4.7 Article

Altered network connectivity predicts response to cognitive-behavioral therapy in pediatric obsessive-compulsive disorder

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NEUROPSYCHOPHARMACOLOGY
卷 45, 期 7, 页码 1232-1240

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DOI: 10.1038/s41386-020-0613-3

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  1. National Institute of Mental Health [R21MH101441]
  2. Fonds de Recherche du Quebec, Sante

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Obsessive-compulsive disorder (OCD) is commonly associated with alterations in cortico-striato-thalamo-cortical brain networks. Yet, recent investigations of large-scale brain networks suggest that more diffuse alterations in brain connectivity may underlie its pathophysiology. Few studies have assessed functional connectivity within or between networks across the whole brain in pediatric OCD or how patterns of connectivity associate with treatment response. Resting-state functional magnetic resonance imaging scans were acquired from 25 unmedicated, treatment-naive children and adolescents with OCD (12.8 +/- 2.9 years) and 23 matched healthy control (HC) participants (11.0 +/- 3.3 years) before participants with OCD completed a course of cognitive-behavioral therapy (CBT). Participants were re-scanned after 12-16 weeks. Whole-brain connectomic analyses were conducted to assess baseline group differences and group-by-time interactions, corrected for multiple comparisons. Relationships between functional connectivity and OCD symptoms pre- and post-CBT were examined using longitudinal cross-lagged panel modeling. Reduced connectivity in OCD relative to HC participants was detected between default mode and task-positive network regions. Greater (less altered) connectivity between left angular gyrus and left frontal pole predicted better response to CBT in the OCD group. Altered connectivity between task-positive and task-negative networks in pediatric OCD may contribute to the impaired control over intrusive thoughts early in the illness. This is the first study to show that altered connectivity between large-scale network regions may predict response to CBT in pediatric OCD, highlighting the clinical relevance of these networks as potential circuit-based targets for the development of novel treatments.

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