Bipolar disorder (BPD) is a major public health priority, responsible for a vast burden of disability, personal suffering, and economic cost. Genetic susceptibility is the strongest known risk factor for BPD, and the identification of specific susceptibility genes would have enormous implications for advancing our understanding of the biology of BPD and revealing novel targets for treatment. The limited success to date of genetic studies of BPD has been due to its complex genetic architecture that likely includes many contributing loci of modest effect. Advances in population genetics and genotyping technologies have recently made the genetic dissection of complex disorders like BPD a feasible project. Genomewide association studies (GWAS) have already identified susceptibility variants underlying a range of other common medical disorders. However, it has become clear that much larger samples than are currently available will be needed to achieve such successes for BPD. This application is a response by an international consortium of investigators to RFA-MH-08-130: """"""""Genomic Parsing of Bipolar Disorder and Schizophrenia: Studies of Large Cohorts in the U.S. and Across the Globe."""""""" The proposed International Cohort Collection for Bipolar Disorder (ICCBD) will address the need for large-scale DNA and data resources by establishing a uniquely large collection of samples and data from individuals with BPD.
The specific aims of this application are 1) to ascertain and collect a large cohort of BPD cases (N = 9000) and unaffected controls (N = 9000) over five years at two U.S. sites (Boston and Los Angeles) using novel high-throughput phenotyping methods; and 2) to construct a harmonized data resource for genetic studies combining phenotypic data from the U.S. case-control sample with a parallel, separately funded European case-control sample (10,000 cases and 10,000 controls) obtained from the UK and Sweden. Separately funded genotyping and genetic analyses of these resources will fully characterize common polymorphisms and copy number variants in the full sample to detect novel risk variants and attempt replication of the most compelling prior findings. This resource, augmented by existing samples, will provide an unprecedented platform for the discovery of the genetic determinants of BPD. Bipolar disorder (BPD) is a major public health priority, responsible for a vast burden of disability, personal suffering, and economic cost. Genetic susceptibility is the strongest known risk factor for BPD, and the identification of specific susceptibility genes would have enormous implications for advancing our understanding of the biology of BPD and revealing novel targets for treatment. The limited success to date of genetic studies of BPD has been due to its complex genetic architecture that likely includes many contributing loci of modest effect. The proposed International Cohort Collection for Bipolar Disorder (ICCBD) will address the need for large-scale DNA and data resources by establishing a uniquely large collection of samples and data from individuals with BPD. ? ? ?

Public Health Relevance

Bipolar disorder (BPD) is a major public health priority, responsible for a vast burden of disability, personal suffering, and economic cost. Genetic susceptibility is the strongest known risk factor for BPD, and the identification of specific susceptibility genes would have enormous implications for advancing our understanding of the biology of BPD and revealing novel targets for treatment. The limited success to date of genetic studies of BPD has been due to its complex genetic architecture that likely includes many contributing loci of modest effect. The proposed International Cohort Collection for Bipolar Disorder (ICCBD) will address the need for large-scale DNA and data resources by establishing a uniquely large collection of samples and data from individuals with BPD.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH085542-01
Application #
7621106
Study Section
Special Emphasis Panel (ZMH1-ERB-S (07))
Program Officer
Lehner, Thomas
Project Start
2008-09-30
Project End
2013-05-31
Budget Start
2008-09-30
Budget End
2009-05-31
Support Year
1
Fiscal Year
2008
Total Cost
$2,084,814
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Bryois, Julien; Garrett, Melanie E; Song, Lingyun et al. (2018) Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun 9:3121
Fazio, Leonardo; Pergola, Giulio; Papalino, Marco et al. (2018) Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory. Proc Natl Acad Sci U S A 115:5582-5587
Gusev, Alexander; Mancuso, Nicholas; Won, Hyejung et al. (2018) Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet 50:538-548
Gandal, Michael J; Zhang, Pan; Hadjimichael, Evi et al. (2018) Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362:
Girdhar, Kiran; Hoffman, Gabriel E; Jiang, Yan et al. (2018) Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome. Nat Neurosci 21:1126-1136
Hauberg, Mads E; Fullard, John F; Zhu, Lingxue et al. (2018) Differential activity of transcribed enhancers in the prefrontal cortex of 537 cases with schizophrenia and controls. Mol Psychiatry :
Smoller, Jordan W (2018) The use of electronic health records for psychiatric phenotyping and genomics. Am J Med Genet B Neuropsychiatr Genet 177:601-612
Agrawal, A; Chou, Y-L; Carey, C E et al. (2018) Genome-wide association study identifies a novel locus for cannabis dependence. Mol Psychiatry 23:1293-1302
Curtis, David (2018) Polygenic risk score for schizophrenia is not strongly associated with the expression of specific genes or gene sets. Psychiatr Genet 28:59-65
Dobbyn, Amanda; Huckins, Laura M; Boocock, James et al. (2018) Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS. Am J Hum Genet 102:1169-1184

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