2/5-The Psychiatric GWAS Consortium: Integrated & Coordinated GWAS Meta-Analyses

2/5-精神病学 GWAS 联盟：综合

基本信息

批准号：
7619426
负责人：
STEPHEN V FARAONE
金额：
$ 85.47万
依托单位：
UPSTATE MEDICAL UNIVERSITY
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：
2008-09-30 至 2010-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7619426
关键词：
Abbreviations Administrator Alcohols American Anorexia Nervosa Appendix Architecture Area Attention Attention deficit hyperactivity disorder Autistic Disorder Bioinformatics Biological Bipolar Disorder Body Height Brain Budgets Caring Charge Classification Clinical Collaborations Committee Members Communication Communities Complex Computer Analysis Computers Conflict (Psychology)Confusion Consensus Country DSM-IV Data Data Set Databases Dependence Deposition Diagnosis Diagnostic Diagnostic and Statistical Manual Disease Electronic Mail Ensure Equilibrium Etiology European Family Foundations Funding Genetic Genomics Genotype Glues Heterogeneity High Performance Computing Human Genetics Illicit Drugs Individual Institution International International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10)Internet Joints Jordan Journals Knowledge Leadership Left Linux Major Depressive Disorder Manuscripts Mental disorders Meta-Analysis Metaphor Modeling National Institute of Mental Health Nature Netherlands New York City Nicotine Non-Insulin-Dependent Diabetes Mellitus Numbers Outcome Paralysed Participant Personal Satisfaction Phenotype Philosophy Policies Population Procedures Process Protocols documentation Psychiatry Publications Purpose Quality Control Recording of previous events Recurrence Request for Applications Research Research Personnel Resources Rights Risk Role Running SNP genotyping Sampling Schizophrenia Science Scientist Secure Source Specific qualifier value Staging Stratification System Teleconferences Telephone Testing Time Title Travel Update Variant Voting Week Work Writing base case control cluster computing concept day depressive symptoms design experience genome wide association study member organizational structure psychogenetics repository research study response trait

项目摘要

DESCRIPTION (provided by applicant): This application consists of five collaborative R01s submitted in response to NIMH RFA-MH-08-121, "Limited Competition for Data Deposition and Analyses of Genome Wide Association Studies of Mental Disorders (Collaborative R01)". These applications are from the Psychiatric GWAS Consortium (PGC). By the end of 2008, there will be GWAS data on 47 samples of individuals with either attention-deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BIP), major depressive disorder (MDD), or schizophrenia (SCZ). Taken together, these GWAS constitute the largest biological experiment ever conducted in psychiatry - over 80,000 subjects (59,000 independent cases/controls and over 7700 family trios), ~500,000 SNP genotypes per subject, and ~40 billion total genotypes. Although the availability of GWAS data is highly attractive, there is a real risk of conflicting claims and confusion. GWAS meta-analysis for any disease is complex and requires considerable care and expertise in order to be done validly. Given the urgent need to know if there are replicable genotype-phenotype associations, a new type of collaboration is required. To accomplish these ends, we initiated the PGC in early 2007 to conduct rigorous and comprehensive within- and cross- disorder GWAS meta-analyses. The overall philosophy of the PGC is to be as inclusive, democratic, and rapid as possible. The PGC is well-underway with a coordinating committee, five disease working groups, a cross-disorder group, statistical analysis group, and a cluster computer for data warehousing and statistical analysis. 101 scientists from 11 countries and 48 institutions. It is remarkable that all but one eligible study is participating and that no one who has joined the PGC has left. The Specific Aims of the PGC are: (1) Within-disorder meta-analyses: conduct separate meta-analyses of all available GWAS data for ADHD, AUT, BIP, MDD, and SCZ to attempt to identify convincing genotype-phenotype associations. (2) Cross-disorder analyses: it is widely suspected that the clinically-derived DSM-IV and ICD-10 definitions may not have "carved nature at the joint" with respect to the fundamental genetic architecture. There are two sub-aims: (2a) Conduct meta-analysis to attempt to identify convincing genotype-phenotype associations that are common to =2 of ADHD, AUT, BIP, MDD, and SCZ. (2b) Convene an expert working group to convert epidemiological and genetic epidemiological evidence into rigorous and explicit hypotheses about overlap amongst these disorders. The analytic plan abides to current best practices for GWAS quality control and meta-analysis, particularly in its attention to investigating sources of heterogeneity. Statistical power should be superior to any prior study in psychiatric genetics. Results will be made available as soon as possible. Finally, the PGC proposes to abide as fully as possible with the NIH's GWAS data sharing policies and we provide a detailed data sharing plan and timetable.

描述（由申请人提供）：此申请由响应NIMH RFA-MH-08-121提交的五个协作R01组成，“数据沉积的竞争有限和基因组广泛的精神疾病研究研究（协作R01）的分析”。这些应用来自精神病GWAS联盟（PGC）。到2008年底，将有47个患有注意力缺陷多动障碍（ADHD），自闭症（AUT），双相情感障碍（BIP），主要抑郁症（MDD）或精神分裂症（SCZ）的个体样本的GWA数据。综上所述，这些GWA构成了有史以来最大的生物学实验 - 超过80,000名受试者（59,000例独立病例/对照和7700多个家庭三重奏），每个受试者约500,000个SNP基因型和约400亿个基因型。尽管GWAS数据的可用性非常有吸引力，但确实存在矛盾的索赔和混乱的风险。任何疾病的GWAS荟萃分析都是复杂的，需要大量的护理和专业知识才能有效完成。鉴于迫切需要知道是否存在可复制的基因型 - 表型关联，因此需要一种新型的合作。为了实现这些目的，我们在2007年初启动了PGC，以进行严格而全面的内部和跨性别GWAS荟萃分析。 PGC的总体哲学是尽可能包容，民主和迅速。 PGC与协调委员会，五个疾病工作组，一个跨疾病组，统计分析组和一台用于数据仓库和统计分析的集群计算机相处。来自11个国家和48个机构的101位科学家。值得注意的是，除了一项合格的研究之外，还没有参加PGC的任何人参加。 PGC的具体目的是：（1）对ADHD，AUT，BIP，BIP，MDD和SCZ的所有可用GWAS数据进行单独的荟萃分析，以试图识别令人信服的基因型 - 表型关联。（2）交叉分析：广泛怀疑临床衍生的DSM-IV和ICD-10定义可能与基本遗传结构有关。有两个子IAM：（2A）进行荟萃分析，以尝试识别具有ADHD，AUT，BIP，MDD和SCZ的2的令人信服的基因型 - 表型关联。（2b）召集专家工作组，将流行病学和遗传流行病学证据转化为关于这些疾病之间重叠的严格和明确的假设。该分析计划遵守GWAS质量控制和荟萃分析的当前最佳实践，特别是在研究异质性来源的关注时。统计能力应优于任何精神遗传学的任何先前研究。结果将尽快提供。最后，PGC建议尽可能充分地遵守NIH的GWAS数据共享政策，并提供详细的数据共享计划和时间表。