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Joint Mapping of Genome-Wide Gene Expression and Association in a Schizophrenia D

Joint Mapping of Genome-Wide Gene Expression and Association in a Schizophrenia D
精神分裂症 D 中全基因组基因表达和关联的联合作图
批准号:
7861092
负责人:
Alan R Sanders
金额:
$128.11万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2011-08-31

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): The broad goal of this project is to initiate a genome-wide study of gene expression of schizophrenia (SZ), targeting over 25,000 annotated genes, in a repository sample with available genome-wide association study (GWAS) data. The basic hypothesis of this proposal is that gene regulation mechanisms are involved in the etiology of SZ, and that gene expression data will be instrumental to the interpretation of SZ GWAS results and for guiding laboratory efforts, including large re-sequencing initiatives. The specific aims are: AIM 1 - Determine genome-wide gene expression levels utilizing the Illumina HT-12 array in a well-powered sample comprised of Epstein Barr Virus (EBV) transformed B lymphocytes (lymphoblastoid cell lines, LCLs) from 1,011 severely affected cases and 1,011 psychiatrically screened controls from the Molecular Genetics of SZ (MGS) sample. The experiment will proceed with full attention to quality control (QC) and the experimental design will allow for the systematic analysis of genetic and non-genetic variance. AIM 2 - Search for eQTLs that regulate the expression of genes associated with SZ. First, expressed sequences that show case-control differences will be sought, and for these gene transcripts, association between the expression levels and SNPs in cis in the gene expression sample (1,011 cases and 1,011 controls) will be tested. Next association between these identified SNPs and SZ will be tested in the rest of the MGS EA sample (1,671 cases and 1,643 controls). A genome-wide search for trans eQTLs will also be performed, however, with decreased statistical power compared to cis eQTLs. While the field of gene expression in human disease is growing at an accelerated pace, this proposal addresses the dearth of well-powered microarray expression studies in SZ (and psychiatric) genetics. This proposal only asks for support for the measurements of DNA transcription, and statistical and bioinformatic analyses thereof. The proposed GWES will greatly augment the value of this public sample, which has been the most accessed clinical sample for NIMH in dbGAP, greatly amplifying the overall impact of the proposed experiments. An already established LCL NIMH resource at the Rutgers University Cell and DNA Repository (RUCDR) will be accessed, and the gene expression results will be rapidly shared with the scientific community through an NIMH sponsored mechanism. Future plans include extending our study of gene expression to the full transcriptome with the aim of integrating genome variation, DNA transcription, and proteomic data relevant to the study of SZ genetics (and biomedical sciences in general), and participating in meta-analyses of gene expression in SZ. SZ is a devastating and costly psychiatric disorder exhibiting complex genetics. The joint analysis of expression and GWAS data is expected to lead to discoveries of mechanisms of SZ susceptibility otherwise obscured to either method in isolation, and create new research opportunities by motivating mechanistically based experiments, e.g., models where pharmacology can be tested hopefully rapidly leading to new treatment strategies. PUBLIC HEALTH RELEVANCE: This study aims to uncover information about differences in gene expression between individuals with schizophrenia versus controls, their relationship to previously studied genetic variation, and the joint analysis thereof. Besides informing important areas of biology, the study especially aims to better understand genetic contributions to schizophrenia, as a means to better understand how disease develops. This knowledge should assist in efforts to prevent and treat this devastating and costly illness.
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Gene Expression in an African American Schizophrenia Dataset
Gene Expression in an African American Schizophrenia Dataset
Gene Expression in an African American Schizophrenia Dataset
Gene Expression in an African American Schizophrenia Dataset
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