This is the final submission of the collaborative R01 MH094421 Psychiatric GWAS Consortium: Genomic Follow-Up Next-Gen Sequencing & Genotyping. The overall goal of this application is ambitious:
we aim to generate a trustworthy, high-confidence maps of the genetic architecture of centrally important psychiatric diseases. Such maps consist of systematic and comprehensive evaluation of the allelic spectrum for these disorders including rare exonic, common SNP, and copy number variation. The feasibility of our aims is supported by the track record of the first iteration of the Psychiatric GWAS Consortium (PGC1) where we united nearly all major groups in the field into a harmonious and functional entity and completed our initial aims to a high scientific standard. Psychiatric diseases are compelling targets for intensive research: they are mostly idiopathic, first-rank public health problems, and cause enormous morbidity, mortality, and personal/societal cost. Consistent with the NIH mission, our goal is to elucidate fundamental knowledge of these diseases. In this PGC2 application, we propose to capitalize on prior NIH investments and on the success of PGC1 for the next logical set of aims. The PGC2 aims are large-scale (largest sample sizes ever in the field) and comprehensive (via the careful application of multiple genomic-scale technologies). Our focus is comprehensive in other senses - the PGC encompasses nearly the entire field, and we aim to elucidate the allelic spectrum of these disorders by integrating empirical data for all readily measurable types of genetic variation of etiological relevance (common SNP, rare exonic, and rare and common copy number variation - what we term the map). There are three analytic aims - systematically to assess copy number variation, to create a pipeline for the analysis of exome data (and eventually whole-genome data), and to investigate genetic associations that span traditional disease boundaries. Finally, we propose to develop the PsychChip a custom 20,000 probe array targeting common SNP, exonic, and CNVs that would then be used to genotype 115,082 subjects. The PGC2 impact is potentially very large - a fundamental understanding of the genetics of these diseases would be a major milestone in psychiatry and in biomedicine.
Psychiatric disorders cause enormous human suffering and cost to society. Our goal is rapidly to learn more about the genetics of some of these disorders. We propose to do this via the largest consortium ever constructed in the field, and by the use of several genetic technologies.
|(2018) Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet 50:668-681|
|Sullivan, Patrick F; Agrawal, Arpana; Bulik, Cynthia M et al. (2018) Psychiatric Genomics: An Update and an Agenda. Am J Psychiatry 175:15-27|
|Bergen, Sarah E; Ploner, Alexander; Howrigan, Daniel et al. (2018) Joint Contributions of Rare Copy Number Variants and Common SNPs to Risk for Schizophrenia. Am J Psychiatry :appiajp201817040467|
|Marshall, Christian R (see original citation for additional authors) (2017) Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet 49:27-35|
|Bigdeli, T B; Ripke, S; Peterson, R E et al. (2017) Genetic effects influencing risk for major depressive disorder in China and Europe. Transl Psychiatry 7:e1074|
|Direk, Nese; Williams, Stephanie; Smith, Jennifer A et al. (2017) An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype. Biol Psychiatry 82:322-329|
|Pers, Tune H; Timshel, Pascal; Ripke, Stephan et al. (2016) Comprehensive analysis of schizophrenia-associated loci highlights ion channel pathways and biologically plausible candidate causal genes. Hum Mol Genet 25:1247-54|
|Agrawal, Arpana; Edenberg, Howard J; Gelernter, Joel (2016) Meta-Analyses of Genome-Wide Association Data Hold New Promise for Addiction Genetics. J Stud Alcohol Drugs 77:676-80|
|Bigdeli, Tim B; Ripke, Stephan; Bacanu, Silviu-Alin et al. (2016) Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness. Am J Med Genet B Neuropsychiatr Genet 171B:276-89|
|Edwards, Alexis C; Bacanu, Silviu-Alin; Bigdeli, Tim B et al. (2016) Evaluating the dopamine hypothesis of schizophrenia in a large-scale genome-wide association study. Schizophr Res 176:136-140|
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