Neuroimaging Identifies Depression 'Biotypes'

Megan Brooks

December 07, 2016

Depression can be grouped into different subtypes as defined by distinct patterns of abnormal connectivity in the brain seen on functional MRI (fMRI), new research shows.

These depression "biotypes" cannot be differentiated solely on the basis of clinical features, but are associated with differing clinical symptom profiles. They also may help predict response to transcranial magnetic stimulation.

The research was published online December 5 in Nature Medicine.

Pinpointing TMS Responders

"For many years, psychiatrists and neuroscientists have recognized that there is a weak correspondence between diagnostic labels like depression and their neurobiological substrates," senior author Conor Liston, MD, PhD, neuroscientist and psychiatrist, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York City, told Medscape Medical News.

Dr Conor Liston

"This poses major obstacles to understanding the underlying biology, identifying biomarkers for assisting in diagnosis, and developing more effective treatments. Our results define one approach for subtyping patients with depression based solely on fMRI-based measures of functional connectivity in depression-related brain networks, allowing us to accurately diagnose individual subjects as depressed or not depressed and predict which patients will respond to a neurostimulation-based antidepressant treatment," said Dr Liston.

By analyzing fMRI scans in a large multisite sample of more than 1100 patients with clinical depression and healthy control individuals, the researchers found that patients with depression can be subdivided into four biotypes defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks and different clinical symptoms.

For example, reduced connectivity in the frontoamygdala networks, which regulate fear-related behavior and reappraisal of negative emotional stimuli, was most severe in biotypes 1 and 4, which are associated with symptoms of increased anxiety, they report.

By contrast, hyperconnectivity in thalamic and frontostriatal networks, which support reward processing, adaptive motor control, and action initiation, were especially pronounced in biotypes 3 and 4 and were associated with increased anhedonia and psychomotor retardation.

Reduced connectivity in anterior cingulate and orbitofrontal areas, which support motivation and incentive-salience evaluation, were most severe in biotypes 1 and 2, which were characterized by increased anergia and fatigue.

In clustering analysis, the researchers were able to develop diagnostic classifiers (biomarkers) with high sensitivity and specificity for depression subtypes in a multisite validation cohort and an out-of-sample replication cohort.

"The four subtypes of depression that we discovered vary in terms of their clinical symptoms, but, more importantly, they differ in their responses to treatment," Dr Liston said in a statement.

The investigators predicted "with high accuracy whether or not a patient will respond to transcranial magnetic stimulation therapy, which is significant because it takes 5 weeks to know if this type of treatment works," he added.

"We view these results as just one, initial solution to the problem of diagnostic heterogeneity in depression," said Dr Liston.

"In the long term, we expect that the methods we have developed will enable psychiatrists to use fMRI brain scans to assist with complex diagnostic questions and treatment selection, targeting specific antidepressant interventions to the individual patients most likely to benefit from them. However, prior to deploying these tools for widespread clinical use, future studies must focus on replicating and validating them in larger, naturalistic patient samples," he added.

"Impressive" Article

Commenting on the findings for Medscape Medical News, Cyrus Raji, MD, PhD, of the University of California, Los Angeles, said, "This paper is an impressive demonstration of the utility of machine learning with psychiatric neuroimaging as applied in depression subtypes. Future work would benefit from showing how these findings can be applied to specific case examples so physicians can better apply such work in the clinic," he said.

The study had no commercial funding. Dr Liston has disclosed no relevant financial relationships. The original article has a complete list of author disclosures.

Nat Med. Published online December 5, 2016. Abstract


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