Researchers detected more than 20 genes involved in suicide


Every 11 minutes, an American dies by suicide. That’s 132 people a day or more than 48,000 annually. For those left behind, the haunting question is why.

One emerging factor is family history. Perhaps the most famous example is Ernest Hemingway’s family. In addition to his own suicide in 1961, the novelist’s father, sister, brother, and niece took their own lives – in all, five deaths by suicide in three generations.

But there are also thousands of families worldwide with similar histories that are compelling researchers to investigate the genetics of suicidal acts.

In a new analysis of this risk, researchers at University of Utah Health’s Huntsman Mental Health Institute have detected more than 20 genes that could have a role in these deaths.

The study, among the first comprehensive genome-wide analyses of suicide death, also found significant genetic cross-connections to psychiatric diseases and behaviors associated with suicide, including bipolar disorder, schizophrenia, and autism spectrum disorder.

The researchers say the study establishes that suicide death is partially heritable and that it tracks in families independent of the effects of a shared environment.

Identifying these genetic risk factors, they say, could lead to better ways to predict who might be at risk of suicide and inform new strategies for preventing the worst from happening.

“What is important about this study is that, using the whole genome, we have created a genetic risk score for suicide that predicts case-control status in the lab,” says Anna R. Docherty, Ph.D., lead author of the study, quantitative geneticist at the Huntsman Mental Health Institute, and assistant professor of psychiatry at U of U Health.

“It can also help us study how genetics and environment interact to increase suicide risk. We are far from using any genetic risk score in the clinic, but this is the first step to quantifying biological risk for suicide in an individual.”

The study appears in the American Journal of Psychiatry.

Although stress, loneliness, financial strains, childhood trauma and other environmental issues can contribute to death by suicide, scientists have long thought that other factors must be involved.

“When I tell people that suicide risk is estimated to be 45% to 55% genetic, they look very surprised,” says Douglas Gray, M.D., co-author of the study and a professor of child psychiatry who specializes in suicide prevention. “They say, ‘No, it’s caused by losing a job, feeling helpless, or experiencing a romantic breakup.’ Well, if romantic breakup was the cause of suicide, we’d all be dead.”

Previously, the U of U Health team identified four gene variants that could amplify the risk of suicide based on a close examination of 43 high-risk families. But that research, like many other genetic suicide studies, focused on specific genetic segments of the human genome.

To get a more comprehensive picture of the genes potentially involved in suicide, Docherty and colleagues used computer technology to analyze millions of DNA variants in 3,413 samples obtained from the Utah Office of the Medical Examiner. Some of these subjects who had died by suicide had a family history of suicide, but others didn’t.

This is the largest suicide death sample in the world, a major improvement on previous genetic studies. These samples were compared to DNA from more than 14,000 individuals with matched ancestry from outside of the state who did not die by suicide. They also examined medical records for mental and physical health conditions.

Using a procedure called genome-wide association study (GWAS), the researchers looked at genetic variants known as SNPs (pronounced “snips”), which are essentially pieces of the genetic code.

These millions of SNPs helped them identify 22 genes potentially implicated in an increased risk of suicide death located on four chromosomes. But using the millions of SNPs together in one formula, they were also able to score and predict suicide status across two separate datasets.

They then also scored suicide deaths for genetic risks for other problems, to see whether people who died from suicide may have had risks for conditions not seen in their medical records. People who died from suicide had significantly elevated genetic risks for impulsivity, schizophrenia, and major depression – critical risk factors for suicide death.

However, the researchers stress that genetics is just one of many factors that can contribute to death by suicide.

“Death by suicide typically requires a cascade of events,” Gray says. “That cascade could include a genetic predisposition combined with untreated or undertreated mental illness, substance abuse, the strains of daily life when your brain isn’t functioning well, firearm availability, and final instigating stressor, such as a romantic breakup, that leads to tragedy.”

Among the study’s limitations are that the majority of suicide cases were from Northern European ancestry. Not every individual with a DNA sample in the analysis had available medical record data to clarify presence or absence of a mental health diagnosis. Missing data may mean an absence of a diagnosis due to care outside the state, lack of insurance, cultural factors, or stigma.

Moving forward, the researchers plan to conduct larger and more diverse suicide death studies that will include people of Mexican and Native American ancestries.

“This study and others that follow are going to allow us to better understand the constellation of risk factors associated with suicide and to help decrease stigma relating to it,” Docherty says.

“It will hopefully encourage families with a history of suicide to learn more and discuss risk and protective factors, as they would talk about other medical conditions like high blood pressure or cardiovascular disease.”

Nearly 800,000 preventable suicide deaths occur each year.1 While environmental factors are undeniably important, evidence suggests that genetic factors play a major role in suicide death, with estimated heritability from meta-analyses of close to 50%.2,3

Identification of suicide genetic risk factors is critical to understanding the biological basis of suicide risk and improving prevention. However, to date only a fraction of the genetic variation influencing suicide risk has been accounted for with most studies focusing on suicidal behaviors (e.g. ideation or attempt) as opposed to suicide death.4

Most genetic studies of suicide focus on common genetic risk variants (variants carried by more than 1% of a given population), despite the high likelihood that rare variants (minor allele frequency; MAF <1%) also significantly contribute to suicide risk.5,6

Discoveries of rare genetic risk variants for other complex psychiatric and non-psychiatric medical conditions (e.g., lipid disorders7, Alzheimer’s disease8, schizophrenia9, obesity10,11) have identified functional gene pathways and now explain a sizeable proportion of the genetic risk for these disorders.

Functional variants that alter gene function or expression tend to be rare in populations because natural selection acts to reduce their prevalence.13 Identification of risk genes and pathways affected by these rare but high-impact variants is critical to the development of targeted interventions.

A primary reason why most research focuses on common variants is that detection and reliable estimates of frequency of rare variants in both case and control groups requires very large genetic studies,14,15 often including many tens of thousands of carefully chosen samples to achieve statistical power.16

Whole genome sequencing (WGS) and whole exome sequencing (WES) studies are becoming more common, yet costs involved are considerable and these studies often have more modest sample sizes compared with genome-wide association studies (GWAS) using cheaper genotyping arrays.

Large genetic datasets from genotyping arrays are an overlooked source of important rare variation. Although most of the content on genotyping arrays is focused on common variants, carefully chosen, medically relevant, rare variants are often also included on these platforms.

The large, population-based genetic dataset available in the Utah Suicide Genetic Risk Study (USGRS) provides unique opportunities to uncover both common and rare variants leading to risk of suicide death. Genetic data from 4,382 suicide death cases were generated with the Illumina PsychArray BeadChip, a high-density, genome-wide microarray developed specifically for large-scale genetic studies of psychiatric disorders.

The PsychArray includes 265,000 common tag-SNPs as well as 245,000 markers from Illumina’s Exome BeadChip, developed to capture coding variants that alter gene function as well as 50,000 additional markers associated with psychiatric conditions ( These latter markers were selected specifically for their potential functional impact and relevance to psychiatric disease.

Modern GWAS focus on the detection and analysis of common genetic risk factors, and SNPs with MAF <1%, such as the rare variants included on the PsychArray, are traditionally removed as being less informative for this study design. However, the removal of content specifically chosen for both functional and disease relevance represents a missed opportunity for the discovery of rare, more highly penetrant risk factors for complex psychiatric traits.

There has been no large-scale effort to evaluate the PsychArray’s rare variant content in the context of complex psychiatric traits. Due to the popularity of the PsychArray as a genotyping platform, content traditionally not considered in GWAS is an untapped resource to investigate rare variants involved in suicide, as well as other complex psychiatric traits.

This analysis requires special methodological considerations, including rigorous attention to quality control issues followed by comparison with external control data as well as secondary molecular validation of variants of interest.

Here, we investigate the role of rare variants in suicide death. First, we identified rare variant content on the PsychArray that is significantly associated with suicide death using a case-control design, comparing USGRS cases against controls from the large gnomAD resource.

Next, we prioritized rare variants by comparing with an independent control cohort genotyped on the PsyschArray, and validated these variants in the USGRS with sequencing data. Follow-up analyses of these variants identified important mechanistic pathways and cross-trait associations. Finally, we characterized the phenotypic attributes of all suicide cases with these rare variants.

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Source: University of Utah


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