Gene expression profiling in postmortem Rett syndrome brain: Differential gene expression and patient classification

被引:165
作者
Colantuoni, C
Jeon, OH
Hyder, K
Chenchik, A
Khimani, AH
Narayanan, V
Hoffman, EP
Kaufmann, WE
Naidu, S
Pevsner, J
机构
[1] Kennedy Krieger Inst, Dept Neurol, Baltimore, MD 21205 USA
[2] Kennedy Krieger Inst, Dept Cognit Neurol, Baltimore, MD 21205 USA
[3] Kennedy Krieger Inst, Dept Neurogenet, Baltimore, MD 21205 USA
[4] Johns Hopkins Univ, Sch Med, Dept Neurosci, Baltimore, MD 21205 USA
[5] Johns Hopkins Univ, Sch Med, Dept Neurol & Pediat, Baltimore, MD 21205 USA
[6] CLONTECH Labs Inc, Palo Alto, CA 94303 USA
[7] Perkin Elmer NEN Life Sci Inc, Boston, MA 02118 USA
[8] Childrens Hosp Pittsburgh, Dept Neurol, Pittsburgh, PA 15213 USA
[9] Childrens Natl Med Ctr, Res Ctr Genet Med, Washington, DC 20010 USA
[10] Johns Hopkins Univ Hosp, Dept Pathol, Baltimore, MD 21205 USA
[11] Johns Hopkins Univ Hosp, Dept Psychiat & Behav Sci, Baltimore, MD 21205 USA
关键词
D O I
10.1006/nbdi.2001.0428
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The identification of mutations in the transcriptional repressor methyl-CpG-binding protein 2 (MECP2) gene in Rett Syndrome (RTT) suggests that an inappropriate release of transcriptional silencing may give rise to RTT neuropathology. Despite this progress, the molecular basis of RTT neuropathogenesis remains unclear. Using multiple cDNA microarray technologies, subtractive hybridization, and conventional biochemistry, we generated comprehensive gene expression profiles of postmortem brain tissue from RTT patients and matched controls. Many glial transcripts involved in known neuropathological mechanisms were found to have increased expression in RTT brain, while decreases were observed in the expression of multiple neuron-specific mRNAs. Dramatic and consistent decreases in transcripts encoding presynaptic markers indicated a specific deficit in presynaptic development. Employing multiple clustering algorithms, it was possible to accurately segregate RTT from control brain tissue samples based solely on gene expression profile. Although previously achieved in cancers, our results constitute the first report of human disease classification using gene expression profiling in a complex tissue source such as brain. (C) 2001 Academic Press.
引用
收藏
页码:847 / 865
页数:19
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