Genome-wide association (GWA) is widely viewed as the most powerful, systematic and unbiased genetic approach to the study of the common disease/common variant (CDCV) hypothesis of complex disorders like schizophrenia. We propose to conduct a single- stage GWA study of schizophrenia in an ethnically homogeneous sample previously collected in Ireland. The sample of 2357 affected individuals and 2000 or 5000 controls provides considerable power to detect genes of modest effect. Our overall goal is to contribute to the conclusive identification of genetic variation that influences the liability to schizophrenia. In order to achieve this, we plan to 1) collect 900,000 individual DNA polymorphism genotypes for each member of the sample, 2) perform a primary analysis of this data for association with schizophrenia, and in secondary analyses to 3) assess weighted significance testing based on prior genetic or biological data, other phenotype data available and clinical features of illness, and 4) assess multi-locus, pathway and system associations, and 5) to recontact, reconsent and resample the affected individuals for contribution to the NIMH repository.

Public Health Relevance

Schizophrenia is a common and often severe mental illness with a population frequency of ~1 percent; substantial numbers of individuals in the US or other populations are affected. The illness is a major public health burden because of the early onset, non-fatal course and need for long-term care for many patients. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH083094-01
Application #
7447591
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Lehner, Thomas
Project Start
2008-09-30
Project End
2012-05-31
Budget Start
2008-09-30
Budget End
2009-05-31
Support Year
1
Fiscal Year
2008
Total Cost
$1,150,948
Indirect Cost
Name
Virginia Commonwealth University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
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Adkins, Amy E; Hack, Laura M; Bigdeli, Tim B et al. (2017) Genomewide Association Study of Alcohol Dependence Identifies Risk Loci Altering Ethanol-Response Behaviors in Model Organisms. Alcohol Clin Exp Res 41:911-928
Edwards, Alexis C; Bigdeli, Tim B; Docherty, Anna R et al. (2016) Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes. Schizophr Bull 42:279-87
Han, Jun; Walters, James T R; Kirov, George et al. (2016) Gender differences in CNV burden do not confound schizophrenia CNV associations. Sci Rep 6:25986
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Franke, Barbara; Stein, Jason L; Ripke, Stephan et al. (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19:420-431
Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Jan et al. (2015) IQ and schizophrenia in a Swedish national sample: their causal relationship and the interaction of IQ with genetic risk. Am J Psychiatry 172:259-65
Docherty, Anna R; Bigdeli, T Bernard; Edwards, Alexis C et al. (2015) Genome-wide gene pathway analysis of psychotic illness symptom dimensions based on a new schizophrenia-specific model of the OPCRIT. Schizophr Res 164:181-6
Andreassen, O A; Harbo, H F; Wang, Y et al. (2015) Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci. Mol Psychiatry 20:207-14
Heron, Elizabeth A; Cormican, Paul; Donohoe, Gary et al. (2014) No evidence that runs of homozygosity are associated with schizophrenia in an Irish genome-wide association dataset. Schizophr Res 154:79-82

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