Schizophrenia is a lifelong illness that is characterized by hallucinations, delusions, disorganized speech, grossly disorganized behavior, and negative symptoms. Although family, twin, and adoption studies have consistently demonstrated a genetic etiology for schizophrenia, no causative genes have yet been identified. Therefore, it is crucial that we pursue an increased understanding of the underlying etiology of schizophrenia. The identification of genetic susceptibility factors in schizophrenia represents a critical step toward detecting presymptomatic individuals who are at high risk for developing the disease, designing novel therapeutic targets to decrease associated morbidity and mortality, and ultimately, preventing the disorder. With new advances in technology, more powerful approaches have emerged. One of these new approaches, called "next-generation sequencing," is a method that can detect all of the genetic sequence variants in a genome. Although sequencing every one of the three billion nucleotides that is present in the human genome is possible, it is not financially feasible to sequence the genomes of a large number of individuals, particularly because the necessary computational and bioinformatics data processing methods for whole-genome sequencing are still under development. Alternatively, the human exome contains all of the exons or coding regions in a genome (~5 Mb), and it is believed that the exome harbors much of the functional variation in humans. These recent advances set the stage for the kinds of comprehensive analysis that are necessary to identify underlying rare genetic variants, particularly in regard to family-based samples, which are the focus of this proposal. Whole exome and targeted sequence data, including data related to noncoding regions, now provide the opportunity to perform comprehensive analyses that will identify schizophrenia susceptibility genes in family-based samples. We hypothesize that the identification and analysis of rare inherited variants in families with schizophrenia will contribute to our understanding of the biological pathways that underlie schizophrenia. Specifically, we hypothesize that rare variants with relatively high penetrance will be important in familial schizophrenia pedigrees selected from the Veterans Affairs Cooperative Study Program #366 and National Institute of Mental Health Genetic Initiative on Schizophrenia. Our interdisciplinary group of investigators anticipates that we can identify these rare variants using novel analytic approaches, next- generation sequencing, and publicly available bioinformatics information. Although individually rare, these higher-penetrance forms of schizophrenia will lead to an improved understanding of the genetic and molecular basis of schizophrenia. Knowledge of these risk genes will facilitate exploration of the pathogenesis of schizophrenia at a molecular level and the development of animal and cellular models for the disease. Such research endeavors will significantly advance the search for treatments for schizophrenia.

Public Health Relevance

Schizophrenia is a major mental health disorder that typically has an onset in early adult life. The disease is a debilitating condition that requires lifelong management of symptoms, often at Veterans Affairs facilities across the nation. Unfortunately, there is no cure for schizophrenia. Therefore, the significance of this research is that the identification of schizophrenia risk genes will uncover specific molecular pathways that increase people's susceptibility to develop the disease. Our research will thus enable the development of more targeted approaches for disease prevention and treatment.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Non-HHS Research Projects (I01)
Project #
1I01BX002241-01A1
Application #
8633781
Study Section
Special Emphasis - Research on Clinical Application of Genetics (SPLC)
Project Start
2014-01-01
Project End
2017-12-31
Budget Start
2014-01-01
Budget End
2014-12-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
VA Puget Sound Healthcare System
Department
Type
DUNS #
020232971
City
Seattle
State
WA
Country
United States
Zip Code
98108