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Personalized brain circuit scores identify clinically distinct biotypes in depression and anxiety. | LitMetric

Article Synopsis

  • There is a pressing need to develop quantitative measures for identifying different types of neurobiological dysfunctions, or 'biotypes,' to better categorize patients with depression and anxiety.
  • Researchers analyzed brain data from 801 patients who were treatment-free and 250 patients after receiving either medication or therapy, creating personalized scores of brain dysfunction based on a theoretical model.
  • The study identified six distinct biotypes, each characterized by unique brain connectivity patterns and correlated with specific symptoms, cognitive performance, and treatment responses, providing a new approach for tailoring clinical care in psychiatry.

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Article Abstract

There is an urgent need to derive quantitative measures based on coherent neurobiological dysfunctions or 'biotypes' to enable stratification of patients with depression and anxiety. We used task-free and task-evoked data from a standardized functional magnetic resonance imaging protocol conducted across multiple studies in patients with depression and anxiety when treatment free (n = 801) and after randomization to pharmacotherapy or behavioral therapy (n = 250). From these patients, we derived personalized and interpretable scores of brain circuit dysfunction grounded in a theoretical taxonomy. Participants were subdivided into six biotypes defined by distinct profiles of intrinsic task-free functional connectivity within the default mode, salience and frontoparietal attention circuits, and of activation and connectivity within frontal and subcortical regions elicited by emotional and cognitive tasks. The six biotypes showed consistency with our theoretical taxonomy and were distinguished by symptoms, behavioral performance on general and emotional cognitive computerized tests, and response to pharmacotherapy as well as behavioral therapy. Our results provide a new, theory-driven, clinically validated and interpretable quantitative method to parse the biological heterogeneity of depression and anxiety. Thus, they represent a promising approach to advance precision clinical care in psychiatry.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11271415PMC
http://dx.doi.org/10.1038/s41591-024-03057-9DOI Listing

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