Genetics of Schizophrenia in Oceanic Palau.

太平洋帕劳精神分裂症的遗传学。

基本信息

批准号：
7686280
负责人：
BERNIE DEVLIN
金额：
$ 17.36万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-09-11 至 2011-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7686280
关键词：
Accounting Affect Brain Buffers Characteristics Chromosomes, Human, Pair 5 Complex Data Diagnosis Diagnostic Disease Environment Environmental Risk Factor Family Fetal Development Fetus Gene Frequency Generations Genes Genetic Genetic Models Genetic Predisposition to Disease Genetic Variation Genome Genome Scan Genotype Goals Government Haplotypes Individual Inheritance Patterns Link Linkage Disequilibrium Literature Location Lod Score Maps Methods Modeling Molecular Mothers Nuclear Family Palau Parents Pattern Population Psychotic Disorders Reporting Research Research Personnel Resources Risk Risk Factors Sampling Schizophrenia Single Nucleotide Polymorphism Statistical Methods Stress Technology Testing Update Variant density environmental stressor falls fetal follow-up gene environment interaction genetic analysis genetic linkage analysis genetic pedigree genome wide association study genome-wide linkage novel offspring segregation statistics

项目摘要

DESCRIPTION (provided by applicant): Our principal objective is to identify genetic variation that underlies liability to schizophrenia and other psychotic disorders (henceforth called Scz) in the Oceanic population of Palau. We will accomplish this goal by capitalizing on a wide range of scientific expertise and an incredible population sample obtained by enduring relationship between the investigators and the Government of Palau for more than a decade. We now have genealogical information on many thousand individuals, who form a compelling resource for genome-wide linkage and association mapping, and represents complete ascertainment from the Oceanic population of Palau. We propose a genome-wide study of linkage and association for risk to Scz by genotyping 500 individuals for 250,000 Single Nucleotide Polymorphisms (SNPs), using the Affymetrix chip technology. We use these genotypes to search for variation conforming to the conventional hypothesis - that risk to Scz is determined directly by genetic variation carried by affected individuals. We will also use these data to test a novel hypothesis - that initial liability to Scz is generated during fetal development by one or more environmental stressors, but it is facilitated by maternal genetic vulnerability to the stress, so that the placental environment cannot adequately buffer the developing fetus. To effectively search for variation affecting risk at either level (maternal or individual), we propose to genotype essentially all individuals affected by Scz, 250, 150 mothers of individuals diagnosed with Scz, and 100 control individuals. DMA from another 450 individual will be used for follow-up analyses. A rich set of risk maternal risk factors will be collected for this population and used in our analyses. Statistical analyses will target identification of extended haplotypes that are shared much more frequently than expected by chance (in either level of risk.) Identification of such haplotypes will be facilitated by extended linkage disequilibrium characteristic of this and other Oceanic populations. Molecular and fine-mapping studies will identify risk loci. We believe this study is unique among studies of Scz genetics for its population, sample, the research team and the novelty of hypotheses and approach.

描述（由申请人提供）：我们的主要目标是确定帕劳海洋人口中导致精神分裂症和其他精神病（以下称为 Scz）的遗传变异。我们将通过利用广泛的科学专业知识和调查人员与帕劳政府十多年来的持久关系获得的令人难以置信的人口样本来实现这一目标。我们现在拥有数千人的家谱信息，这些信息构成了全基因组连锁和关联图谱的令人信服的资源，并代表了帕劳海洋人口的完整确定。我们建议通过使用 Affymetrix 芯片技术对 500 个人的 250,000 个单核苷酸多态性 (SNP) 进行基因分型，对 Scz 风险的连锁和关联进行全基因组研究。我们使用这些基因型来寻找符合传统假设的变异——Scz 的风险直接由受影响个体携带的遗传变异决定。我们还将使用这些数据来检验一个新的假设 - Scz 的初始易感性是在胎儿发育过程中由一个或多个环境压力源产生的，但母体遗传对压力的脆弱性会促进这种易感性，因此胎盘环境无法充分缓冲 Scz 的影响。发育中的胎儿。为了有效地寻找影响任一水平（母亲或个人）风险的变异，我们建议对几乎所有受 Scz 影响的个体、250 名、150 名被诊断为 Scz 的个体的母亲以及 100 名对照个体进行基因分型。另 450 名个体的 DMA 将用于后续分析。我们将为该人群收集一组丰富的孕产妇危险因素，并将其用于我们的分析。统计分析的目标是识别扩展的单倍型，这些单倍型的共享频率比偶然预期的要高得多（在任一风险水平下）。这种单倍型的识别将通过该种群和其他海洋种群的扩展连锁不平衡特征来促进。分子和精细绘图研究将确定风险位点。我们相信这项研究在 Scz 遗传学研究中是独一无二的，因为它的群体、样本、研究团队以及假设和方法的新颖性。