Life Science and Medical News from Around the Globe
Suicide Risk May Be Predicted at 80%-96% Certainty with Blood Test for Changes in Single Gene—Multiple Benefits Foreseen by Hopkins Scientists
Johns Hopkins researchers say they have discovered a chemical alteration in a single human gene linked to stress reactions that, if confirmed in larger studies, could give doctors a simple blood test to reliably predict a person's risk of attempting suicide. The discovery, described online on July 30, 2014 in The American Journal of Psychiatry, suggests that changes in a gene involved in the function of the brain's response to stress hormones plays a significant role in turning what might otherwise be an unremarkable reaction to the strain of everyday life into suicidal thoughts and behaviors. "Suicide is a major preventable public health problem, but we have been stymied in our prevention efforts because we have no consistent way to predict those who are at increased risk of killing themselves," says study leader Zachary Kaminsky, Ph.D., an assistant professor of psychiatry and behavioral sciences at the Johns Hopkins University School of Medicine. "With a test like ours, we may be able to stem suicide rates by identifying those people and intervening early enough to head off a catastrophe." For his series of experiments, Dr. Kaminsky and his colleagues focused on a genetic mutation in a gene known as SKA2. By looking at brain samples from mentally ill and healthy people, the researchers found that in samples from people who had died by suicide, levels of SKA2 were significantly reduced. Within this common mutation, they then found in some subjects an epigenetic modification that altered the way the SKA2 gene functioned without changing the gene's underlying DNA sequence. The modification added chemicals called methyl groups to the gene. Higher levels of methylation were then found in the same study subjects who had killed themselves. The higher levels of methylation among suicide decedents were then replicated in two independent brain cohorts.