Predicting Suicide: Using Brain Imaging Techniques to Identify At-Risk Individuals

Snigdha Nandipati | June 24, 2017

Predicting Suicide: Using Brain Imaging Techniques to Identify At-Risk Individuals

Suicide is a common end result for many people with psychiatric disorders, including depression, schizophrenia, and bipolar disorder. Understanding the underlying neural mechanisms in these disorders can reveal the beginnings of suicidal thoughts and predict individuals especially prone to suicide. A recent study at Yale has focused on several brain imaging techniques to predict and possibly prevent suicide in individuals with bipolar disorder.

Hilary Blumberg, John and Hope Furth Professor of Psychiatric Neuroscience, is the leading author on this study. Blumberg’s lab performed a cross-sectional study of adolescents and young adults with bipolar disorder. These individuals were divided into two groups: those who had previously attempted suicide (“attemptors”), and those who had not done so (“non-attemptors”). “We chose to study the adolescent population, because that’s when [mood disorders and suicide attempts] start to emerge ,” Blumberg said. “We would be able to look for clues about how suicidal thoughts develop and how the risk develops if we study it in young adults and adolescents.” Blumberg and her team used multiple modes of neuroimaging, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI), to scan the brains of attemptors and non-attemptors. They noticed several important structural abnormalities in the brain scans of the attemptor group, including decreased gray matter volume and decreased structural and functional connectivity between frontotemporal regions that control emotion and impulse.

“These findings suggest that the frontal regions involved in this circuitry are not working as well as they should to regulate emotion and control impulsivity.” Blumberg said. “This can lead to more extreme emotional pain, difficulties in finding alternatives to suicide attempt, and greater likelihood of acting on suicidal impulses.”

However, the ability to predict individual suicide risk from brain images is still in the research phase. “For example, there’s no way to hold up a brain scan of one individual and a brain scan of another individual and know which one has bipolar disorder, or which one has depression, or which one is going to attempt suicide,” Blumberg explained. Current studies in the field compare groups of individuals with and without suicide risk and extrapolate subtle differences between the two groups. “It would take a lot more research before we would be able to take a brain scan of an individual and determine their suicide risk.”

Most studies currently performed in the field analyze populations of adults with bipolar disorder and major depressive disorder who have already made suicide attempts. However, very little progress has been made in fully understanding the brain circuitry related to suicide risk across mood disorders. Blumberg and her team plan to conduct longitudinal studies to determine the effects of early childhood stressors, specifically child maltreatment such as physical neglect and emotional abuse, on brain circuitry abnormalities. Intriguingly, adolescents exposed to early childhood maltreatment showed similar structural changes as adolescents with bipolar who attempted suicide. Researchers are looking into the epigenetic mechanisms that result from exposure to previous stress, such as DNA methylation.

Blumberg and colleagues are currently working on potential treatments for those with implicated suicide risk. A new behavioral treatment designed to change brain circuitry involved in emotional regulation was recently pilot-tested and showed notable improvements in those brain regions. Blumberg hopes that further research in this area will help clinicians identify these prone individuals with more efficiency and accuracy and provide therapies to reduce risk factors and strengthen the target brain circuits.