# Genetic risk discovery using WGS from a population-based resource of 10,000 suicide deaths with DNA

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2022 · $400,346

## Abstract

ABSTRACT
Suicide is the 10th leading cause of death, with over 47,000 preventable deaths per year in the U.S. alone. The
rate of suicide death across the U.S. has risen by 33% over the past two decades. In spite of this dramatic
public health crisis, suicide research lags far behind other major health conditions due to the perception that
risk factors are too complex and uncontrollable for study. Importantly, while environment has undeniable
impact, evidence suggests that genetic factors play a major role in suicide death. While the study of genetic
risks is therefore promising, most studies of suicide genetics have focused on the much more common traits of
suicidal thoughts and behaviors. This strategy has allowed other research groups to acquire sufficiently
statistically-powered samples. However, suicidal behaviors can be difficult to quantify, and represent
individuals with a wide range of risk for later suicide death. Using the unique resources available to the Utah
Suicide Genetic Risk Study (USGRS), we are able to study the genetic risks of the unambiguous, high-impact
health outcome of suicide death directly. The USGRS currently has DNA from >6,000 population-ascertained
suicide deaths; this resource grows by ~650 cases per year through an unprecedented two-decade
collaboration with the Utah Department of Health’s centralized Office of the Medical Examiner (OME). We have
completed whole genome sequence (WGS) data on a subset of 281 of the Utah suicide deaths selected for
high genetic risk. We have Illumina PsychArray data on these cases and additional Utah suicides (total
N=4,382). All cases are linked to the Utah Population Database (UPDB), a statewide resource that includes
demographic data and comprehensive medical records. The UPDB phenotypic data also includes unique
information on familial risk far exceeding that of other data resources through genealogical records that go
back to the 1700s. To truly understand risk of suicide death and to implement highly effective interventions
that provide appropriate, targeted services to those most likely to die, we must understand the risks specifically
associated with suicide deaths. This proposal focuses on the identification, validation, characterization, and
replication of variants with high functional impact that implicate genes and gene pathways important for risk of
suicide death. From our WGS data, we have already detected high-impact structural variants (SVs) and single
nucleotide variants (SNVs) showing genome-wide significant gene pathway enrichment and protein-protein
interactions. These pathways are also supported by genes implicated in our genome-wide association
analyses of 3,413 Utah suicide deaths, suggesting overlap at the functional level of rare and common risk
variation. Extensive familial risk data and large sample size will allow us to select an additional subset of 760
suicides with enhanced genetic risk to replicate and extend our current findings, setting the stage fo...

## Key facts

- **NIH application ID:** 10337286
- **Project number:** 5R01MH122412-03
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Hilary Coon
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $400,346
- **Award type:** 5
- **Project period:** 2020-04-01 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10337286

## Citation

> US National Institutes of Health, RePORTER application 10337286, Genetic risk discovery using WGS from a population-based resource of 10,000 suicide deaths with DNA (5R01MH122412-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10337286. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*