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Results for “Expression profiling”

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PubMed2003

Gene expression profiling of alcoholic liver disease in the baboon (Papio hamadryas) and human liver.

The molecular pathogenesis of alcoholic liver disease (ALD) is not well understood. Gene expression profiling has the potential to identify new pathways and altered molecules in ALD. Gene expression profiles of ALD in a baboon model and humans were compared using DNA arrays. Reverse transcriptase-polymerase chain reaction and immunohistochemistry were used for downstream analysis of array results. cDNA array analysis revealed differential expression of several novel genes and pathways in addition to genes known to be involved in ALD pathogenesis. Overall gene expression profiles were similar in both species, with a majority of genes involved with fibrogenesis and xenobiotic metabolism, as well as inflammation, oxidant stress, and cell signaling. Genes associated with stellate cell activation (collagens, matrix metalloproteinases, tissue inhibitors of matrix metalloproteinase) were up-regulated in humans. Decreased expression of several metallothioneins was unexpected. Fourteen molecules related to the annexin family were up-regulated, including annexin A1 and A2. Immunofluorescence revealed a marked overexpression of annexin A2 in proliferating bile duct cells, hepatocyte cell surface, and selective co-localization with CD14-positive cells in human ALD. The gene expression profile of ALD is dominated by alcohol metabolism and inflammation and differs from other liver diseases. Annexins may play a role in the progression of fibrosis in ALD.

Adult↗

PubMed2000

Expression profiling in the muscular dystrophies: identification of novel aspects of molecular pathophysiology.

We used expression profiling to define the pathophysiological cascades involved in the progression of two muscular dystrophies with known primary biochemical defects, dystrophin deficiency (Duchenne muscular dystrophy) and alpha-sarcoglycan deficiency (a dystrophin-associated protein). We employed a novel protocol for expression profiling in human tissues using mixed samples of multiple patients and iterative comparisons of duplicate datasets. We found evidence for both incomplete differentiation of patient muscle, and for dedifferentiation of myofibers to alternative lineages with advancing age. One developmentally regulated gene characterized in detail, alpha-cardiac actin, showed abnormal persistent expression after birth in 60% of Duchenne dystrophy myofibers. The majority of myofibers ( approximately 80%) remained strongly positive for this protein throughout the course of the disease. Other developmentally regulated genes that showed widespread overexpression in these muscular dystrophies included embryonic myosin heavy chain, versican, acetylcholine receptor alpha-1, secreted protein, acidic and rich in cysteine/osteonectin, and thrombospondin 4. We hypothesize that the abnormal Ca(2)+ influx in dystrophin- and alpha-sarcoglycan-deficient myofibers leads to altered developmental programming of developing and regenerating myofibers. The finding of upregulation of HLA-DR and factor XIIIa led to the novel identification of activated dendritic cell infiltration in dystrophic muscle; these cells mediate immune responses and likely induce microenvironmental changes in muscle. We also document a general metabolic crisis in dystrophic muscle, with large scale downregulation of nuclear-encoded mitochondrial gene expression. Finally, our expression profiling results show that primary genetic defects can be identified by a reduction in the corresponding RNA.

Actins↗

PubMed2004

Constrained clusters of gene expression profiles with pathological features.

MOTIVATION: Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. RESULTS: We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Algorithms↗

PubMed2003

Accurate and reproducible gene expression profiles from laser capture microdissection, transcript amplification, and high density oligonucleotide microarray analysis.

Gene expression profiling using high density oligonucleotide arrays is a powerful method to generate an unbiased survey of a cell's transcriptional landscape. Increasingly complex biological questions require that this approach be applicable to the small numbers of cells that are obtained from sources such as laser capture microdissection (LCM) of solid tissues. In this report, we demonstrate that two rounds of transcript amplification can generate accurate and reproducible gene expression profiles using high density oligonucleotide microarrays, starting with as little as 10 ng of total RNA. Biased amplification of the 3' end of transcripts does not have a major impact on the overall transcript profile due to the 3' bias of probe sets incorporated in the array design. Furthermore, greater than 95% of all genes detected demonstrate less than a twofold difference in expression when independent tissue dissections of identical cell populations are compared. The accuracy and technical reproducibility of the method suggests that expression profiling using transcript amplification and high density oligonucleotide microarrays can be used on a routine basis.

Breast Neoplasms↗

PubMed2004

Gene expression profile of degenerated cervical intervertebral disc tissues in rats.

OBJECTIVE: To analyze the gene expression profile of degenerated cervical intervertebral disc of Sprague Dawley rats on a large scale. METHODS: Degenerated models of Sprague Dawley rats of 9 months old (degeneration group, n=9) and normal Sprague Dawley rats of 3 months old (control group, n=9) were prepared, respectively. mRNA was obtained from the cervical intervertebral disc of rats in both groups, respectively, and then labelled by Cy5 and Cy3 fluorescence respectively after reverse transcription to obtain intervertebral disc cDNA probes. cDNA probes were hybridized with BiostarR-40s gene expression profile chips and scanned by laser scanner. The results were treated with portrait analysis, standardization management, and ratio analysis with softwares. RESULTS: Compared with the rats in the control group, 9.6% (381 pieces in total) gene expression changed obviously in the rats in the degeneration group, among which, the gene expression quantities of 171 pieces increased significantly (r=the ratio of the degeneration group to the control group>2.0), 52 pieces of which had certain function. While the gene expression quantities of 211 pieces decreased significantly (r<0.5), 41 pieces of which had certain function. CONCLUSIONS: Gene chip technology can be used to analyze the gene expression profile of degenerated intervertebral disc of rats in parallel, in quantity and on a large scale, which helps to testify the representative genes and protein expression, and plays an important role in clarifying the pathogenesis of degenerated intervertebral disc.

Animals↗

PubMed2004

Gene Ontology friendly biclustering of expression profiles.

The soundness of clustering in the analysis of gene expression profiles and gene function prediction is based on the hypothesis that genes with similar expression profiles may imply strong correlations with their functions in the biological activities. Gene Ontology (GO) has become a well accepted standard in organizing gene function categories. Different gene function categories in GO can have very sophisticated relationships, such as 'part of' and 'overlapping'. Until now, no clustering algorithm can generate gene clusters within which the relationships can naturally reflect those of gene function categories in the GO hierarchy. The failure in resembling the relationships may reduce the confidence of clustering in gene function prediction. In this paper, we present a new clustering technique, Smart Hierarchical Tendency Preserving clustering (SHTP-clustering), based on a bicluster model, Tendency Preserving cluster (TP-Cluster). By directly incorporating Gene Ontology information into the clustering process, the SHTP-clustering algorithm yields a TP-cluster tree within which any subtree can be well mapped to a part of the GO hierarchy. Our experiments on yeast cell cycle data demonstrate that this method is efficient and effective in generating the biological relevant TP-Clusters.

Algorithms↗

PubMed2001

Differential gene expression profiling in human brain tumors.

Gene expression profiling of three human temporal lobe brain tissue samples (normal) and four primary glioblastoma multiforme (GBM) tumors using oligonucleotide microarrays was done. Moreover, confirmation of altered expression was performed by whole cell patch clamp, immunohistochemical staining, and RT-PCR. Our results identified several ion and solute transport-related genes, such as N-methyl-d-aspartate (NMDA) receptors, alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)-2 receptors, GABA(A) receptor subunits alpha3, beta1, beta2, and beta3, the glutamate transporter, the glutamate/aspartate transporter II, the potassium channel K(V)2.1, hK(V)beta3, and the sodium/proton exchanger 1 (NHE-1), that are all downregulated in the tumors compared with the normal tissues. In contrast, aquaporin-1, possibly aquaporins-3 and -5, and GLUT-3 message appeared upregulated in the tumors. Our results also confirmed previous work showing that osteopontin, nicotinamide N-methyltransferase, murine double minute 2 (MDM2), and epithelin (granulin) are upregulated in GBMs. We also demonstrate for the first time that the cytokine and p53 binding protein, macrophage migration inhibitory factor (MIF), appears upregulated in GBMs. These results indicate that the modulation of ion and solute transport genes and heretofore unsuspected cytokines (i.e., MIF) may have profound implications for brain tumor cell biology and thus may identify potential useful therapeutic targets in GBMs.

Aquaporin 1↗

PubMed2004

[Comparison of changes in left ventricular gene expression profiles from different cardiac hypertrophy models in rats].

To get insights into the principles of gene expression changes during cardiac hypertrophy, three rat cardiac hypertrophy models were prepared, i.e., suprarenal abdominal aortic stenosis (SRS), arterial-vein fistula (AVF) and continuous jugular vein infusion of norepinephrine (NEi). The cardiac function and structure were analyzed by echocardiograph as well as histological examination. Total RNA of left ventricles was extracted and gene expression profiles were analyzed by cDNA microarray. SRS and NEi induced concentric cardiac hypertrophy and AVF induced eccentric hypertrophy in rats, among which NEi caused obvious cardiac fibrosis. The changes of gene expression profiles were compared comprehensively across different pathologic cardiac hypertrophy models. While gene expression profiles of different cardiac hypertrophy models compared with pairs, parts of the genes involved were found overlapped, and mostly the gene expression changed in the same direction between two models, but some of them changed in the opposite directions. Expression levels of 19 genes were found changed across all cardiac hypertrophy models, and genes relatively regulated in a specific model was also found when comparison of all the three models was carried out. Novel clues for further study might derive from the results mentioned above, and some genes might be the marker genes of cardiac hypertrophy or the targets of therapy.

Animals↗

PubMed2006

Global gene expression profiling of asymptomatic bacteriuria Escherichia coli during biofilm growth in human urine.

Urinary tract infection (UTI) is an important health problem worldwide, with many millions of cases each year, and Escherichia coli is the most common organism causing UTI in humans. Also, E. coli is responsible for most infections in patients with chronic indwelling bladder catheter. The two asymptomatic bacteriuria (ABU) E. coli strains 83972 and VR50 are significantly better biofilm formers in their natural growth medium, human urine, than the two uropathogenic E. coli isolates CFT073 and 536. We used DNA microarrays to monitor the expression profile during biofilm growth in urine of the two ABU strains 83972 and VR50. Significant differences in expression levels were seen between the biofilm expression profiles of the two strains with the corresponding planktonic expression profiles in morpholinepropanesulfonic acid minimal laboratory medium and human urine; 417 and 355 genes were up- and down-regulated, respectively, during biofilm growth in urine of 83972 and VR50. Many genes involved in transcription and stress were up-regulated in biofilm-grown cells. The role in biofilm formation of four of the up-regulated genes, i.e., yceP, yqgA, ygiD, and aaeX, was investigated by creating single-knockout mutant versions of 83972 and VR50; all mutants showed reduced biofilm formation in urine by 18 to 43% compared with the wild type (P < 0.05). Also, the expression profile of strain 83972 in the human urinary tract partially overlaps with the biofilm expression profile.

Adaptation, Physiological↗

PubMed2001

Gene expression profile in BALB/c-3T3 cells transformed with beryllium sulfate.

Differential gene expression was studied to understand the potential molecular mechanism responsible for cell transformation and tumorigenesis induced by beryllium. Cell lines were derived from tumors developed in nude mice injected subcutaneously with BALB/c-3T3 cells morphologically transformed with beryllium sulfate. Using the Atlas mouse 1.2 cDNA expression microarray, the expression profiles of 1176 genes, belonging to several different functional categories, were studied in the tumor cells as well as in the nontransformed control cells. Expression of 18 genes belonging to two functional groups was found to be consistently and reproducibly different (at least twofold) in the tumor cells compared with the control cells. The functional groups and the differentially expressed genes are as follows: The cancer-related genes (nine genes) were the ets-related transcription factor activated by ras, colony-stimulating factor, A-myb, sky, cot1, c-fos, c-jun, c-myc, and R-ras proto-oncogenes. The DNA synthesis, repair, and recombination genes (nine genes) were the DNA replication licensing factor MCM4, the DNA replication licensing factor MCM5, the DNA mismatch repair gene PMS2, the DNA excision repair gene, the DNA mismatch repair gene MSH2, the ultraviolet excision repair gene Rad23 DNA ligase 1, Rad51, and Rad52. The differential gene expression profile was confirmed with reverse transcription-polymerase chain reaction using primers specific for the differentially expressed genes. In general, expression of the cancer-related genes was upregulated, while expression of genes involved in DNA synthesis, repair, and recombination was downregulated in the tumor cells compared with the control cells. Using c-fos and c-jun, two of the differentially expressed genes, as model genes, we have found that in the nontransformed BALB/c-3T3 cells, the beryllium-induced transcriptional activation of these genes was dependent on pathways of protein kinase C and mitogen-activated protein kinase and independent of reactive oxygen species. These results indicate that beryllium-induced cell transformation and tumorigenesis are accompanied by and are possibly a product of alterations in expression of genes related to cancer and to DNA synthesis, repair, and recombination.

3T3 Cells↗

PubMed2003

Multiclass cancer classification using gene expression profiling and probabilistic neural networks.

Gene expression profiling by microarray technology has been successfully applied to classification and diagnostic prediction of cancers. Various machine learning and data mining methods are currently used for classifying gene expression data. However, these methods have not been developed to address the specific requirements of gene microarray analysis. First, microarray data is characterized by a high-dimensional feature space often exceeding the sample space dimensionality by a factor of 100 or more. In addition, microarray data exhibit a high degree of noise. Most of the discussed methods do not adequately address the problem of dimensionality and noise. Furthermore, although machine learning and data mining methods are based on statistics, most such techniques do not address the biologist's requirement for sound mathematical confidence measures. Finally, most machine learning and data mining classification methods fail to incorporate misclassification costs, i.e. they are indifferent to the costs associated with false positive and false negative classifications. In this paper, we present a probabilistic neural network (PNN) model that addresses all these issues. The PNN model provides sound statistical confidences for its decisions, and it is able to model asymmetrical misclassification costs. Furthermore, we demonstrate the performance of the PNN for multiclass gene expression data sets. Here, we compare the performance of the PNN with two machine learning methods, a decision tree and a neural network. To assess and evaluate the performance of the classifiers, we use a lift-based scoring system that allows a fair comparison of different models. The PNN clearly outperformed the other models. The results demonstrate the successful application of the PNN model for multiclass cancer classification.

Artificial Intelligence↗

PubMed2005

Global approach to the diagnosis of leukemia using gene expression profiling.

Accurate diagnosis and classification of leukemias are the bases for the appropriate management of patients. The diagnostic accuracy and efficiency of present methods may be improved by the use of microarrays for gene expression profiling. We analyzed gene expression profiles in 937 bone marrow and peripheral blood samples from 892 patients with all clinically relevant leukemia subtypes and from 45 nonleukemic controls by U133A and U133B GeneChip arrays. For each subgroup, differentially expressed genes were calculated. Class prediction was performed using support vector machines. Prediction accuracy was estimated by 10-fold cross-validation and was assessed for robustness in a 100-fold resampling approach using randomly chosen test sets consisting of one third of the samples. Applying the top 100 genes of each subgroup, an overall prediction accuracy of 95.1% was achieved that was confirmed by resampling (median, 93.8%; 95% confidence interval, 91.4%-95.8%). In particular, acute myeloid leukemia (AML) with t(15;17), AML with t(8;21), AML with inv(16), chronic lymphatic leukemia (CLL), and pro-B-cell acute lymphoblastic leukemia (pro-B-ALL) with t(11q23) were classified with 100% sensitivity and 100% specificity. Accordingly, cluster analysis completely separated all 13 subgroups analyzed. Gene expression profiling can predict all clinically relevant subentities of leukemia with high accuracy.

Adolescent↗

PubMed2003

Gene expression profiling of preneoplastic liver disease and liver cancer: a new era for improved early detection and treatment of these deadly diseases?

Hepatocellular carcinoma (HCC) is a multi-step process associated with changes in gene expression. Currently, several technologies enable global gene expression profiling. The number of studies to probe global gene expression profiles of HCC or preneoplastic chronic liver diseases has increased exponentially in recent years. These studies have quickly provided rich information and some additional clues to the genesis of liver cancer. The application of gene expression profiling to preneoplastic liver diseases and HCC is growing in importance and practicality. In this commentary, we review the recent advances in the utilization of global gene expression profiling to liver cancer, which have provided new insight into the molecular mechanisms underlying the development of HCC. We have also discussed the problems related to these new technologies, as well as their contributions and implications. By recognizing the shortcomings, we can reassess our current approaches, which allow us to better design and analyze global gene expression-based experiments. These new approaches will undoubtedly contribute to a better understanding of hepatocarcinogenesis.

Gene Expression Profiling↗

PubMed2002

Expression profiling to understand actions of NMDA/glutamate receptor antagonists in rat brain.

Agents acting as noncompetitive N-methyl-D-aspartate (NMDA)/glutamate receptor antagonists induce the expression of several genes in limbic cortical regions, such as the cingulate, retrosplenial, and entorhinal cortices. These include important regulatory genes such as the neurotrophin brain-derived neurotrophic factor (BDNF), its receptor trkB, and c-fos. We applied expression profiling methods to find genes coregulated with BDNF following treatment with the prototypical NMDA/glutamate receptor antagonist MK-801. Expression profiling provides a useful technique for describing the molecular and transcriptional level events that follow various processes. We illustrate the utility of microarrays to find novel ESTs regulated by MK-801. We also used expression profiling with microarrays to characterize the levels of transcription factor cAMP response element modulator (CREM) and inducible cAMP early repressor (ICER) isoforms that are induced by MK-801. These factors may act as the eventual repressors for BDNF expression via competition and heterodimerization with phosphorylated CREB, a transcription factor important for BDNF expression. Finally, we find and confirm the regulation of Erp29, RTNI, and an ABC transporter by antagonism of NMDA/glutamate receptors as potential stress related molecules in brain. The emerging picture generated by using these expression profiling approaches, identifies several of what likely will be many molecules that take part in the complex events that occur during BDNF signaling mediated by blockade of NMDA/ glutamate receptors.

Animals↗

PubMed2006

Differential endocrine regulation of genes enriched in initial segment and distal caput of the mouse epididymis as revealed by genome-wide expression profiling.

We have performed genome-wide expression profiling of endocrine regulation of genes expressed in the mouse initial segment (IS) and distal caput of the epididymis by using Affymetrix microarrays. The data revealed that of the 15 020 genes expressed in the epididymis, 35% were enriched in one of the two regions studied, indicating that differential functions can be attributed to the IS and the more distal caput regions. The data, furthermore, showed that 27% of the genes expressed in the IS and/or distal caput epididymidis are under the regulation of testicular factors present in the duct fluid, while bloodborne androgens can regulate for 14% of them. This is in line with the high testis dependency of epididymal physiology. We then focused on genes with moderate or strong expression, showing strict segment enrichment and strong dependency on testicular factors. Analyses of the 59 genes, including upregulated and downregulated genes, fulfilling the criteria indicated that the expression of 18 (17 downregulated genes; 1 upregulated gene) of 19 gonadectomy-responsive genes enriched in the IS was not maintained by the androgen treatment, whereas the expression of all six downregulated genes enriched in the distal caput and the majority of those with no strict segment enrichment of expression (28 of 34; consisting of 23 downregulated and 5 upregulated genes) were maintained by androgens. Hence, it is evident that testicular factors other than androgens are important for the expression of IS-enriched genes, whereas the expression of distal caput-enriched genes is typically regulated by androgens. Identical data were obtained by independent clustering analyses performed for the expression data of 3626 epididymal genes. Several novel genes with putative involvement in epididymal sperm maturation, such as a disintegrin and metallopeptidase domain 28 (Adam28) and a solute carrier organic anion transporter family, member 4C1 (Slco4c1), were identified, indicating that this approach is successful for identifying novel epididymal genes.

ADAM Proteins↗

PubMed2003

[Indentification of differentially expressed genes in proliferating and involuting hemangiomas by cDAN microarray analysis of gene-expression profiles].

OBJECTIVE: To investigate the differentially expressed genes of proliferating and involuting hemangiomas by cDNA microarray analysis of gene-expression profiles in an effort to identify the key disease-related genes. METHODS: Samples were processed from total RNA and purified to mRNA, which was reverse-transcripted and hybridized onto Biodoor Genechip expression microarrays. Analyses were performed to determine the consensus pattern of gene expression in the proliferating and involuting stages of the same hemangioma and the changes in the expression level. RESULTS: In proliferating hemangioma, 79 genes were overexpressed, and 115 genes were underexpressed in comparison with the involuting hemangioma. Some cytokines and growth factors such as neurotensin, Nov, CYR6, keratinocyte growth factor, interleukin-10 were overexpressed in proliferative hemangioma. In involuting hemangioma, apoptotic factors such as bcl-2 binding component, cytochrome C were overexpressed. The overexpression of Nov, CYR6, c-myc implied that angiogenesis and oncogenes might participate in the pathogenesis of hemangiomas. Mitochondria activated apoptotic passage (cytokines, bcl-2, cytochrome C) and Wnt/beta-catenin passage(Frizzled, beta-catenin, c-myc) were involved. CONCLUSION: The development of hemangiomas may be the results of imbalance of cell proliferation and apoptosis.

Apoptosis↗

PubMed2005

Comparing the global mRNA expression profile of human atrial and ventricular myocardium with high-density oligonucleotide arrays.

OBJECTIVES: The knowledge of chamber-specific gene expression in human atrial and ventricular myocardium is essential for the understanding of myocardial function and the basis for the identification of putative therapeutic targets in the treatment of cardiac arrhythmia and heart failure. In this study the gene expression pattern of human left atrial and ventricular myocardium was analyzed. METHODS: Global mRNA expression patterns with high-density oligonucleotide arrays between left atrial and left ventricular myocardium of 6 patients with heart failure undergoing heart transplantation were compared. Clustering of microarray data confirmed chamber-specific gene expression profiles. Genes similarly expressed in all patients were further analyzed, and data were confirmed by means of real-time polymerase chain reaction and Western blot analysis. RESULTS: Of 22,215 genes examined, 7115 transcripts were found to be expressed in all 12 human myocardial samples. One hundred twenty-five genes were differentially expressed between left atrial and left ventricular specimens in all patients examined. Novel genes preferentially expressed in human atria were identified. Interestingly, several potassium channels of subfamily K are more highly expressed in atria than in ventricles. Members of the potassium inwardly rectifying channel of subfamily J were found to be more highly expressed in human ventricular myocardium. Finally, chronic atrial fibrillation was associated with reduced atrial expression of the potassium channel TWIK-1, suggesting potential contribution of the corresponding current to electrical remodeling. CONCLUSIONS: Human atria and ventricles show specific gene expression profiles. Our data provide the basis of a comprehensive understanding of chamber-specific gene expression in diseased human hearts and will support the identification of therapeutic targets in the treatment of arrhythmia and heart failure.

Gene Expression Profiling↗

PubMed2005

Using peripheral blood mononuclear cells to determine a gene expression profile of acute ischemic stroke: a pilot investigation.

BACKGROUND: Direct brain biopsy is rarely indicated during acute stroke. This study uses peripheral blood mononuclear cells (PBMCs) to determine whether a systemic gene expression profile could be demonstrated in patients with acute ischemic stroke. METHODS AND RESULTS: Using oligonucleotide microarrays, we compared the gene expression profile of an index cohort of 20 patients with confirmed ischemic stroke on neuroimaging studies with that of 20 referent subjects. Validation studies used quantitative real-time polymerase chain reaction to measure the levels of 9 upregulated genes in the index cohort, and an independent cohort of 9 patients and 10 referent subjects was prospectively studied to determine the accuracy of the Prediction Analysis for Microarrays list to classify stroke. After correction for multiple comparisons with the Bonferroni technique, 190 genes were significantly different between the stroke and referent groups. Broad classes of genes included white blood cell activation and differentiation (approximately 60%), genes associated with hypoxia and vascular repair, and genes potentially associated with an altered cerebral microenvironment. Real-time polymerase chain reaction confirmed increased mRNA expression in 9 of 9 upregulated stroke-associated genes in the index cohort. A panel of 22 genes derived from the Prediction Analysis for Microarrays algorithm in the index cohort classified stroke in the validation cohort with a sensitivity of 78% and a specificity of 80%. Control for the Framingham stroke risk score revealed only a partial dependence of the stroke gene expression profile in PBMCs on vascular risk. CONCLUSIONS: This study demonstrated an altered gene expression profile in PBMCs during acute ischemic stroke. Some genes with altered expression were consistent with an adaptive response to central nervous system ischemia.

Acute Disease↗