Modeling Dimensionality and Genetic Heterogeneity in Schizophrenia

精神分裂症的维度和遗传异质性建模

基本信息

批准号：
9088679
负责人：
Anna R. Docherty
金额：
$ 2.75万
依托单位：
VIRGINIA COMMONWEALTH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-03-15 至 2016-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9088679
关键词：
Accounting Address Age of Onset Alcohol consumption Applied Genetics Architecture Autopsy Bioinformatics Biological Brain Chromosome Mapping Classification Clinical Collaborations Complex Data Dimensions Disease Environment Gene Expression Genes Genetic Genetic Heterogeneity Genetic Polymorphism Genetic Risk Genomics Goals Heritability Heterogeneity Human Individual Interview Lead Machine Learning Malignant neoplasm of lung Malignant neoplasm of ovary Maps Measurement Measures Mental disorders Mentors Meta-Analysis Methods Mission Modeling Molecular Molecular Genetics National Institute of Mental Health Nicotine Outcome Performance Personality Phenotype Population Prefrontal Cortex Preventive Intervention Process Psychotic Disorders Public Health Questionnaires Research Research Domain Criteria Research Training Risk Risk Assessment Risk Factors Sample Size Sampling Schizophrenia Schizotypal Personality Disorder Series Signal Transduction Statistical Methods Stratification Structure Students Subgroup Suicide attempt Symptoms Techniques Testing Time Tissue-Specific Gene Expression Training Transcript Translational Research Trees Validation Variant Wisconsin aged base brain tissue burden of illness case control clinical risk cocaine use density differential expression disorder subtype endophenotype gene function genetic pedigree genetic variant genome wide association study genome-wide genomic data improved innovation insight malignant breast neoplasm marijuana use mind control novel programs public health relevance response severe mental illness sex substance misuse symptomatology theories training opportunity trait transmission process

项目摘要

DESCRIPTION (provided by applicant): Schizophrenia (SZ) represents a significant and costly public health burden. Recently, we have witnessed the emergence of the first molecular insights into the etiopathogenic mechanisms of SZ, via the first genome-wide association studies (GWAS) with sufficient case-control sample sizes to detect allelic effects. Importantly, a polygenic signature, which includes genome-wide significant common genetic variants of small effect, has been clearly demonstrated to influence SZ risk. The availability of well-defined risk factors makes it possible, for the first time, to address several critical questions about the genetic architecture of SZ and its component phenotypes and endophenotypes. The overarching goals of this K01 proposal are 1) to test polygenic risk score prediction of dimensional SZ and schizotypy phenotypes across large case, high-density SZ pedigree, and prodromal-aged GWAS samples, and 2) to develop and test, with leaders of the Psychiatric Genomics Consortium, innovative statistical methods to identify and characterize "genetic subtypes" of SZ. This proposal delineates a series of training and research goals for the candidate that incorporates strengths from phenotypic assessment, statistical genetics, and molecular genetics and combines samples reflecting a broad range of genetic risk. The candidate will capitalize on previously established expertise in schizotypy and clinical risk assessment, as well as expertise in the familial transmission of dimensional traits, to establish a program of translational research wherein the application of statistical genetic/bioinformatic techniques to genetic subtyping analyses will be used to generate promising candidates for further exploration in human genomic data. Empirically-based genetic subtyping methods will be developed and tested in the largest SZ case sample to date, and subtypes will be characterized with respect to dimensional phenotypic traits. Top loci hits in subtype analyses of dimensional symptoms will be validated in secondary analyses of differential gene expression in post-mortem SZ brain. This will allow for a detailed analysis of function at both the SNP and gene levels, and will provide the candidate with substantive training in both statistical and molecular genetics methods. The institutional environment is ideal for the candidate's goal of developing a comprehensive program in SZ research, and the proposed research represents an important contribution toward advancing the understanding of SZ through a combination of clinical, statistical, molecular, and translational methods, consistent with the mission of the NIMH.

描述（由申请人提供）：精神分裂症（SZ）是一种重大且昂贵的公共卫生负担。最近，我们通过首次全基因组关联研究（GWAS）见证了对 SZ 发病机制的首次分子见解的出现。重要的是，多基因特征（包括小效应的全基因组显着常见遗传变异）已被明确证明可以影响明确风险的可用性。这些因素首次使得解决有关 SZ 遗传结构及其组成表型和内表型的几个关键问题成为可能。该 K01 提案的总体目标是 1) 测试维度 SZ 和分裂型表型的多基因风险评分预测。跨大病例、高密度 SZ 谱系和前驱年龄 GWAS 样本，2) 与精神病基因组学的领导者一起开发和测试联盟，用于识别和表征 SZ“遗传亚型”的创新统计方法该提案为候选人描绘了一系列培训和研究目标，其中结合了表型评估、统计遗传学和分子遗传学的优势，并结合了反映广泛的样本。候选人将利用先前在精神分裂和临床风险评估方面建立的专业知识，以及在维度特征的家族遗传方面的专业知识，建立一个转化研究计划中，统计遗传/生物信息学技术在遗传亚型分析中的应用将用于产生有希望的候选者，以进一步探索人类基因组数据。将开发基于经验的遗传亚型方法，并在最大的 SZ 病例样本中进行测试。维度症状亚型分析中的热门基因座命中将在死后 SZ 大脑中差异基因表达的二次分析中得到验证。对 SNP 和基因水平的功能进行详细分析，并将为候选人提供统计和分子遗传学方法方面的实质性培训，该机构环境对于候选人开发 SZ 研究综合计划的目标和拟议的目标来说是理想的。研究通过结合临床、统计、分子和转化方法，为增进对 SZ 的理解做出了重要贡献，这与 NIMH 的使命一致。