# Genome-Wide Association Analysis of Suicide Death

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2022 · $640,193

## Abstract

PROJECT SUMMARY
The current proposal seeks to clarify the mechanisms underlying suicide death. Suicide constitutes a severe
and steadily worsening public health crisis, and suicide prevention has become a primary focus of NIMH
efforts. Aggregated data across multiple large genetic studies yield heritability estimates of suicide death at
approximately 45%. However, research on risk factors to date has been largely confined to epidemiological
observations, with a lack of access to molecular genetic data on suicide death. This lack of access has
resulted in an overwhelming focus on the genetic study of subthreshold phenotypes—ideation and attempt—
which very rarely result in suicide. Currently, positive predictive values for suicide attempt are high (.9), while
positive predictive values for suicide death continue to hover near zero. This research team has
unprecedented access to DNA from thousands of independent, population-based suicide deaths from the Utah
Office of the Medical Examiner. DNA resources are enhanced by a wealth of electronic medical record and
environmental exposure data on all suicides, using the Utah Population Database, a unique resource of >10
million residents. Due to the extreme and unambiguous nature of suicide relative to psychiatric phenotypes,
genotyping and genome-wide association analysis of the first 3,413 cases and 14,848 matched controls has
already resulted in genome-wide significant signals and strong polygenic signal. Five novel, rare missense
SNPs are also significantly associated with suicide death in these preliminary data. By genotyping additional
and incoming suicide deaths, this project aims to replicate and significantly expand on genetic discoveries. In
addition, approximately 20% of the population-based suicides evidence significant ancestry admixture,
providing valuable diversity to enhance both discovery and generalizability. This research team will work
closely in partnership with the Psychiatric Genomics Consortium and UK Biobank to examine new data on
suicide death, test clinically informative risk models, and leverage large external cohorts to model complex
suicide etiologies. Some of the high-impact deliverables from this project include a) comprehensive co-
morbidity, mode of death, and risk factor statistics from the largest population-based suicide cohort to date, b)
the first genome-wide data and summary statistics for suicide death, linked to a wealth of risk phenotypes,
polygenic risks, and diagnoses (e.g., ADHD, affective disorders, alcohol use disorder, autism spectrum
disorder, pain, mania, metabolic conditions, opiate use, pregnancy, psychosis), c) genetic correlation estimates
of suicide death with a range of phenotypes, for the development of genetic risk models, and d) clinically
informative genetic and environmental predictors of suicide, accounting for sex, ancestry, and age.

## Key facts

- **NIH application ID:** 10432045
- **Project number:** 5R01MH123619-03
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Anna R. Docherty
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $640,193
- **Award type:** 5
- **Project period:** 2020-08-17 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10432045

## Citation

> US National Institutes of Health, RePORTER application 10432045, Genome-Wide Association Analysis of Suicide Death (5R01MH123619-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10432045. Licensed CC0.

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