DESCRIPTION (provided by applicant): Suicide is a significant health concern. There are over 33,000 suicide deaths per year in the United States, accounting for 1.3% of all fatalities (WISQARS, 2005), and about 2% of deaths worldwide (World Health Organization, 2000). Aggregated data across multiple large studies has produced heritability estimates of completed suicide of 45%. The Rocky Mountain States have much higher age-adjusted suicide rates, and Utah is consistently in the top ten. In Utah, suicide is the leading cause of death for males between the ages of 15 and 54. Our project will use a large DNA resource already collected from decedents through a long-term collaboration with the centralized Utah State Office of the Medical Examiner (OME). Records of >2,000 decedents with DNA were linked to the Utah Population DataBase (UPDB), a computerized genealogy database that includes medical data, demographic information, and genealogical data for over 6.5 million individuals. Using the UPDB, we identified 27 high risk families containing ~150 suicide decedents with DNA. As a rare condition (1-2/10,000 per year), aggregation of suicide completion in high-risk pedigrees represents a unique resource to study risk factors. We will use the genealogical, demographic, and medical data in the UPDB to identify and focus on the most compelling of these high-risk suicide pedigrees; those that contain both a significant excess of suicide completion and that exhibit the most discriminating characteristics compared to non-familial suicide. By using these phenotypic comparisons to choose the most unique high-risk pedigrees, we will increase homogeneity and strengthen our ability to isolate genetic variants related to suicide risk. These discriminating phenotypes will also identify non-genetic factors associated with high familial risk that can foster other epidemiological studies, and can facilitate future gene x environment analyses. We currently have in hand a large resource of DNA and phenotype information from ~2500 additional Utah suicide decedents. This sample will grow to over 4000 DNAs by the end of the study, the largest population-based sample of DNA from suicide decedents ever collected. We propose to focus on unusual high-risk suicide pedigrees with increased likelihood for more penetrant rare genetic variation, followed by confirmation and follow-up analyses in large cohorts of Utah decedents and publicly-available psychiatric data sets. The detection of genetic variants associated with suicide could shed light on biological pathways leading to suicide risk in the population, or in association with specific disorders. We have chosen state-of-the-art analytical methods, and have assembled a team of experts (analytic, phenotypic, and molecular) to explore these unique data resources to identify genetic risk factors for suicide. The detection of rare variants associated with suicide could shed light on biological pathways leading to suicide risk in the population, or in association with specific disorders.

Familial genetic risk for suicide will be determined by selecting the most compelling high-risk pedigrees through comparisons to pedigrees where no excess familial risk of suicide was found. Genetic risk will be determined through the study of whole genome and whole exome sequence data from suicides in these high- risk families with existing DNA. Follow-up will use > 4000 Utah suicides with DNA, and data/DNA reference and control sequence data and data from external psychiatric studies.