New research shows blood tests could be effective in diagnosing depression
By Nick Lavars
April 30, 2014
At present, reaching a diagnosis for depression typically involves interviews with the patient, resulting in a drawn out and costly process. Some recent research efforts have sought to address this, such as a diagnostic technique that measures electrical activity in the brain to more quickly detect mental illness. Now a team of Austrian researchers has demonstrated a link between levels of serotonin in the blood and the depression network in the brain, meaning that diagnosing depression could soon become a much more efficient undertaking.
Working at the Department of Biological Psychiatry at the Medical University of Vienna, a team led by Associate Professor Lukas Pezawas examined the relationship between the speed of serotonin uptake in blood platelets and the neural depression network in the brain.
The study focused on the serotonin transporter (SERT), a protein in the membrane that enables serotonin to be transported into the cell. In the brain, this regulates the depression network and is key in fending off depressive conditions.
Recent studies have demonstrated that not only is this serotonin transporter also present in the blood, it works in the same way that it does in the brain, ensuring that the concentration of serotonin in the blood plasma is kept at healthy levels. In observing this process alongside functional magnetic resonance imaging of the brain, the team concluded that there is in fact a close relationship between the rate of serotonin uptake in the blood and the function of the neural depression network.
"This is the first study that has been able to predict the activity of a major depression network in the brain using a blood test," says Pezawas. "While blood tests for mental illnesses have until recently been regarded as impossible, this study clearly shows that a blood test is possible in principle for diagnosing depression and could become reality in the not too distant future."
The team's research was published in the journal PLOS ONE.
Source: Medical University of Vienna