Whole Blood Transcriptome Analysis in Children with Sickle Cell Anemia

Whole transcriptome RNA-sequencing was performed to quantify RNA expression changes in whole blood samples collected from steady state sickle cell anemia (SCA) and control subjects. Pediatric SCA and control subjects were recruited from Atlanta (GA)—based hospital(s) systems and consented for RNA sequencing. RNA sequencing was performed on an Ion Torrent S5 sequencer, using the Ion Total RNA-seq v2 protocol. Data were aligned to the hg19 reference genome and analyzed in the Partek Genomics studio package (v7.0). 223 genes were differentially expressed between SCA and controls (± 1.5 fold change FDR p < 0.001) and 441 genes show differential transcript expression (± 1.5 fold FDR p < 0.001). Differentially expressed RNA are enriched for hemoglobin associated genes and ubiquitin-proteasome pathway genes. Further analysis shows higher gamma globin gene expression in SCA (33-fold HBG1 and 49-fold HBG2, both FDR p < 0.05), which did not correlate with hemoglobin F protein levels. eQTL analysis identified SNPs in novel non-coding RNA RYR2 gene as having a potential regulatory role in HBG1 and HBG2 expression levels. Gene expression correlation identified JHDM1D-AS1(KDM7A-DT), a non-coding RNA associated with angiogenesis, enhanced GATA1 and decreased JAK-STAT signaling to correlate with HBG1 and HBG2 mRNA levels. These data suggest novel regulatory mechanisms for fetal hemoglobin regulation, which may offer innovative therapeutic approaches for SCA.

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Whole blood RNA sequencing reveals a differential transcriptomic profile associated with cervical insufficiency: a pilot study

Reproductive Biology and Endocrinology ◽

10.1186/s12958-021-00715-2 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Ga-Hyun Son ◽

So Yeon Choi ◽

Yeon-Ji Ju ◽

Keun-Young Lee ◽

Jae Jun Lee ◽

...

Keyword(s):

Gene Expression ◽

Rna Sequencing ◽

Differentially Expressed Genes ◽

Pregnancy Outcomes ◽

Whole Blood ◽

Differentially Expressed ◽

Cervical Insufficiency ◽

Transcriptomic Profile ◽

Extremely Preterm ◽

And Control

Abstract Background The uterine cervix is a mechanical and immunological barrier against ascending infection during pregnancy. Cervical insufficiency (CI), a painless cervical dilation that occurs in the mid-trimester, is an important cause of extremely preterm birth. We hypothesized that women with CI have a differential transcriptomic profile. Therefore, we compared the transcriptomic profile of peripheral blood in women with CI and that of controls. Methods RNA sequencing was used to generate the global gene expression profiles of 11 women with CI and 4 controls, and differential expression analysis was performed to identify genes showing significant expression changes between the CI (n = 11) and control (n = 4) groups as well as between the CI-preterm (n = 7) and CI-term (n = 4) groups. Gene set enrichment was assessed in terms of Gene Ontology processes, and a subset of differentially expressed genes in CI was validated in a different sample-set by qRT-PCR and ELISA. Results Thirty genes were differentially expressed between the CI and control groups. Differentially upregulated genes in the CI group included neutrophil-mediated immunity-associated (DEFA3 and ELANE) and bicarbonate transport-related genes. The serum concentration of alpha defensin 3 was significantly higher in women with CI than in controls (P = 0.014). Analysis of differential gene expression according to pregnancy outcomes revealed 338 differentially expressed genes between the CI-term and CI-preterm groups. Immune and defense response to organism-associated genes and influenza A and NOD-like receptor signaling pathways were upregulated in the CI-term group. Conclusions Our results revealed significant differences in the whole blood transcriptomic profiles of women with CI compared to those of controls. Different immune responses in women with CI may affect pregnancy outcomes.

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15 Differentially Expressed Long Non-coding RNA Associated with Gastrointestinal Nematode Infection in Divergent Immune Response Sheep

Journal of Animal Science ◽

10.1093/jas/skab235.013 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 7-8

Author(s):

Maria Malane M Muniz ◽

Mohammed Boareki ◽

Samantha Dixon ◽

Andrew S Peregrine ◽

Paula Menzies ◽

...

Keyword(s):

Rna Sequencing ◽

Liver Tissue ◽

Gastrointestinal Nematode ◽

Nematode Infection ◽

Differentially Expressed ◽

Control Group ◽

Non Coding Rna ◽

And Control ◽

Long Non Coding Rna ◽

Transcript Discovery

Abstract Gastrointestinal nematode infection is one of the major production problems for sheep producers worldwide due its high incidence, morbidity, and mortality in affected flocks. The study of long non-coding RNA (lncRNA) in liver tissue of high (HIR) and low immune responder (LIR) sheep to GINs using RNA-Sequencing technology may provide a better understanding of the gene regulation mechanism associated with the host response to the infection. The aim of this study was to identify differentially expressed (DE) lncRNA between HIR and LIR natural infested sheep and control group. Liver tissue samples from the 13 divergent animals (out of a population of 211) based on their immunoglobulin G levels after vaccination using Hen Egg White (HEW) Lysozyme, and immature abomasum worm counts [HIR (> 4000) (n = 5), LIR (< 1500) (n=5) and control (no parasite challenge) (n=4) groups] were used to perform transcriptomic analysis using RNA-Sequencing. The “Large Gap read mapping “and “Transcript Discovery” tools from CLC Genomics Workbench 20.0.4 (CLC Bio, Aarhus, Denmark), were used to map reads to a reference genome (Oar_rambouillet_v1.0) and transcript discovery, respectively. The FEELnc software was used to identify, from predicted transcript model, potential lncRNAs and classify those transcripts into intro putative lncRNAs and protein coding RNAs. As preliminary results, 8 and 48 DE lncRNAs for HIR and LIR compared to control group were identified, respectively using an adjusted p-value False Discovery Rate (FDR) < 0.05 and Fold change (FC) abs > 2. Functional analyses using the list of DE lncRNAs identified metabolic pathways related to immune function. In depth analysis will help to better understand the physiological mechanisms of resilience of high immune sheep.

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Changes in gene expression at the CD160 locus in the whole blood of sepsis patients.

10.31219/osf.io/hyktr ◽

2020 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Expression Analysis ◽

Whole Blood ◽

Gene Expression Analysis ◽

Differentially Expressed ◽

Blood Gene Expression ◽

Non Coding Rna ◽

Long Non Coding Rna

Sepsis is a leading cause of mortality (1). We mined published datasets from the whole blood of patients with sepsis to identify differentially expressed genes in the septic state (2, 3). We found changes in CD160 expression as among the most significant quantitative differences in sepsis whole blood gene expression. Analysis of a separate dataset (4) demonstrated significant repression of a long non-coding RNA produced at the CD160 locus in the blood of patients with sepsis. In the datasets we analyzed, changes in coding and non-coding gene expression at the CD160 locus were among the most significant changes in gene expression in the blood of patients with sepsis.

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Hypoxia Dependent and Independent Dysregulation of the Transcriptome in Sickle Cell Anemia

Blood ◽

10.1182/blood-2019-132078 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2262-2262

Author(s):

Xu Zhang ◽

Jihyun Song ◽

Binal N. Shah ◽

Taif Hassan ◽

Galina Miasnikova ◽

...

Keyword(s):

Gene Expression ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Research Funding ◽

Molecular Mechanisms ◽

Target Genes ◽

Differentially Expressed ◽

Specific Gene ◽

Regulation Of Transcription ◽

Disease Specific

Sickle cell anemia (SCA) is associated with an increased hypoxic response from anemia and vaso-occlusion-impaired tissue perfusion. The effects of hypoxia are mediated by hypoxia transcription factors (HIFs). Chuvash erythrocytosis (CE) is an inherited condition due to homozygosity for the missense mutation in VHL gene (VHLR200W) that impairs interactions of VHL with HIF-α subunits, thereby augmenting transcription of HIF-regulated genes. CE and SCA share increased expression of erythropoietin (EPO) and other HIF target genes. As HIF-regulation of transcription is tissue and differentiation-stage specific, in this study we used reticulocytes, which are easily accessible and purified peripheral blood erythroid cells. We compared the transcriptomes of SCA and CE reticulocytes to differentiate HIF-mediated dysregulation from non-hypoxic dysregulation of SCA transcripts. Our study revealed reticulocyte gene expression changes that are common to both diseases as well as SCA-specific changes. The reticulocytes were purified from 5 HbSS and 5 age- and gender-matched HbAA African-American individuals, and from 17 VHLR200W homozygotes from Chuvashia and 13 wild type Chuvash individuals. Total RNA was depleted of ribosomal RNA and globin transcripts, and reverse transcribed. Strand-specific libraries were constructed for 100 or 125 bp paired-end sequencing to 30-45 million reads using Illumina HiSeq 2500 or 4000 platform. The sequencing data were mapped to human reference genome version GRCh37 using the splice-aware aligner STAR and analyzed using DESeq2. In separate analyses of the two diseases, we identified 1435 genes differentially expressed in SCA among 6965 analyzed genes, 848 increased and 587 decreased in SCA relative to control individuals. We also identified 1498 genes differentially expressed in CE among 8989 analyzed genes, 862 increased and 636 decreased in CE relative to control individuals. Across all analyzed genes, there was a moderate correlation (r=0.30) of expression changes between the two diseases. Among genes differentially expressed, 258 up-regulated and 155 down-regulated genes overlapped between the two diseases, representing a 1.4-fold enrichment. In a combined analysis of the two diseases, we identified 1228 genes among 6924 analyzed genes that shared altered regulation in both diseases. The 693 genes increased in both diseases were enriched (adjusted P < 0.05) in multiple metabolic, inflammatory, and oxidative pathways. The 535 genes decreased in both diseases were enriched in a cell cycle pathway. Among the commonly increased genes, the expression level of ERFE encoding erythroferrone was increased by 9.4-fold in CE and by 4.3-fold in SCA, suggesting markedly altered iron regulation in CE and SCA. This would be expected as both SCA and CE share upregulated erythropoiesis that is associated with augmented erythroferrone. Among the commonly decreased genes, RPL3L encoding Ribosomal Protein L3 Like was decreased by 68% in CE and by 93% in SCA. These common expression changes reflect hypoxic regulation related to chronic anemia in SCA. To assess disease-specific gene expression change, we tested the disease (SCA versus CE) by genotype (mutation versus wildtype) interaction effect. We identified 822 genes that showed disease-specific expression changes among 6924 analyzed genes. Of these disease-specific genes, 304 were increased and 153 decreased in SCA (adjusted P <0.05) but not in CE (nominal P >0.05). For example, SLC16A1, encoding Solute Carrier Family 16 Member 1 and associated with an erythrocyte lactate transporter defect, was increased in SCA by 11-fold whereas PPBP encoding Pro-Platelet Basic Protein was decreased in SCA by 92%; both genes showing no change in CE. The 304 genes with SCA-specific increased expression were enriched in "Thyroid hormone signaling" (5.1 fold) and "Glioma" (7.0-fold) pathways. The 153 genes with SCA-specific decreased expression were enriched in "Ribosome" (12-fold) pathway. Among the disease-specific genes, only 34 increased and 28 decreased in CE but not in SCA. Our study demonstrates high HIF transcriptional activity in both CE and SCA reticulocytes but also reveals hypoxia-independent gene expression changes in SCA reticulocytes. These results suggest that HIF might be a therapeutic target of SCA. These data also shed light on the different molecular mechanisms underlying SCA complications. Disclosures Gordeuk: Pfizer: Research Funding; Modus Therapeutics: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Emmaus: Consultancy, Honoraria; Global Blood Therapeutics: Consultancy, Honoraria, Research Funding; Inctye: Research Funding; CSL Behring: Consultancy, Honoraria, Research Funding; Ironwood: Research Funding; Imara: Research Funding.

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Coding and non-coding RNAs transcribed at the RORA locus (ROR𝛂) are differentially expressed in the whole blood of sepsis patients.

10.31219/osf.io/cdv8y ◽

2020 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Expression Analysis ◽

Whole Blood ◽

Gene Expression Analysis ◽

Differentially Expressed ◽

Blood Gene Expression ◽

Non Coding Rna ◽

Non Coding Rnas ◽

Long Non Coding Rna

Sepsis is a leading cause of mortality (1). We mined published datasets from the whole blood of patients with sepsis to identify differentially expressed genes in the septic state (2, 3). We found changes in RORA expression as among the most significant quantitative differences in sepsis whole blood gene expression. Analysis of a separate dataset (4) demonstrated significant repression of a long non-coding RNA produced at the RORA locus in the blood of patients with sepsis.

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Effect of Acute Aldosterone Administration on Gene Expression Profile in the Heart

Endocrinology ◽

10.1210/en.2005-1674 ◽

2006 ◽

Vol 147 (7) ◽

pp. 3183-3189 ◽

Cited By ~ 24

Author(s):

Alexander Turchin ◽

Christine Z. Guo ◽

Gail K. Adler ◽

Vincent Ricchiuti ◽

Isaac S. Kohane ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Expression Profile ◽

Software Tool ◽

Differentially Expressed ◽

Control Group ◽

Myocardial Inflammation ◽

Acute Administration ◽

Mrna Levels ◽

And Control

Aldosterone is known to have a number of direct adverse effects on the heart, including fibrosis and myocardial inflammation. However, genetic mechanisms of aldosterone action on the heart remain unclear. This paper describes an investigation of temporal changes in gene expression profile of the whole heart induced by acute administration of a physiologic dose of aldosterone in the mouse. mRNA levels of 34,000 known mouse genes were measured at eight time points after aldosterone administration using oligonucleotide microarrays and compared with those of the control animals who underwent a sham injection. A novel software tool (CAGED) designed for analysis of temporal microarray experiments using a Bayesian approach was used to identify genes differentially expressed between the aldosterone-injected and control group. CAGED analysis identified 12 genes as having significant differences in their temporal profiles between aldosterone-injected and control groups. All of these genes exhibited a decrease in expression level 1–3 h after aldosterone injection followed by a brief rebound and a return to baseline. These findings were validated by quantitative RT-PCR. The differentially expressed genes included phosphatases, regulators of steroid biosynthesis, inactivators of reactive oxygen species, and structural proteins. Several of these genes are known to functionally mediate biochemical phenomena previously observed to be triggered by aldosterone administration, such as phosphorylation of ERK1/2. These results provide the first description of cardiac genetic response to aldosterone and identify several potential mediators of known biochemical sequelae of aldosterone administration in the heart.

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OP0021 IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN EARLY RHEUMATOID ARTHRITIS PATIENTS RESPONDING TO TOCILIZUMAB

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.3668 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 12.2-12

Author(s):

I. Muller ◽

M. Verhoeven ◽

H. Gosselt ◽

M. Lin ◽

T. De Jong ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Gene Expression ◽

T Cells ◽

Gene Ontology ◽

Regulatory T Cells ◽

Early Rheumatoid Arthritis ◽

Whole Blood ◽

Differentially Expressed ◽

Rna Seq ◽

Double Blind

Background:Tocilizumab (TCZ) is a monoclonal antibody that binds to the interleukin 6 receptor (IL-6R), inhibiting IL-6R signal transduction to downstream inflammatory mediators. TCZ has shown to be effective as monotherapy in early rheumatoid arthritis (RA) patients (1). However, approximately one third of patients inadequately respond to therapy and the biological mechanisms underlying lack of efficacy for TCZ remain elusive (1). Here we report gene expression differences, in both whole blood and peripheral blood mononuclear cells (PBMC) RNA samples between early RA patients, categorized by clinical TCZ response (reaching DAS28 < 3.2 at 6 months). These findings could lead to identification of predictive biomarkers for TCZ response and improve RA treatment strategies.Objectives:To identify potential baseline gene expression markers for TCZ response in early RA patients using an RNA-sequencing approach.Methods:Two cohorts of RA patients were included and blood was collected at baseline, before initiating TCZ treatment (8 mg/kg every 4 weeks, intravenously). DAS28-ESR scores were calculated at baseline and clinical response to TCZ was defined as DAS28 < 3.2 at 6 months of treatment. In the first cohort (n=21 patients, previously treated with DMARDs), RNA-sequencing (RNA-seq) was performed on baseline whole blood PAXgene RNA (Illumina TruSeq mRNA Stranded) and differential gene expression (DGE) profiles were measured between responders (n=14) and non-responders (n=7). For external replication, in a second cohort (n=95 therapy-naïve patients receiving TCZ monotherapy), RNA-seq was conducted on baseline PBMC RNA (SMARTer Stranded Total RNA-Seq Kit, Takara Bio) from the 2-year, multicenter, double-blind, placebo-controlled, randomized U-Act-Early trial (ClinicalTrials.gov identifier: NCT01034137) and DGE was analyzed between 84 responders and 11 non-responders.Results:Whole blood DGE analysis showed two significantly higher expressed genes in TCZ non-responders (False Discovery Rate, FDR < 0.05): urotensin 2 (UTS2) and caveolin-1 (CAV1). Subsequent analysis of U-Act-Early PBMC DGE showed nine differentially expressed genes (FDR < 0.05) of which expression in clinical TCZ non-responders was significantly higher for eight genes (MTCOP12, ZNF774, UTS2, SLC4A1, FECH, IFIT1B, AHSP, and SPTB) and significantly lower for one gene (TND2P28M). Both analyses were corrected for baseline DAS28-ESR, age and gender. Expression of UTS2, with a proposed function in regulatory T-cells (2), was significantly higher in TCZ non-responders in both cohorts. Furthermore, gene ontology enrichment analysis revealed no distinct gene ontology or IL-6 related pathway(s) that were significantly different between TCZ-responders and non-responders.Conclusion:Several genes are differentially expressed at baseline between responders and non-responders to TCZ therapy at 6 months. Most notably, UTS2 expression is significantly higher in TCZ non-responders in both whole blood as well as PBMC cohorts. UTS2 could be a promising target for further analyses as a potential predictive biomarker for TCZ response in RA patients in combination with clinical parameters (3).References:[1]Bijlsma JWJ, Welsing PMJ, Woodworth TG, et al. Early rheumatoid arthritis treated with tocilizumab, methotrexate, or their combination (U-Act-Early): a multicentre, randomised, double-blind, double-dummy, strategy trial. Lancet. 2016;388(10042):343-55.[2]Bhairavabhotla R, Kim YC, Glass DD, et al. Transcriptome profiling of human FoxP3+ regulatory T cells. Human Immunology. 2016;77(2):201-13.[3]Gosselt HR, Verhoeven MMA, Bulatovic-Calasan M, et al. Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis. Journal of Personalized Medicine. 2021;11(1).Disclosure of Interests:None declared

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O18 Integrated molecular analysis of systemic sclerosis skin and blood shows significant differences between major autoantibody subgroups

Rheumatology ◽

10.1093/rheumatology/keab246.017 ◽

2021 ◽

Vol 60 (Supplement_1) ◽

Author(s):

Kristina E Clark ◽

Corrado Campochiaro ◽

Eszter Csomor ◽

Adam Taylor ◽

Katherine Nevin ◽

...

Keyword(s):

Gene Expression ◽

Systemic Sclerosis ◽

Whole Blood ◽

Serum Markers ◽

Differentially Expressed ◽

Longitudinal Change ◽

Beta Catenin ◽

Skin Score ◽

Topoisomerase 1 ◽

Organ Manifestations

Abstract Background/Aims The major antinuclear autoantibodies of systemic sclerosis (SSc) associate with different skin score trajectories and risk of internal organ manifestations. To elucidate molecular differences between ANA-defined subgroups, we utilised the prospective BIOPSY cohort of well-characterised SSc patients. Methods The prospectively collected BIOPSY cohort recruited 52 SSc patients (21 early dcSSc, 15 established dcSSc, 16 lcSSc) and 16 healthy controls (HC). 36 (69%) of the SSc patients are female. Mean disease duration in the early dcSSc cohort was 24 months (sd 12 months), and in established dcSSc was 11.3 years. ANA frequency in BIOPSY reflected the overall dcSSc population: anti-topoisomerase-1 (ATA) n = 14 (27%), anti-RNA pol III (ARA) n = 12 (23%) and other n = 26 (50%). Mean baseline skin score (MRSS) for early dcSSc was 21 (sd 11.2). At a group level mRSS peak was 21.9 (11.8) at 3 months and fell to 19.1(10.5) at 12 months. Serum biomarkers of ECM turnover and fibrosis were measured three monthly and genome-wide transcriptomic profiling of whole skin and whole blood performed by RNA-Seq. Statistical analysis used RStudio with ANOVA, and Tukey post-hoc test. Differential gene expression used the Bioconductor limma software, with standard thresholds for significance. Results At baseline, there were differences in soluble markers between clinical SSc sugroups and HC but not for major ANA subgroups. However, we found clear differences in early dcSSc analysed by major ANA subset for longitudinal change in serum markers of fibrosis and in whole skin gene expression, suggesting a mechanistic basis for the distinct clinical phenotypes associated with hallmark ANAs. During follow-up, significant differences were observed in HA, TIMP1, and PIIINP at 6 and 12 months (p < 0.05), with stable levels in ATA+ patients compared to progressively increased levels in the other subgroups. There were 564 significantly differentially expressed genes in skin between early dcSSc and HC. Unsupervised clustering differentiated patients with ARA and ATA positivity with early dcSSc. 54 genes were significantly differentially expressed in skin between ATA and ARA patients. Whilst 179 genes were differentially expressed in whole blood between early dcSSc compared with HC, no genes could significantly differentiate ATA from ARA. Functional analysis using HALLMARK pathway analysis identified both shared pathways associated with SSc across ANA groups (e.g. TGF beta signaling, IL6 JAK STAT3 signalling, inflammatory response), and pathways only upregulated in patients with ATA (e.g. Wnt beta catenin signaling, Notch signaling), and ARA (e.g. interferon gamma response, adipogenesis). Conclusion We have found significant differences in skin gene expression and longitudinal change in serum markers by autoantibody specificity in dcSSc. Our findings have implications for SSc pathogenesis and support stratification by ANA subgroup in clinical studies. Disclosure K.E. Clark: None. C. Campochiaro: None. E. Csomor: Corporate appointments; employee of GSK. A. Taylor: Corporate appointments; employee of GSK. K. Nevin: Corporate appointments; employee of GSK. N. Galwey: Corporate appointments; employee of GSK. M.A. Morse: Corporate appointments; employee of GSK. V.H. Ong: None. E. Derrett-Smith: None. N. Wisniacki: Corporate appointments; employee of GSK. S. Flint: Corporate appointments; employee of GSK. C.P. Denton: Consultancies; Actelion, GlaxoSmithKline, Bayer, Sanofi, lnventiva, Boehringer Ingelheim, Roche, Bristol Myers Squibb, CSL Behring, UCB, Leadiant Biosciences, Corbus, Servier, Arxx Therapeutics.

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Abstract W P73: Feasibility and Preliminary Results of Whole Blood RNA-Sequencing Analysis in Patients With Intracranial Aneurysms

Stroke ◽

10.1161/str.45.suppl_1.wp73 ◽

2014 ◽

Vol 45 (suppl_1) ◽

Author(s):

Blake Haas ◽

Nestor R Gonzalez ◽

Elina Nikkola ◽

Mark Connolly ◽

William Hsu ◽

...

Keyword(s):

Gene Expression ◽

Network Analysis ◽

Rna Sequencing ◽

Whole Blood ◽

Intracranial Aneurysms ◽

Small Sample Size ◽

Expression Patterns ◽

Small Sample ◽

Cellular Respiration ◽

Sequencing Analysis

Introduction: Intracranial aneurysms (IA) growth and rupture have been associated with chronic remodeling of the arterial wall. However, the pathobiology of this process remains poorly understood. The objective of the present study was to evaluate the feasibility of analyzing gene expression patterns in peripheral blood of patients with ruptured and unruptured saccular IAs. Materials and Methods: We analyzed human whole blood transcriptomes by performing paired-end, 100 bp RNA-sequencing (RNAseq) using the Illumina platform. We used STAR to align reads to the genome, HTSeq to count reads, and DESeq to normalize counts across samples. Self-reported patient information was used to correct expression values for ancestry, age, and sex. We utilized weighted gene co-expression network analysis (WGCNA) to identify gene expression network modules associated with IA size and rupture. The DAVID tool was employed to search for Gene Ontology enrichment in relevant modules. Results: Samples from 12 patients (9 females, age 57.6 +/-12) with IAs were analyzed. Four had ruptured aneurysms. RNA isolation and application of the methodology described above was successful in all samples. Although the small sample size prevents us from drawing definite conclusions, we observed promising novel co-expression networks for IAs: WCGNA analysis showed down-regulation of two transcript modules associated with ruptured IA status (r=-0.78, p=0.008 and r=-0.77, p=0.009), and up-regulation of two modules associated with aneurysm size (r=0.86, p=0.002 and r=0.9, p=4e-04), respectively. DAVID analyses showed that genes upregulated in an IA size-associated module were enriched with genes involved in cellular respiration and translation, while genes involved in transcription were down-regulated in a module associated with ruptured IAs. Conclusions: Whole blood RNAseq analysis is a feasible tool to capture transcriptome dynamics and achieve a better understanding of the pathophysiology of IAs. Further longitudinal studies of patients with IAs using network analysis are justified.

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Abstract 3259: Leukocyte Subset Specific Gene Expression In Acute Stroke Patients

Stroke ◽

10.1161/str.43.suppl_1.a3259 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

Mateusz G Adamski ◽

Yan Li ◽

Hua Yu ◽

Erin Wagner ◽

Sareen Amarjeet ◽

...

Keyword(s):

Gene Expression ◽

Acute Stroke ◽

Whole Blood ◽

Peripheral Blood ◽

Fold Increase ◽

Specific Gene ◽

Related Gene ◽

Stroke Patients ◽

Leukocyte Subset ◽

Control Subjects

Background: Alterations in gene expression in the peripheral blood of patients with acute stroke have been demonstrated using microarray technology. Whole blood and peripheral blood mononuclear cells (PBMCs) were used in prior studies in which panels of genes diagnostic for stroke were developed. We aimed to determine the cellular sources of alterations in gene expression by studying individual leukocyte subsets. Methods: The expression of four genes previously found to be upregulated in ischemic and hemorrhagic stroke (IL1R2, S100A9, ETS2 and F5) was measured in four leukocyte subsets: CD14+ monocytes, CD4+ T cell lymphocytes, CD20+ B cell lymphocytes and PBMCs. These four genes had been reported in at least two of the previously published stroke-related gene panels. Peripheral blood was obtained from six acute stroke patients (all <48 hours from symptom onset) and 6 age, race and sex matched control subjects. Leukocytes were separated from whole blood using density gradient centrifugation and column magnetic bead cell sorting. The purity of separated leukocyte subsets exceeded 90% and was verified with flow cytometry. Messenger RNA was isolated from each leukocyte subset and analyzed by two step RT PCR and qPCR. The expression of the four stroke-related genes was compared to the expression of a housekeeping gene (GAPDH). The relative expression of individual genes and of the 4 gene panel within cellular subsets was compared between stroke patients and control subjects. Results: Individually, IL1R2 and S100A9 were significantly over-expressed in stroke patients with a 10 fold increase for IL1R2 in PBMCs (p<0.05) and a 3 fold increase for S100A9 in the CD4+ T and CD20+ B lymphocyte subsets (p<0.05). When analyzed as a panel of four genes the expression of IL1R2, S100A9, ETS2 and F5 was significantly higher in both the CD4+ T lymphocytes (p<0.05) and CD20+ B lymphocytes (p<0.05) of stroke patients but not in the monocytes or the PBMCs. Conclusion: These results show the potential diagnostic value of selected genes from panels previously found in microarray studies in stroke patients. They also emphasize the value of panel analysis over that of single gene expression and the potential cellular specificity of alterations in gene expression. Analysis of whole blood and PBMCs alone may not reflect important dynamic changes in stroke-related gene expression.

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