scholarly journals Blood Genomic Expression Profile for Neuronal Injury

2003 ◽  
Vol 23 (3) ◽  
pp. 310-319 ◽  
Author(s):  
Yang Tang ◽  
Alex C. Nee ◽  
Aigang Lu ◽  
Ruiqiong Ran ◽  
Frank R. Sharp
Keyword(s):  
Gene Expression ◽  
Brain Injury ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Whole Blood ◽  
Neuronal Injury ◽  
Adult Rats ◽  
Mild Brain Injury ◽  
Microarray Analyses ◽  
Genomic Response

This study determined whether stroke and other types of insults produced a gene expression profile in blood that correlated with the presence of neuronal injury. Adult rats were subjected to ischemic stroke, intracerebral hemorrhage, status epilepticus, and insulin-induced hypoglycemia and compared with untouched, sham surgery, and hypoxia animals that had no brain injury. One day later, microarray analyses showed that 117 genes were upregulated and 80 genes were downregulated in mononuclear blood cells of the “injury” (n = 12) compared with the “no injury” (n = 9) animals. A second experiment examined the whole blood genomic response of adult rats after global ischemia and kainate seizures. Animals with no brain injury were compared with those with brain injury documented by TUNEL and PANT staining. One day later, microarray analyses showed that 37 genes were upregulated and 67 genes were downregulated in whole blood of the injury (n = 4) animals compared with the no-injury (n = 4) animals. Quantitative reverse transcription–polymerase chain reaction confirmed that the vesicular monoamine transporter-2 increased 2.3- and 1.6-fold in animals with severe and mild brain injury, respectively, compared with no-injury animals. Vascular tyrosine phosphatase-1 increased 2.0-fold after severe injury compared with no injury. The data support the hypothesis that there is a peripheral blood genomic response to neuronal injury, and that this blood response is associated with a specific blood mRNA gene expression profile that can be used as a marker of the neuronal damage.

scholarly journals Effect of agonal and postmortem factors on gene expression profile: quality control in microarray analyses of postmortem human brain

2004 ◽  
Vol 55 (4) ◽  
pp. 346-352 ◽  
Author(s):  
Hiroaki Tomita ◽  
Marquis P Vawter ◽  
David M Walsh ◽  
Simon J Evans ◽  
Prabhakara V Choudary ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quality Control ◽  
Human Brain ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Postmortem Human Brain ◽  
Microarray Analyses

Novel Stratification Scheme for AML Based on a Large-Scale DNA Microarray Analysis of CD133-Positive Blasts.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2043-2043
Author(s):  
Hiroyuki Mano ◽  
Yoshihiro Yamashita
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Expression Profile ◽  
Treatment Strategy ◽  
Large Scale ◽  
Dna Microarray Analysis ◽  
Wide Range ◽  
Microarray Analyses

Abstract AML is a clonal disorder of immature hematopoietic blasts and has a variable clinical outcome. Current classification of AML is based predominantly on the cytogenetic abnormalities and morphology of the malignant blasts and is not always helpful for optimization of treatment strategy. It is, for instance, very difficult to predict the prognosis of AML patients with a normal karyotype, who constitute ~50% of the AML population. DNA microarray analysis has the potential to provide a novel stratification scheme for AML patients, which is based on gene expression profile, and might help to predict the prognosis of, and optimize the treatment strategy for, each affected individual. However, leukemic blasts derived from bone marrow (BM) of AML-related disorders, are not homogeneous. The blasts may constitute from 20% to almost 100% of mononuclear cells (MNCs) in the marrow. Furthermore, given that many leukemic blasts possess the ability to differentiate to a certain extent, the marrow of AML patients contains not only the immature blasts (leukemic stem clone) but also differentiated blasts. A simple comparison of BM MNCs among heterogeneous AML patients is thus likely to reveal a large number of changes in gene expression that only reflect differences either in the percentage of blasts or in the differentiation ability of the blasts. To minimize such population-shift effects in microarray analyses, we established a large-scale cell depository “Blast Bank” for the storage of CD133 (AC133)-positive hematopoietic stem cell-like fractions from individuals with a wide range of hematopoietic disorders. In the present study, we have used Affymetrix HGU133 A&B microarrays to measure the expression profiles of ~33,000 genes in the Blast Bank specimens of 99 adults with AML-related disorders: 83 individuals with AML and 16 patients in the RAEB stage of MDS. In contrast to the previous microarray analyses of BM MNCs of AML, unsupervised hierarchical clustering of the subjects based on the expression profile did not separate the patients into FAB subtype-matched subgroups. Comparison of gene expression profile between the long-time and short-time survivors has identified a small number of outcome-related genes. Supervised class prediction, based on these genes, with k-nearest neighbor method or Cox proportional hazard model both succeeded to clearly separate individuals into subgroups with statistically distinct prognoses. Our analysis may pave a way toward the expression profile-based novel stratification scheme for AML.

Gene Expression Profiling of Multiple Patients with Cyclic Thrombocytopenia Reveals Consistent Profile.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 219-219 ◽  
Author(s):  
Ruchira Sood ◽  
Erin Gourley ◽  
Stanley L. Schrier ◽  
Ronald Go ◽  
James L. Zehnder
Keyword(s):  
Gene Expression ◽  
Platelet Count ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Whole Blood ◽  
Gene Clusters ◽  
Underlying Disease ◽  
Multiple Time ◽  
Platelet Counts ◽  
History Of

Abstract Cyclic thrombocytopenia (CTP) is a rare disorder characterized by periodic changes in platelet count. While some previous reports suggest an association with several cytokines, the etiology of this disorder remains poorly characterized. Using DNA microarrays, we examined the gene expression profile in peripheral whole blood at multiple time points encompassing a cycle of platelet counts from two CTP patients. We hypothesized that the variation in gene expression program in whole blood would reflect on the transcriptional changes associated with or perhaps even underlying this disease. Genome-wide cDNA microarray analysis was performed using amplified RNA obtained from 11 and 8 whole blood samples from each patient. The first patient is a 41-year old male with a 2-year history of CTP while the second patient is a 54-year old male with a 3-year history of CTP. The period of both patients’ cycles is roughly 3 weeks. No associated underlying disease has been found in both patients. With a focus on 1500 genes that change 3 fold within each group of samples we observed clusters of gene expression in whole blood that correlate with changing platelet numbers in both patients. Significant variation in expression of a cluster of interferon responsive genes during the platelet count cycle was particularly striking in both samples. Interferon (IFN) therapy is known to suppress platelet counts, and this observation suggests that aberrant IFN levels and signalling could be in part responsible for CTP. At high platelet counts, platelet transcripts were detected in whole blood RNA as inferred by high expression of previously described platelet genes including TBXAS1, TUBB1, OAZ1, SEPT5, several mitochondrial genes, NRGN and F13A1. In addition, gene clusters including known genes as well as previously uncharacterized genes were found to correlate with the peak, increasing or decreasing trends of platelet counts. Briefly, GATA2 and NFE2 expression coincided with the platelet count peak, while Tyk2 and SOCS5 expression was consistent with a rising trend of platelet counts and GATA3 and JAK2 coincided with decreasing trend of platelet counts. These results show gene expression changes associated with CTP in all cell types in whole blood and pave the way for new investigation into regulation of platelet number in a rare and fascinating disease. Gene expression profile of whole blood of two CTP patients with platelet counts ranging from high to low and then increasing again from left to right of each panel Gene expression profile of whole blood of two CTP patients with platelet counts ranging from high to low and then increasing again from left to right of each panel

scholarly journals Whole Blood Gene Expression Profile Associated with Spontaneous Preterm Birth in Women with Threatened Preterm Labor

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e96901 ◽  
Author(s):  
Yujing Jan Heng ◽  
Craig Edward Pennell ◽  
Hon Nian Chua ◽  
Jonathan Edward Perkins ◽  
Stephen James Lye
Keyword(s):  
Gene Expression ◽  
Preterm Birth ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Whole Blood ◽  
Preterm Labor ◽  
Spontaneous Preterm Birth ◽  
Blood Gene Expression ◽  
Threatened Preterm Labor

Gene Expression Profile Changes Are Commonly Modulated across Models and Species after Traumatic Brain Injury

2003 ◽  
Vol 20 (10) ◽  
pp. 907-927 ◽  
Author(s):  
Joanne E. Natale ◽  
Farid Ahmed ◽  
Ibolja Cernak ◽  
Bogdan Stoica ◽  
Alan I. Faden
Keyword(s):  
Gene Expression ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Profile Changes

Microarray analyses of the effects of NF-κB or PI3K pathway inhibitors on the LPS-induced gene expression profile in RAW264.7 cells

2009 ◽  
Vol 21 (7) ◽  
pp. 1109-1122 ◽  
Author(s):  
Sofia Dos Santos Mendes ◽  
Aurélie Candi ◽  
Martine Vansteenbrugge ◽  
Marie-Rose Pignon ◽  
Hidde Bult ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Pi3k Pathway ◽  
Raw264.7 Cells ◽  
Microarray Analyses

scholarly journals Integrating the analysis of transcriptome-wide association study and gene expression profile to identify genes associated with spondyloarthritis

2021 ◽  
Author(s):  
Jiawen Xu ◽  
Haibo Si ◽  
Yi Zeng ◽  
Yuangang Wu ◽  
Shaoyun Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Association Study ◽  
Candidate Genes ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Whole Blood ◽  
Genome Wide Association Study ◽  
Bone Diseases ◽  
Functional Enrichment

Abstract Background Spondyloarthritis(SpA) is a group of multi-factorial bone diseases influenced by genetic factors, environment and lifestyles. However, the genetic and pathogenic mechanism of SpA is still elusive. Methods Firstly, the tissue-specific transcriptome-wide association study (TWAS) of SpA was performed by utilizing the genome-wide association study (GWAS, including 3966 SpA patients and 452264 controls) summary data and gene expression weights of the whole blood and skeletal muscle. Secondly, the SpA-associated genes identified by TWAS were further compared with the differentially expressed genes(DEGs) detected by gene expression profile of SpA acquired from the Gene Expression Omnibus database (GEO, accession number:GSE58667). Finally, FUMA and Metascape tools were used to conduct gene functional enrichment and annotation analysis. Results TWAS detected 28 significant genes associated with SpA both in the whole blood and skeletal muscle, such as CTNNAL1 (PSM=0.0304, PWB=0.0096). Further comparing with gene expression profile of SpA, we identified 20 candidate genes which overlapped in TWAS, such as MCM4 (PTWAS=0.0132, PDEG=0.0275), KIAA1109 (PTWAS=0.0371,PDEG=0.0467). The enrichment analysis of the genes identified by TWAS detected 93 significant GO terms 33 and KEGG pathways, such as mitochondrion organization (GO:0007005, log10(P)= -4.29) and axon guidance(hsa04360, log10(P)= -4.26). Conclusion We identified multiple candidate genes genetically related to SpA. Our study may provide some novel clues for the further study of the genetic mechanism, diagnosis and treatment of SpA.

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