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Uncovering complex expression patterns in schizophrenia

揭示精神分裂症的复杂表达模式

基本信息

批准号：
7440266
负责人：
Karoly Mirnics
金额：
$ 11.17万
依托单位：
VANDERBILT UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-04-01 至 2009-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7440266
关键词：
Age of Onset Autopsy Biological Biometry Brain Brain region Cell physiology Collection Complementary DNA Complex Custom DNA Sequence Data Data Set Diagnosis Discipline Disease Disease Progression Experimental Designs Expressed Sequence Tags Female Freezing Functional disorder GTP-Binding Proteins Gender Gene Expression Gene Expression Profile Generic Drugs Genes Genetic Polymorphism Genome Genomics Genotype Glutamates Human Genome Immunohistochemistry Impaired cognition In Situ Hybridization Individual Knowledge Left Legal patent Light Localized Mediating Mental disorders Metabolic Metabolism Methodology Methods Molecular Molecular Profiling Neocortex Neurobehavioral Manifestations Neurons Neurosciences Neurotransmitter Receptor Oligodendroglia Oligonucleotide Microarrays Pathway interactions Pattern Pharmaceutical Preparations Phenotype Polyamines Polymers Population Genetics Prefrontal Cortex Principal Component Analysis Procedures Proteins Psychotic Disorders Recording of previous events Reporting Right-On Sampling Schizophrenia Scientist Sex Characteristics Short-Term Memory Signal Transduction Statistical Methods Structure Superior temporal gyrus Susceptibility Gene Testing Tissues Transcript Variant Work cDNA Arrays cell type follow-up improved interest male neocortical neuroimaging neurotransmission postsynaptic presynaptic research study

项目摘要

DESCRIPTION (provided by applicant): My objective is to acquire advanced and working knowledge of disciplines that will help place the microarray-obtained gene expression data into a broader biological context. For a scientist interested in genomics, ideal expertise encompasses multiple neuroscience disciplines, including (but not limited to) population genetics, biostatistics and stereological assessment of the studied tissue. This additional expertise will enable me to identify complex relationships between datasets, interpret the obtained microarray data in the light of existing linkage studies, perform limited genotyping experiments on our postmortem samples and verify the uncovered gene expression changes using non-biased, stereological sampling methods. Dysfunction of the prefrontal cortex (PFC) in schizophrenia has been associated with deficits of working memory, while functional changes in the superior temporal gyrus (STG) have been related to psychosis. Furthermore, the presentation of schizophrenia across genders has been associated with differences in age of onset, symptomathology, premorbid history, neuroimaging findings, drug responsiveness and brain structure. This application is focused around two critical questions: 1) Is there a schizophrenia-related expression profile within and across different brain regions and 2) Are schizophrenia-related expression changes different across genders? In this context, we propose to test seven specific hypotheses using 3 specific aims: Aim1 Compare gene expression pattern in 12 MALE subjects with schizophrenia and matched controls across the prefrontal (PFC) and superior temporal (STG) cortices. Aim 2. Compare gene expression pattern in 12 FEMALE subjects with schizophrenia and matched controls across the prefrontal (PFC) and superior temporal (STG) cortices. Aims 1 and 2 will share the same methodology, and compare the transcriptomes: A) Using whole genome HG_U133A and B Affymetrix microarrays. B) Using custom-made, high-sensitivity polymer eDNA microarrays. These eDNA polymer arrays, involving our proprietary probes (patent application in progress) will allow us an improved and targeted assessment of many transcripts that are too sparse to be detected by the currently available microarrays. Aim 3. Verify and localize the microarray-uncovered gene expression changes to cell types A) at transcript level using in situ hybridization; B) at protein level using immunohistochemistry and C) follow up the most promising expression changes with genotyping of postmortem samples.

描述（由申请人提供）：我的目标是获得学科的高级和工作知识，这将有助于将微阵列获得的基因表达数据置于更广泛的生物学背景下。对于一个对基因组学感兴趣的科学家来说，理想的专业知识包括多个神经科学学科，包括（但不限于）群体遗传学、生物统计学和研究组织的立体学评估。这种额外的专业知识将使我能够识别数据集之间的复杂关系，根据现有的连锁研究解释获得的微阵列数据，对我们的死后样本进行有限的基因分型实验，并使用无偏见的立体采样方法验证未发现的基因表达变化。