Xiaoqian J Chai1, Dina Hirshfeld-Becker2, Joseph Biederman3, Mai Uchida3, Oliver Doehrmann4, Julia A Leonard4, John Salvatore4, Tara Kenworthy3, Ariel Brown3, Elana Kagan3, Carlo de Los Angeles4, John D E Gabrieli5, Susan Whitfield-Gabrieli4. 1. Poitras Center for Affective Disorders Research at the McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge. Electronic address: xiaoqian@mit.edu. 2. Department of Psychiatry, Harvard Medical School, Boston. 3. Department of Psychiatry, Harvard Medical School, Boston; Clinical and Research Program in Pediatric Psychopharmacology, Massachusetts General Hospital, Boston. 4. Poitras Center for Affective Disorders Research at the McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge. 5. Poitras Center for Affective Disorders Research at the McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge; Department of Psychiatry, Harvard Medical School, Boston; Clinical and Research Program in Pediatric Psychopharmacology, Massachusetts General Hospital, Boston; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Abstract
BACKGROUND: Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. METHODS: We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8-14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16). RESULTS: At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. CONCLUSIONS: Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression.
BACKGROUND: Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. METHODS: We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8-14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16). RESULTS: At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. CONCLUSIONS:Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression.
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