Genetics and Heritability
Since 2007, Douglas Ruderfer, PhD, MS, assistant professor in VUMC’s Division of Genetic Medicine, has centered most of his research on understanding the genetic architecture of psychiatric disorders and behavioral health traits to better quantify the role genetics play in risk and to understand the biology that leads to disease. By converting large-scale clinical data into quantitative phenotypes using prediction models, he hopes to improve power to identify genes and biological pathways that contribute to the behavioral health traits with the most pressing need for improved understanding and risk stratification, such as suicide.
“I don’t think genetics in isolation will solve the problem of identifying individuals at risk from suicide, but the question is if — and when — it can help,” said Ruderfer, an assistant professor in the departments of Medicine, Biomedical Informatics and Psychiatry and Behavioral Sciences.
By studying the genetics of different psychiatric disorders, Ruderfer’s lab hopes to tease apart the relationship between the variants contributed to one disease versus another or the symptoms that underlie those diseases. While psychiatric diseases, such as depression and schizophrenia, are commonly seen in individuals who attempt suicide, variants that contribute to those diseases don’t necessarily contribute directly to suicide.
“Evidence shows there are independent genetic factors that correlate with risk of suicide that don’t correlate with risk of psychiatric disease, even though most people who attempt suicide have a psychiatric illness,” said Ruderfer. “There’s also a difference between genes that are associated and genes that are causal. We’re working to prioritize the variants that are statistically likely to be causal by incorporating other functional information, such as gene expression.”
Because most people who consider suicide don’t actually attempt it, Ruderfer’s lab is working with colleagues such as Colin Walsh, MD, to determine clinical and genetic risk factors that lead an individual to transition from thoughts to actual behavior. In the future, they hope to explore genetics in the context of the full spectrum of suicidal phenotypes — including suicidal ideation, attempt and death — to see how variants and biology may differ.
In 2019, Ruderfer’s team published a study identifying significant and comparable heritability estimates of suicide attempt between an independent patient-reported phenotype and the clinically predicted phenotype from VUMC. The finding demonstrated that significant heritability for suicide attempt risk can be captured from applying prediction models to clinical data to generate a quantitative phenotype. The study also uncovered a new strategy for powering genetic studies when patient outcomes are not directly captured or are rare.
“The approach enabled tens of thousands of patients to be included for genetic studies using a quantitative phenotype that represents the probability of attempting suicide, allowing us to do genetic studies at-scale. It has been a challenge to perform large-scale genetic studies of suicide due to small sample sizes in any one cohort,” said Ruderfer.
Since then, the team has helped build a growing international consortium with over 27,000 cases of suicide and suicide attempt.
While Ruderfer can’t prove whether genetics will be helpful in predicting suicide risk, he hopes the information will provide improved understanding of the biological underpinnings to suicide and potentially an additional tool for clinicians when they’re on the fence about suicide risk for a patient. It may also help identify how patients will respond to specific medications for psychiatric illness, as treatment resistance is common.
“This is a situation we want to improve as soon as possible,” said Ruderfer. “If we can quickly short circuit genetic information into something that’s clinically useful, then that’s where we’re trying to get.”