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Psychiatric Genomics Consortium

Consortium conducting meta-analyses of genome-wide genetic data for psychiatric disease. The basic idea is that individual studies are generally too small to identify robust and replicable associations. Meta-analysis is a widely-used technique that can combine information across studies. The PGC has focused on five critically-important disorders: autism, attention-deficit hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia. They have also done the initial cross-disorder analysis to look for genetic variants that predispose to multiple disorders. Additional GWAS data may become available for other disorders like anorexia nervosa (AN), Tourette syndrome (TS), and obsessive-compuls ive disorder (OCD). The initial intent of the PGC was to investigate the common single nucleotide polymorphisms (SNPs) genotyped on commercial arrays. The focus has expanded to include structural variation (copy number variation) and uncommon or rare genetic variation. To participate you are asked to upload the data from your study to the central computer used by this consortium. The Genetic Cluster Computer will serve as the data warehouse and analytical platform for this study (http://www.geneticcluster.org). When the data from your study have been incorporated, your analyst will get an account on the central server and access to all GWAS genotypes, phenotypes, and meta-analytic results relevant to the data you deposited and the aims in which you participate. The appropriate people from your group will also become members of the relevant working groups. These steps will occur as soon as possible (under a week). It is understood that groups will share their data with the PGC at a time that is appropriate for them and their study. Published PGC results can be viewed using ricopili, a web site that generates high-resolution images of PGC results. This web resource takes as input a gene name or genomic region, and produces a plot of PGC findings in genomic context. Results files can be obtained by any PGC member for any disease to which they contributed data. These files can also be obtained by application to the NIMH Genetics Repository. * Individual-level genotype and phenotype data: Requires application, material transfer agreement, and informed consent consideration. PGC analytic datasets can be obtained by application to the controlled-access NIMH Genetics Repository. Some datasets are also in the controlled-access dbGaP and Wellcome Trust Case-Control Consortium repositories. These data can be obtained by any credible investigator. PGC members can also receive back cleaned and imputed data and results for the samples they contributed to PGC analyses. * NHGRI GWAS Catalog: This catalog contains updated information about all GWAS in biomedicine, and is usually an excellent starting point to find a comprehensive list of studies.

URL: https://pgc.unc.edu/

Resource ID: nlx_143769     Resource Type: Resource     Version: Latest Version

Keywords

structural variation, genetic variation, single nucleotide polymorphism, attention deficit-hyperactivity disorder, bipolar disorder, schizophrenia, mental disease, one mind ptsd, data sharing, visualization, genome-wide association study, genomic, genotype, phenotype, psychiatry, gwas, copy number variation

Funding Information

A wide range of national international and commercial funders, Netherlands Genetic Cluster Computer, Hersenstichting Nederland, NIMH,

Availability

Available to members for any disease to which they contributed data or by application to individuals

Species

human

Related To

Ricopili, GWAS: Catalog of Published Genome-Wide Association Studies, dbGaP at NCBI, Wellcome Trust Case Control Consortium

Abbreviation

PGC

Parent Organization

Synonyms

Psychiatric GWAS Consortium

Additional Resource Types

Computational Hosting, Community Building Portal

Related Disease

Mental disease, Attention deficit-hyperactivity disorder, Bipolar Disorder, Schizophrenia, Major Depressive Disorder, Autism, Cross-disorder

Supercategory

Resource

Original Submitter

Anonymous

Version Status

Curated

Submitted On

12:00am November 22, 2011

Originated From

SciCrunch

Changes from Previous Version

  • Additional Resource Types was changed

Version 4

Created 2 weeks ago by Christie Wang

Version 3

Created 2 weeks ago by Christie Wang

Version 2

Created 2 weeks ago by Christie Wang

Version 1

Created 4 years ago by Anonymous

Dissecting the phenotype in genome-wide association studies of psychiatric illness.

  • Cross-Disorder Phenotype Group of the Psychiatric GWAS Consortium
  • Br J Psychiatry
  • 2009 3

Over the past 2 years genome-wide association studies have made major contributions to understanding the genetic architecture of many common human diseases. This editorial outlines the development of such studies in psychiatry and highlights the opportunities for advancing understanding of the biological underpinnings and nosological structure of psychiatric disorders.

Genome-wide association studies: a primer.

  • Corvin A
  • Psychol Med
  • 2010 7

There have been nearly 400 genome-wide association studies (GWAS) published since 2005. The GWAS approach has been exceptionally successful in identifying common genetic variants that predispose to a variety of complex human diseases and biochemical and anthropometric traits. Although this approach is relatively new, there are many excellent reviews of different aspects of the GWAS method. Here, we provide a primer, an annotated overview of the GWAS method with particular reference to psychiatric genetics. We dissect the GWAS methodology into its components and provide a brief description with citations and links to reviews that cover the topic in detail.

The psychiatric GWAS consortium: big science comes to psychiatry.

  • Sullivan PF
  • Neuron
  • 2010 21

The Psychiatric GWAS Consortium was founded with the aim of conducting statistically rigorous and comprehensive GWAS meta-analyses for five major psychiatric disorders: ADHD, autism, bipolar disorder, major depressive disorder, and schizophrenia. In the era of GWAS and high-throughput genomics, a major trend has been the emergence of collaborative, consortia approaches. Taking advantage of the scale that collaborative consortia approaches can bring to a problem, the PGC has been a major driver in psychiatric genetics and provides a model for how similar approaches may be applied to other disease communities.

Genomewide association studies: history, rationale, and prospects for psychiatric disorders.

  • Psychiatric GWAS Consortium Coordinating Committee
  • Am J Psychiatry
  • 2009 4

OBJECTIVE: The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses. METHOD: A literature review was carried out, power and other issues discussed, and planned studies assessed. RESULTS: Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress. CONCLUSIONS: GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

A framework for interpreting genome-wide association studies of psychiatric disorders.

  • Psychiatric GWAS Consortium Steering Committee
  • Mol. Psychiatry
  • 2009 19

Genome-wide association studies (GWAS) have yielded a plethora of new findings in the past 3 years. By early 2009, GWAS on 47 samples of subjects with attention-deficit hyperactivity disorder, autism, bipolar disorder, major depressive disorder and schizophrenia will be completed. Taken together, these GWAS constitute the largest biological experiment ever conducted in psychiatry (59 000 independent cases and controls, 7700 family trios and >40 billion genotypes). We know that GWAS can work, and the question now is whether it will work for psychiatric disorders. In this review, we describe these studies, the Psychiatric GWAS Consortium for meta-analyses of these data, and provide a logical framework for interpretation of some of the conceivable outcomes.