profiling elucidates a molecular gene signature for pulmonary hypertension in sarcoidosis.

Pulmonary hypertension (PH), when it complicates sarcoidosis, carries a poor prognosis, in part because it is difficult to detect early in patients with worsening respiratory symptoms. Pathogenesis of sarcoidosis occurs via incompletely characterized mechanisms that are distinct from the mechanisms of pulmonary vascular remodeling well known to occur in conjunction with other chronic lung diseases. To address the need for a biomarker to aid in early detection as well as the gap in knowledge regarding the mechanisms of PH in sarcoidosis, we used genome-wide peripheral blood gene expression analysis and identified an 18-gene signature capable of distinguishing sarcoidosis patients with PH (n = 8), sarcoidosis patients without PH (n = 17), and healthy controls (n = 45). The discriminative accuracy of this 18-gene signature was 100% in separating sarcoidosis patients with PH from those without it. If validated in a large replicate cohort, this signature could potentially be used as a diagnostic molecular biomarker for sarcoidosis-associated PH.

Host-Based Peripheral Blood Gene Expression Analysis for Diagnosis of Infectious Diseases

Emerging pandemic infectious threats, inappropriate antibacterial use contributing to multidrug resistance, and increased morbidity and mortality from diagnostic delays all contribute to a need for improved diagnostics in the field of infectious diseases. Historically, diagnosis of infectious diseases has relied on pathogen detection; however, a novel concept to improve diagnostics in infectious diseases relies instead on the detection of changes in patterns of gene expression in circulating white blood cells in response to infection. Alterations in peripheral blood gene expression in the infected state are robust and reproducible, yielding diagnostic and prognostic information to help facilitate patient treatment decisions.

Reactive Oxygen Species–Associated Molecular Signature Predicts Survival in Patients with Sepsis

Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)-associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies.

Peripheral blood gene expression analysis implicates B lymphocyte proliferation and ribosomal S26 transcripts in cognitive dysfunction in people with remitted Major Depression

Residual impairments in cognitive domains including attention, memory, executive function, and social perception occur in about 40% of patients with Major Depressive Disorder (MDD) following remission from acute episodes (Conradi et al., 2011), and are associated with reductions in pre-morbid functioning and higher unemployment rates (Baune et al., 2010; Evans et al., 2014). Cognitive impairment in MDD may represent a trait marker, trait-byillness interaction marker, or endophenotype of MDD that is independent of the acute depressive state and particularly active in a subgroup of MDD patients (Hasler et al., 2004; Iverson et al., 2011). We explored the potential molecular underpinnings of such a ‘cognitive’ MDD phenotype in a well-matched pilot sample of remitted MDD patients with poorer versus better performance on cognitive testing. Because the phenotype is likely highly complex, polygenic, and heterogeneous, we performed weighted gene coexpression network analysis (WGCNA), a hypothesis-free systems biology approach that identifies ‘modules’ of co-regulated – and therefore functionally related – genes in transcriptomic datasets. After constructing a gene co-expression network from samples of all patients, we determined whether modules were correlated with poorer versus better cognitive performance. We additionally explored whether modules were also correlated with a continuous measure of cognitive performance in both groups. We utilized whole blood transcriptomic data from remitted MDD patients from the Adelaide Cognitive Function and Mood Study (CoFaMS, HREC RAH protocol no. 111230g) matched for race, gender, age, Hamilton Depression Scale score, presence of psychotic features during any depressive episode, educational status, annual household income, current drugand alcohol use, and

Peripheral Blood Gene Expression Analysis in Biopsy Proven Clinical and Subclinical Chronic Antibody Mediated Rejection After Renal Transplantation: Analysis of Treg, Breg and Anergy Related Biomarkers.

Peripheral Blood Gene Expression Analysis in Biopsy Proven Clinical and Subclinical Chronic Antibody Mediated Rejection After Renal Transplantation: Analysis of Treg, Breg and Anergy Related Biomarkers.

Peripheral Blood Gene Expression Analysis in Small Bowel Transplantation: a Pilot Study to Detect Novel Biomarkers of Graft Rejection

Introduction: Long term survival of intestinal transplant patients is hampered by rejection episodes. Currently protocol endoscopy of the graft and biopsies are the only way to predict a rejection episode. Symptoms and clinical findings frequently appear when injury to the graft is irreversible. In this report we present our initial data of putative candidate biomarkers of graft rejection in peripheral blood of intestinal transplant patients. Materials and methods: Gene expression analysis was performed in peripheral blood of intestinal transplant patients. The results were matched with concurrent graft biopsies using bioinformatics. Peripheral blood samples of intestinal transplant patients were collected in Tempus Blood RNA tubes. Concurrent graft endoscopies were performed and graft biopsies were obtained at the time of the blood samples, to match the results of the gene expression analysis with the state of the graft. Whole genome microarray analysis using the Illumina-HT12 Expression beadchip microarray was performed. The gene expression levels in patient samples were compared to those in a pool of healthy volunteers. Bioinformatics analysis was performed using the MetaCore 6.3 software from GeneGo Inc. and the Pathway Studio 7.1 software from Ariadne Genomics. Results: Peripheral blood samples (n=11), of 3 adult patients [transplant day (n=1), no rejection (n=1), minimal rejection (n=2), mild rejection (n=5) and severe rejection (n=2)] were collected. Bioinformatics: Enrichment Analysis: The three most affected pathways differentially expressed in rejection versus a pool of healthy volunteers were related to protein translation: translation initiation, translation elongation termination, and translation in mitochondria, with p-values for all rejection stages in all patients in the 10-4 to 10-18 range. No significant enrichment was observed for these categories in the day of transplant sample. In addition to translation, significant enrichment of several immune response categories was observed in rejection samples. Subsequent gene set enrichment analysis verified these results. The level of enrichment was very high (p-values of 10-5 - 10-60) and increased with the level of rejection in all patients. Genes significantly down-regulated in translation related gene sets included ribosomal proteins RPL13A, RP L22, RPS23, RPL13 and RPL10A, that could be used as potential biomarkers for future experiments. These results were further verified with the use of additional samples of 2 more small bowel transplant patients. Conclusion: In this pilot study we found a list of genes (involved in translation) significantly down-regulated in the peripheral blood of intestinal transplant patients during rejection. Our hypothesis, derived from this project, is that down-regulation of translation in peripheral blood mononuclear cells occurs early during the course of rejection and persists and progresses with the severity of the rejection episode as determined by concurrent graft biopsies.

Peripheral Blood Gene Expression as a Novel Genomic Biomarker in Complicated Sarcoidosis

Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ∼20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis). Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated) sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39) from healthy controls (n = 35, 86% classification accuracy) and which served as a molecular signature for complicated sarcoidosis (n = 17). As aberrancies in T cell receptor (TCR) signaling, JAK-STAT (JS) signaling, and cytokine-cytokine receptor (CCR) signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR) was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs) in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1). In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis.

Peripheral Blood Gene Expression Analysis in Intestinal Transplantation: A Feasibility Study for Detecting Novel Candidate Biomarkers of Graft Rejection

We investigated the putative candidate biomarkers of graft rejection in peripheral blood of intestinal transplant patients. Peripheral blood gene expression analysis was performed in intestinal transplant patients. The results were matched with concurrent graft biopsies using bioinformatics. Peripheral blood samples (n=11), of 3 adult patients [transplant day (n=1), no rejection (n=1), minimal rejection (n=2), mild rejection (n=5) and severe rejection (n=2)] were collected. Bioinformatics: Enrichment Analysis: The three most affected pathways differentially expressed in rejection versus a pool of healthy volunteers were related to protein translation: translation initiation, translation elongation termination, and translation in mitochondria, with p-values for all rejection stages in all patients in the 10-4 to 10-18 range. No significant enrichment was observed for these categories in the day of transplant sample. In addition to translation, significant enrichment of several immune response categories was observed in rejection samples. Subsequent gene set enrichment analysis verified these results. The level of enrichment was very high (p-values of 10-5-10-60) and increased with the level of rejection in all patients. Genes significantly down-regulated in translation related gene sets included ribosomal proteins RPL13A, RP L22, RPS23, RPL13 and RPL10A, that could be used as potential biomarkers for future experiments. In this pilot study we found a list of genes (involved in translation) significantly downregulated in the peripheral blood of three intestinal transplant patients during rejection. These results will be verified in further studies with increased number of patients and with isolation of peripheral blood subpopulations.

Sensitive and Quantitative Measurement of Gene Expression Directly from Peripheral Whole Blood, without RNA Isolation and Target Amplification.

Peripheral blood gene expression analysis is increasingly used for diagnosis and prognosis of hematological diseases, as well as for surrogate biomarker discovery in a wide range of non-hematological disorders. However, a critical issue concerning the potential clinical application of these research findings relates to the validity and reproducibility of the blood mRNA quantitation results. Current gene expression technologies often depend on multiple steps: 1) blood isolation; 2) RNA purification and 3) subsequent enzymatic reactions, which affect the accuracy and consistency of results. We describe an assay to measure single- and multi-plexed gene expression directly from whole blood without RNA purification and target amplification. The hybridization-based assay uses branched DNA signal amplification technology with a whole blood lysis protocol that preserves the RNA integrity. The assay is sensitive enough to quantitatively measure genes expressed at low levels in a minority of cells from less than 30ul of whole blood. The coefficients of variations are less than 10% and the dynamic range is 3–4 logs for both singleplex and multiplex formats. The assay signals are several times higher than purified RNA from an equivalent amount of blood. Blood proteins, genomic DNA and reticulocyte mRNAs do not interfere with the assay. The assays are compatible with common anticoagulants and Paxgene treated samples. However, we found the Paxgene induced expression of antiapoptotic genes during processing of the whole blood. We used the multiplex assay to evaluate the impact of common blood processing on the expression of a panel of 30 cytokine and apoptosis genes known to be sensitive to ex vivo purtabation. Minimal impact was found with RBC lysis, followed by whole blood RNA extraction, PBMC isolation and Paxgene stabilization. The lowest correlation of expression was found between RNA extracted from whole blood and RNA extracted from same blood treated with Paxgene (R square=0.77). We believe this assay will contribute to fundamental and therapeutic applications where quantitative gene expression and/or throughput are required.