EEG May Guide Optimal Treatment for PTSD, Major Depression

Megan Brooks

October 23, 2020

By analyzing brainwaves, researchers have identified two clinically relevant subtypes of major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) that may respond differently to psychotherapy, antidepressants, or brain stimulation in findings that could accurately pinpoint optimal treatment at diagnosis.

"Brain stimulation is a costly and somewhat burdensome intervention. Knowing early on that it would be the most effective treatment for a patient, it could save time and suffering to go right to brain stimulation and reduce the money spent on treatments that don't work," lead researcher Amit Etkin, MD, PhD, Stanford University, Stanford, California, and founder and CEO of Alto Neuroscience, told Medscape Medical News.

The study was published October 19 in Nature Biomedical Engineering.

Great Need for Objective Testing

The researchers examined data on more than 700 participants with PTSD or MDD or healthy control persons.

Using electroencephalography (EEG) data and advanced machine-learning techniques, the investigators identified two subtypes of PTSD and MDD characterized by "robust and distinct" functional connectivity patterns, prominently within the frontoparietal control network and the default mode network.

Although the two subtypes did not differ in terms of baseline clinical severity, they did differ in terms of clinical outcome with respect to either psychotherapy for PTSD or treatment with an antidepressant vs placebo for MDD.

Of note, individuals with subtype 2, whose functional connectivity patterns differed the most from those of healthy control persons, responded less well to psychotherapy for PTSD and failed to respond to an antidepressant for MDD.

In contrast, for both subtypes, patients responded equally well to repetitive transcranial magnetic stimulation for MDD.

"There is a great need in psychiatry for objective tests that can inform diagnostic development and clinical treatment decisions for heterogeneous conditions such as PTSD and MDD," Etkin said in a news release.

"Our findings are exciting because they reflect progress towards identifying evidence-based biomarkers, and they also demonstrate the value of machine learning techniques for advancing a personalized approach to treatment ― which are part of a tipping point in the field," he said.

Etkin told Medscape Medical News that the goal is to make a "robust FDA-approvable test and extend the clinical relevance to understand which other kinds of treatments have effects one way or the other. There are a variety of new treatments being developed for both depression and PTSD so we're very interested in understanding the breadth of the clinical role of this approach."

"Exactly What the Field Needs"

Commenting on the findings for Medscape Medical News, James Potash, MD, MPH, professor of psychiatry and behavioral sciences, Johns Hopkins Medicine, Baltimore, Maryland, said this study is "exactly the kind of work that the field needs to be doing right now.

"It's so important that we define subtypes of psychiatric illnesses. Our hope is that if we can get more clarity about the subtypes of illness, we'll get more clarity about which treatments are going to be most useful for people who fall into these different categories," said Potash.

He noted that past attempts to subtype psychiatric illness have largely hinged on clinical impressions, "which have some value, but they've been too vague, unfortunately, to yield anything meaningful. Our tools are better than they've ever been now to begin to try to understand at the level of biology how to subcategorize people.

"This is very good work, and I very much hope and expect that we will get to a point eventually where we can use this kind of approach in the clinic. We're not there yet, but it seems like with more work like this, we'll be able to get there before long," Potash said.

The study was supported by grants from the Steven and Alexandra Cohen Foundation, Cohen Veterans Bioscience and the National Institutes of Health. Etkin receives equity and salary from Alto Neuroscience, along with equity from Mindstrong Health, Akili Interactive, and Sizung. Potash has disclosed no relevant financial relationships.

Nat Biomed Eng. Published online October 19, 2020. Abstract

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