Clinically Distinct Biotypes in Depression and Anxiety
A key issue in the treatment of Major Depressive Disorder (MDD) is prescribing the appropriate medication, as medication efficacy varies by patient. Without a reliable and widely available diagnostic test to determine the most appropriate pharmacotherapy, Psychiatrists use trial and error. Given the number of different types of antidepressant medication approved for use, this can sometimes take months or even years to optimise. In the intervening period, it is possible that a patient’s symptoms do not improve or even worsen.
However, it may soon be possible to determine the most appropriate course of treatment through functional MRI. According to a recent study led by Stanford University, in which the University of Sydney also participated, brain MRI combined with machine learning can reveal subtypes of depression and anxiety. The study, published in the journal Nature Medicine, describes six biological subtypes (also known as biotypes) of depression and identifies treatments that are more likely or less likely to work for some of these subtypes.
Not only does this new development promise to improve the efficacy of pharmacotherapy, but it also promises to enhance the efficacy of talk therapy. For example, in the study, patients with one subtype characterised by overactivity in cognitive regions of the brain experienced the best response to the antidepressant venlafaxine compared with those who have other biotypes. Those with another subtype had better alleviation of symptoms with talk therapy. And those with a third subtype, who had lower levels of activity at rest in the brain circuit that controls attention, were less likely to see improvement in their symptoms with talk therapy than those with other biotypes.
It is hoped that this new development will lead not only to better outcomes for patients through enhanced pharmacotherapy and talk therapy but also to new diagnostic and treatment options in the future. The study can be found here: https://www.nature.com/articles/s41591-024-03057-9.