Six subtypes of depression and anxiety identified via MRI

Brain imaging combined with artificial intelligence has identified six distinct “biotypes” of depression and anxiety that could lead to more personalized and effective treatment.

This research has “immediate clinical implications,” said researcher Leanne Williams, PhD, director of the Stanford Medicine Center for Precision Mental Health and Wellness. Medscape Medical News.

“At Stanford, we have begun using imaging technology in a new precision mental health clinic. The technology is being actively developed for broader use in clinical settings, and we hope to make it accessible to more clinicians and practitioners. patients,” Williams said. .

The study was published online on June 17, 2024 in Natural medicine.

More trial and error?

Depression is a very heterogeneous disease, with each patient presenting different symptoms and therapeutic responses. Approximately 30% of patients with major depression are treatment resistant, and approximately half of patients with generalized anxiety disorder do not respond to first-line treatment.

“The dominant 'one size fits all' diagnostic approach in psychiatry leads to navigating treatment options by trial and error, which is time-consuming, expensive and frustrating, with 30-40% of patients failing to achieve remission after trying one treatment. “, note the authors.

“The goal of our work is to figure out how to get it right the first time,” Williams said in a press release, which requires a better understanding of the neurobiology of depression.

To this end, 801 adults with depression and anxiety underwent functional MRI to measure brain activity at rest and during tasks designed to test cognitive and emotional functioning.

The researchers studied six brain circuits previously associated with depression: the default mode circuit, the salience circuit, the attention circuit, the negative affect circuit, the positive affect circuit, and the cognitive control circuit.

Using a machine learning technique known as cluster analysis to group patients' brain images, they identified six clinically distinct biotypes of depression and anxiety defined by specific profiles of dysfunction in taskless brain circuits and evoked by the task.

“These biotypes predict response to different pharmacological and behavioral interventions, which is important for clinical translation,” the researchers wrote.

For example, patients with a biotype characterized by hyperactivity in cognitive regions of the brain showed the best response to the antidepressant venlafaxine compared to patients with other biotypes.

Patients with a different biotype, characterized by higher resting activity levels in three regions associated with depression and problem solving, responded better to behavioral therapy.

Additionally, those with a third biotype, who had lower levels of resting activity in the brain circuit that controls attention, were less likely to see improvement in their symptoms with behavioral therapy than those with a third biotype. other biotypes. The different biotypes were also correlated with differences in symptoms and task performance.

For example, individuals with overactive cognitive regions of the brain had higher levels of anhedonia than those with other biotypes, and they also performed worse on tasks measuring executive function. Those whose biotype responded best to behavioral therapy also made errors on executive tasks, but performed well on cognitive tasks.

A work in progress

The results provide a better understanding of the neurobiological underpinnings of depression and anxiety and could lead to better diagnostic accuracy and more tailored therapeutic approaches, the researchers noted.

Naming biotypes is a work in progress, Williams said.

“We thought a lot about choosing the name. In the Natural medicine In this paper, we use a technical convention to name biotypes based on the brain circuit issues that define each one,” she explained.

“For example, the first biotype is called D_C+S_C+A_C+ because it is defined by increases in connectivity (C+) across three resting circuits: default mode (D), salience (S), and frontoparietal attention (A). We are working with collaborators to generate biotype names that could converge between results and laboratories. In the near future, we plan to generate more descriptive medical names that clinicians can refer to alongside technical names,” Williams said.

Commenting on the research Medscape Medical NewsJames Murrough, MD, PhD, director of the Center for Depression and Anxiety Research and Treatment at the Icahn School of Medicine at Mount Sinai in New York, called it “super exciting.”

“The work of this research group is an excellent example of the current state of precision psychiatry research, particularly as it relates to the use of brain imaging to personalize treatment, and this article gives us insight of where we might be in the future – a distant future,” Murrough said.

However, he cautioned that at this point, “we are far from realizing the dream of precision psychiatry. We simply do not have strong evidence that brain imaging markers can actually guide decision-making clinic at present.

Funding for the study was provided by the National Institutes of Health and Brain Resource Ltd. Williams declared U.S. patent applications numbered 10/034,645 and 15/820,338: “Systems and methods for detecting complex networks in MRI data.” Murrough had no relevant disclosures.