Blood Transcriptome Profiling Research Articles

Repeated administration of dapirolizumab pegol in a randomised phase I study is well tolerated and accompanied by improvements in several composite measures of systemic lupus erythematosus disease activity and changes in whole blood transcriptomic profiles

ObjectivesSystemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease associated with diffuse immune cell dysfunction. CD40–CD40 ligand (CD40L) interaction activates B cells, antigen-presenting cells and platelets. CD40L blockade might provide...

An interaction map of circulating metabolites, immune gene networks, and their genetic regulation

BackgroundImmunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up.ResultsWe identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus.ConclusionsThis study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.

Modeling Rett Syndrome Using TALEN-Edited MECP2 Mutant Cynomolgus Monkeys

Gene-editing technologies have made it feasible to create nonhuman primate models for human genetic disorders. Here, we report detailed genotypes and phenotypes of TALEN-edited MECP2 mutant cynomolgus monkeys serving as a model for a neurodevelopmental disorder, Rett syndrome (RTT), which is caused by loss-of-function mutations in the human MECP2 gene. Male mutant monkeys were embryonic lethal, reiterating that RTT is a disease of females. Through a battery of behavioral analyses, including primate-unique eye-tracking tests, in combination with brain imaging via MRI, we found a series of physiological, behavioral, and structural abnormalities resembling clinical manifestations of RTT. Moreover, blood transcriptome profiling revealed that mutant monkeys resembled RTT patients in immune gene dysregulation. Taken together, the stark similarity in phenotype and/or endophenotype between monkeys and patients suggested that gene-edited RTT founder monkeys would be of value for disease mechanistic studies as well as development of potential therapeutic interventions for RTT.

Meta-analysis of host response networks identifies a common core in tuberculosis

Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host’s whole blood transcriptomic profiles that were integrated into a genome-scale protein–protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data.

Identification of a Novel MPL Loss of Function Mutation in a Patient with Cyclic Thrombocytopenia and Characterization of This Syndrome

Introduction: Cyclic thrombocytopenia (CT) is a rare disease characterized by periodic fluctuations in platelet counts. The etiology of this disease has not been fully elucidated. Here, we present molecular characterization of CT in a 53-year-old male patient who has platelet counts ranging between 1 x 109/L to >400 x 109/L during a cycle period of 40 days which has occurred over several years.Methods: Blood transcriptome profiles and plasma cytokine levels were investigated in 24 samples that were sequentially collected every 3-4 days to cover two complete cycles. Total RNA was extracted after lysing red blood cells. 3SEQ (3′-end RNA sequencing for expression quantification) was performed for transcriptome profiling. SAMSeq quantitative analyses were conducted to identify differentially expressed genes. Three screening criteria were applied to this data set to identify a panel of exclusive platelet-specific genes. Plasma TPO (thrombopoietin)/testosterone/ estradiol/CD41a/CD42b levels were detected by ELISA. A total of 62 cytokines were screened using a luminex immunoassay. MPL (TPO receptor) gene was Sanger-sequenced using blood DNA and mRNA templates. DNA was extracted from the patient’s hair follicles to exam the presence of the identified MPL mutation, and in-silico predictions were conducted to evaluate the MPL mutation. The wild-type (WT) and c.1210G>A mutant MPL expression constructs were generated and transfected into Ba/F3 cells for stable MPL expression. TPO-stimulated, IL-3 independent growth of MPL-expressing Ba/F3 cells were assessed to determine the function of MPL proteins.Results: Plasma TPO levels cycled between 6 to 2745 pg/mL during the sampling period; TPO levels inversely mirrored the fluctuation of platelet counts and preceded the latter by 3-4 days. Additional plasma cytokines demonstrated either an inverse correlation (e.g. FasL, GM-CSF, and TNF-β, etc.), or well synchronized correlation (e.g. BDNF, PDGF-BB, and RANTES etc.), with platelet counts. The patient was negative for platelet autoantibodies. Transcriptome analysis revealed 977 genes with expression that positively correlated with platelet count changes. Unsupervised clustering stratified these genes into subgroups, including: i) platelet-specific genes, which precede platelet count changes by 3-4 days; ii) platelet-modulated genes, which follow platelet count changes and are regulated by coagulation factors (e.g. F2) and platelet-contained growth factors (e.g. PDGF-BB and EGF); and iii) neutrophil-specific genes, which precede platelet count changes by 7-10 days. Among platelet-specific genes, 34 genes were identified to have >50-fold induction over a cycle, and are present in the platelet transcriptome [Rowley JW, 2011]. A heat map of these exclusive platelet genes is shown in Figure 1A.A novel MPL c.1210G>A heterozygous mutation, which leads to a p.Gly404Arg substitution, was identified in both blood and hair follicle DNA samples of the patient. This substitution resides in a highly conserved site and is predicted to be deleterious. In addition, the mutation creates a novel splice site, which results in the insertion of a 36 bp intron fragment in approximately 15% of MPL transcripts. In vitro analysis confirmed that MPL c.1210G>A is a loss-of-function (LOF) variant. Ba/F3 cells that express WT MPL exhibited IL-3 independent growth in the presence of TPO; however, the Gly404Arg mutant failed to support TPO-stimulated growth (Figure 1B).Conclusion: We describe a patient with CT who exhibits fluctuations of multiple cytokines including an inverse correlation between TPO and platelet counts, and profound gene expression changes in neutrophil- and platelet-specific gene expressions which precede platelet count fluctuations. These data suggest that the cyclic megakaryopoiesis and thrombopoiesis underlies pathogenesis of the disease. Moreover, the identified novel LOF MPL allele may contribute to the disease pathogenesis. The biologic and molecular annotation of this case presents a unique opportunity to examine the transcriptional regulation of platelet homeostasis. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Systematic review of blood transcriptome profiling in neuropsychiatric disorders: guidelines for biomarker discovery.

The utility of blood for genome-wide gene expression profiling and biomarker discovery has received much attention in patients diagnosed with major neuropsychiatric disorders. While numerous studies have been conducted, statistical rigor and clarity in terms of blood-based biomarker discovery, validation, and testing are needed. We conducted a systematic review of the literature to investigate methodological approaches and to assess the value of blood transcriptome profiling in research on mental disorders. We were particularly interested in statistical considerations related to machine learning, gene network analyses, and convergence across different disorders. A total of 108 peripheral blood transcriptome studies across 15 disorders were surveyed: 25 studies used a variety of machine learning techniques to assess putative clinical viability of the candidate biomarkers; 11 leveraged a higher-order systems-level perspective to identify gene module-based biomarkers; and nine performed analyses across two or more neuropsychiatric phenotypes. Notably, ~50% of the surveyed studies included fewer than 50 samples (cases and controls), while ~75% included less than 100. Detailed consideration of statistical analysis in the early stages of experimental planning is critical to ensure blood-based biomarker discovery and validation. Statistical guidelines are presented to enhance implementation and reproducibility of machine learning and gene network analyses across independent studies. Future studies capitalizing on larger sample sizes and emerging next-generation technologies set the stage for moving the field forwards. Copyright © 2016 John Wiley & Sons, Ltd.

Metabolic targets of endocrine disrupting chemicals assessed by cord blood transcriptome profiling

Early life exposure to endocrine disrupting chemicals (EDCs) has been frequently associated with impaired perinatal growth, an important risk factor for later onset of metabolic disorders.We analyzed whether the cord blood transcriptome showed early indications of alterations in metabolic processes in 195 human samples in relation to cord blood levels of dichlorodiphenyldichloroethylene (p,p′-DDE), polychlorinated biphenyl-153 (PCB-153), perfluorooctanoic acid (PFOA), and perfluorooctane sulfonate (PFOS).Overall, 39 metabolically relevant transcription factors were significantly enriched (31 by p,p′-DDE, 10 by PCB-153, 8 by PFOA, and 2 by PFOS). These included the glucocorticoid receptor (p,p′-DDE and PCB-153) and the progesterone receptor (PFOA and PFOS). The ‘insulin receptor signaling’, ‘acute phase response signaling’, ‘Interleukin(IL)-6 signaling’, and ‘prolactin signaling’ pathways were significantly enriched in relation to p,p′-DDE.Transcriptional changes at birth suggest a role for specific metabolic targets as a link between prenatal EDC exposure and metabolic disorders later in life.

Whole blood transcriptional profiling comparison between different milk yield of Chinese Holstein cows using RNA-seq data.

BackgroundThe objective of this research was to investigate the variation of gene expression in the blood transcriptome profile of Chinese Holstein cows associated to the milk yield traits.ResultsWe used RNA-seq to generate the bovine transcriptome from the blood of 23 lactating Chinese Holstein cows with extremely high and low milk yield. A total of 100 differentially expressed genes (DEGs) (p < 0.05, FDR < 0.05) were revealed between the high and low groups. Gene ontology (GO) analysis demonstrated that the 100 DEGs were enriched in specific biological processes with regard to defense response, immune response, inflammatory response, icosanoid metabolic process, and fatty acid metabolic process (p < 0.05). The KEGG pathway analysis with 100 DEGs revealed that the most statistically-significant metabolic pathway was related with Toll-like receptor signaling pathway (p < 0.05). The expression level of four selected DEGs was analyzed by qRT-PCR, and the results indicated that the expression patterns were consistent with the deep sequencing results by RNA-Seq. Furthermore, alternative splicing analysis of 100 DEGs demonstrated that there were different splicing pattern between high and low yielders. The alternative 3’ splicing site was the major splicing pattern detected in high yielders. However, in low yielders the major type was exon skipping.ConclusionThis study provides a non-invasive method to identify the DEGs in cattle blood using RNA-seq for milk yield. The revealed 100 DEGs between Holstein cows with extremely high and low milk yield, and immunological pathway are likely involved in milk yield trait. Finally, this study allowed us to explore associations between immune traits and production traits related to milk production.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2901-1) contains supplementary material, which is available to authorized users.

Evaluating the Stability of RNA-Seq Transcriptome Profiles and Drug-Induced Immune-Related Expression Changes in Whole Blood.

Methods were developed to evaluate the stability of rat whole blood expression obtained from RNA sequencing (RNA-seq) and assess changes in whole blood transcriptome profiles in experiments replicated over time. Expression was measured in globin-depleted RNA extracted from the whole blood of Sprague-Dawley rats, given either saline (control) or neurotoxic doses of amphetamine (AMPH). The experiment was repeated four times (paired control and AMPH groups) over a 2-year span. The transcriptome of the control and AMPH-treated groups was evaluated on: 1) transcript levels for ribosomal protein subunits; 2) relative expression of immune-related genes; 3) stability of the control transcriptome over 2 years; and 4) stability of the effects of AMPH on immune-related genes over 2 years. All, except one, of the 70 genes that encode the 80s ribosome had levels that ranked in the top 5% of all mean expression levels. Deviations in sequencing performance led to significant changes in the ribosomal transcripts. The overall expression profile of immune-related genes and genes specific to monocytes, T-cells or B-cells were well represented and consistent within treatment groups. There were no differences between the levels of ribosomal transcripts in time-matched control and AMPH groups but significant differences in the expression of immune-related genes between control and AMPH groups. AMPH significantly increased expression of some genes related to monocytes but down-regulated those specific to T-cells. These changes were partially due to changes in the two types of leukocytes present in blood, which indicate an activation of the innate immune system by AMPH. Thus, the stability of RNA-seq whole blood transcriptome can be verified by assessing ribosomal protein subunits and immune-related gene expression. Such stability enables the pooling of samples from replicate experiments to carry out differential expression analysis with acceptable power.

Differential transcriptomic and metabolic profiles of M. africanum- and M. tuberculosis-infected patients after, but not before, drug treatment.

The epidemiology of Mycobacterium tuberculosis (Mtb) and M. africanum (Maf) suggest differences in their virulence, but the host immune profile to better understand the pathogenesis of tuberculosis (TB) have not been studied. We compared the transcriptomic and metabolic profiles between Mtb and Maf-infected TB cases to identify host biomarkers associated with lineages-specific pathogenesis and response to anti-TB chemotherapy. Venous blood samples from Mtb- and Maf-infected patients obtained before and after anti-TB treatment were analysed for cell composition, gene expression and metabolic profiles. Prior to treatment, similar transcriptomic profiles were seen in Maf- and Mtb-infected patients. In contrast, post-treatment, over 1600 genes related to immune responses and metabolic diseases were differentially expressed between the groups. Notably, the upstream regulator hepatocyte nuclear factor 4-alpha (HNF4α), which regulated 15% of these genes, was markedly enriched. Serum metabolic profiles were similar in both group pre-treatment, but the decline in pro-inflammatory metabolites post-treatment were most pronounced in Mtb-infected patients. Together, the differences in both peripheral blood transcriptomic and serum metabolic profiles between Maf- and Mtb-infected patients observed over the treatment period, might be indicative of intrinsic host factors related to susceptibility to TB and/or differential efficacy of the standard anti-TB treatment on the two lineages.

Effects of Thrombopoietin Mimetics on Patients with Chronic ITP: Perspectives from Blood Transcriptome Profiling Analysis

Introduction: Immune thrombocytopenia (ITP) is an autoimmune disorder characterized by low platelet counts due to accelerated platelet destruction and impaired platelet production. Thrombopoietin (TPO) is the major regulator of platelet production, and TPO mimetics have been approved to treat patients with ITP with a response rate around 80%. In this study, we assessed the impact of eltrombopag on patients at the RNA level and explored the biological mechanisms underlying the variations in individual responses through blood transcriptome profiling analysis.Methods: Peripheral blood specimens were collected for RNA extraction from patients with ITP at three time points: pre-treatment, one-week into treatment, and one-month into treatment. The criteria for response assessment are modified from the 2009 IWG guideline. The 3′-end RNA sequencing for expression quantification (3SEQ) was performed on 112 specimens from 37 patients. A globin-reduction approach was utilized for 77 samples with adequate RNA quantity to increase detection sensitivity. Sequencing data was mapped to human reference transcriptome to generate gene expression profiles. Using globin-reduced samples, SAMSeq analysis were conducted to identify differentially expressed genes. The pathways and upstream regulators associated with these genes were recognized using IPA (Ingenuity Pathway Analysis). With selected platelet specific genes as surrogate markers, post-treatment platelet gene expression- and platelet count-normalized platelet gene expression were compared with the pre-treatment expressions for each patient to assess platelet production and life span. In addition, the genomic coding regions of MPL (myeloproliferative leukemia virus oncogene) gene, encoding the receptor of TPO, were amplified by PCR and screened by Sanger sequencing for mutations in 10 responders and 7 nonresponders to assess for possible associations with drug responses.Results: No gene was identified as statistically significant to differentiate the responders and nonresponders at the pretreatment time point. No genetic variant within the coding regions of MPL was identified to be associated with the response to treatment. Along with the increased platelet counts at one-week into treatment, paired pretreatment and one-week into treatment analysis reveals TPO mimetics-induced upregulation of 215 genes in TPO responders (Figure 1A shows the SAM plot of SAMSeq two class paired comparison of 16 responders treated with eltrombopag at pretreatment and 1-week into treatment points, indicating a set of genes were upregulated at 1-week into treatment point. Figure 1C shows a heatmap of treatment-induced genes at baseline and after 1 week of eltrombopag treatment). On the contrary, nonresponders share no genes with statistically significant changes at one-week into treatment (Figure 1B). Interestingly, at one-month into treatment, responders show decreased expressions of the treatment-induced genes, even though the platelet counts are further elevated compared to the one-week into treatment time point. In responders, platelet gene expression was significantly increased at both one-week (p = 0.009) and one-month (p = 0.032) into treatment points, reflecting increased platelet production. Moreover, compared to the one-week into treatment time point, responders showed significantly reduced platelet count-normalized gene expression level (p = 0.033) at the one-month into treatment time point, indicating longer platelet life span and suggesting decreased platelet turnover rate. Pathway analysis identified TPO, GATA1 (GATA binding protein 1), and TGFB1 (transforming growth factor, beta1) as the top three activated upstream regulators for the treatment-induced genes.Conclusions: These results suggest that the TPO mimetics may exert dual effects in responders: stimulation of platelet production, as well as ameliorate platelet destruction, possibly involving TGFB1 pathway and regulatory T cells. [Display omitted] DisclosuresBussel:Shionogi: Research Funding; GlaxoSmithKline: Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Amgen: Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Research Funding. Zehnder:GlaxoSmithKline: Research Funding.

Whole blood gene expression profiling of neonates with confirmed bacterial sepsis.

Neonatal infection remains a primary cause of infant morbidity and mortality worldwide and yet our understanding of how human neonates respond to infection remains incomplete. Changes in host gene expression in response to infection may occur in any part of the body, with the continuous interaction between blood and tissues allowing blood cells to act as biosensors for the changes. In this study we have used whole blood transcriptome profiling to systematically identify signatures and the pathway biology underlying the pathogenesis of neonatal infection. Blood samples were collected from neonates at the first clinical signs of suspected sepsis alongside age matched healthy control subjects. Here we report a detailed description of the study design, including clinical data collected, experimental methods used and data analysis workflows and which correspond with data in Gene Expression Omnibus (GEO) data sets (GSE25504). Our data set has allowed identification of a patient invariant 52-gene classifier that predicts bacterial infection with high accuracy and lays the foundation for advancing diagnostic, prognostic and therapeutic strategies for neonatal sepsis.

Gene co-expression network analysis identifies porcine genes associated with variation in Salmonella shedding.

BackgroundSalmonella enterica serovar Typhimurium is a gram-negative bacterium that can colonise the gut of humans and several species of food producing farm animals to cause enteric or septicaemic salmonellosis. While many studies have looked into the host genetic response to Salmonella infection, relatively few have used correlation of shedding traits with gene expression patterns to identify genes whose variable expression among different individuals may be associated with differences in Salmonella clearance and resistance. Here, we aimed to identify porcine genes and gene co-expression networks that differentiate distinct responses to Salmonella challenge with respect to faecal Salmonella shedding.ResultsPeripheral blood transcriptome profiles from 16 pigs belonging to extremes of the trait of faecal Salmonella shedding counts recorded up to 20 days post-inoculation (low shedders (LS), n = 8; persistent shedders (PS), n = 8) were generated using RNA-sequencing from samples collected just before (day 0) and two days after (day 2) Salmonella inoculation. Weighted gene co-expression network analysis (WGCNA) of day 0 samples identified four modules of co-expressed genes significantly correlated with Salmonella shedding counts upon future challenge. Two of those modules consisted largely of innate immunity related genes, many of which were significantly up-regulated at day 2 post-inoculation. The connectivity at both days and the mean gene-wise expression levels at day 0 of the genes within these modules were higher in networks constructed using LS samples alone than those using PS alone. Genes within these modules include those previously reported to be involved in Salmonella resistance such as SLC11A1 (formerly NRAMP1), TLR4, CD14 and CCR1 and those for which an association with Salmonella is novel, for example, SIGLEC5, IGSF6 and TNFSF13B.ConclusionsOur analysis integrates gene co-expression network analysis, gene-trait correlations and differential expression to provide new candidate regulators of Salmonella shedding in pigs. The comparatively higher expression (also confirmed in an independent dataset) and the significantly higher connectivity of genes within the Salmonella shedding associated modules in LS compared to PS even before Salmonella challenge may be factors that contribute to the decreased faecal Salmonella shedding observed in LS following challenge.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-452) contains supplementary material, which is available to authorized users.

THU0040 Serum IFN Alpha, but not IFN Beta or IFN Omega, Correlates with IFN Signature in SLE Patients

BackgroundInterferon-α-kinoid (IFN-K) elicits a polyclonal antibody response against IFNα in humans. In a previously reported study, we found that administration of IFN-K to SLE patients induces significant changes in biological...

Whole blood gene expression and atrial fibrillation: the Framingham Heart Study.

BackgroundAtrial fibrillation (AF) involves substantial electrophysiological, structural and contractile remodeling. We hypothesize that characterizing gene expression might uncover important pathways related to AF.Methods and ResultsWe performed genome-wide whole blood transcriptomic profiling (Affymetrix Human Exon 1.0 ST Array) of 2446 participants (mean age 66±9 years, 55% women) from the Offspring cohort of Framingham Heart Study. The study included 177 participants with prevalent AF, 143 with incident AF during up to 7 years follow up, and 2126 participants with no AF. We identified seven genes statistically significantly up-regulated with prevalent AF. The most significant gene, PBX1 (P = 2.8×10−7), plays an important role in cardiovascular development. We integrated differential gene expression with gene-gene interaction information to identify several signaling pathways possibly involved in AF-related transcriptional regulation. We did not detect any statistically significant transcriptomic associations with incident AF.ConclusionWe examined associations of gene expression with AF in a large community-based cohort. Our study revealed several genes and signaling pathways that are potentially involved in AF-related transcriptional regulation.

Th17/Treg ratio derived using DNA methylation analysis discriminates allergen-induced early from dual asthmatic responses

Background Atopic allergic asthmatic individuals experience acute bronchoconstriction (early response) upon allergen exposure. Several hours after the initial exposure, some individuals exhibit a chronic late phase (dual responders, DRs) whereas others do not (early responders, ERs). The purpose of this study is to determine changes in Th17 and regulatory T (Treg) cell numbers and their associated gene expression profiles in whole blood between allergen-induced ERs and DRs. Methods 14 participants with mild, atopic asthma (8 ERs and 6 DRs) underwent a cat allergen inhalation challenge as part of the AllerGen Clinical Investigator Collaborative. Whole blood was collected immediately prior to challenge (pre) and 2 hours post-challenge. DNA methylation analysis was used to measure the frequency of Th17, Treg, B and T cells (Epiontis, Germany). Whole blood transcriptome profiling was performed using Affymetrix GeneChip ® Human Gene 1.0 ST Arrays. Statistical analysis was performed using R. Results Sum of the T cell and B cell frequencies obtained using the methylation assays strongly correlated (r = 0.95) with the lymphocyte frequency obtained using a hematolyzer. Allergen inhalation did not significantly (p>0.05) change Th17, Treg, B and T cell counts between ERs and DRs. However, the Th17/Treg ratio was significantly (p=0.03) different between ERs and DRs post challenge. 199 genes positively correlated with Th17 cells at an FDR of 5%. 463 genes positively correlated with Treg cells at an FDR of 5%. Th17 genes were inversely correlated with Treg genes. Conclusions Th17/Treg ratio derived using DNA methylation analysis discriminates allergen-induced early from dual asthmatic responses. The inverse correlation between Th17 genes and Treg genes may be indicative of the inflammatory or suppressive phenotypes of these cells.

Predicting epilepsy with peripheral blood transcriptome biomarkers during early latent period

Status epilepticus (SE) is a common cause of hippocampal neurodegeneration and synaptic reorganization that may or may not lead to the development of epilepsy. Currently there is no method to predict whether chronic epilepsy would develop in post‐SE patients. We used microarrays to analyze expression changes in the blood of two rat models of chronic epilepsy to identify prognostic peripheral biomarkers of epilepsy.Peripheral blood was collected from Adult Wistar male rats before SE and one, three, seven and thirty days after subjected to SE induced by either systemic pilocarpine or intrahippocampal kainic acid. Blood RNA was used for global transcriptome analysis using microarrays. Post‐SE animals underwent continuous monitoring to retrospectively correlate seizure syndrome with the changes in blood transcriptome profile.We identified nearly 100 predictor/biomarker genes for later occurring chronic seizures regulated similarly in both models, which were confirmed in independent groups of post‐SE rats by semi quantitative RT‐PCR and by a custom designed prognostic microarray.The molecular signature preceding the development of epilepsy present in the peripheral blood allows the design of a prognostic/diagnostic transcriptome biomarker chip for potential epilepsy patients and monitoring the effectiveness of antiepileptogenic therapy.This work was supported by NIH Grant NS060476‐01 (SLK).

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