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.
|Martin, Alicia R; Gignoux, Christopher R; Walters, Raymond K et al. (2017) Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations. Am J Hum Genet 100:635-649|
|St Pourcain, B; Robinson, E B; Anttila, V et al. (2017) ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties. Mol Psychiatry :|
|Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena et al. (2017) Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa. Am J Psychiatry 174:850-858|
|Duncan, L E; Ratanatharathorn, A; Aiello, A E et al. (2017) Largest GWAS of PTSD (N=20?070) yields genetic overlap with schizophrenia and sex differences in heritability. Mol Psychiatry :|
|Weiner, Daniel J; Wigdor, Emilie M; Ripke, Stephan et al. (2017) Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders. Nat Genet 49:978-985|
|Germine, L; Robinson, E B; Smoller, J W et al. (2016) Association between polygenic risk for schizophrenia, neurocognition and social cognition across development. Transl Psychiatry 6:e924|
|Lek, Monkol; Karczewski, Konrad J; Minikel, Eric V et al. (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:285-91|
|Robinson, Elise B; St Pourcain, Beate; Anttila, Verneri et al. (2016) Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat Genet 48:552-5|
|Bulik-Sullivan, Brendan K; Loh, Po-Ru; Finucane, Hilary K et al. (2015) LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet 47:291-5|
|Robinson, Elise B; Neale, Benjamin M; Hyman, Steven E (2015) Genetic research in autism spectrum disorders. Curr Opin Pediatr 27:685-91|
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