Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major 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

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)

Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and dif-ferences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA)

Association of Intrinsic Brain Architecture With Changes in Attentional and Mood Symptoms During Development.

ImportanceUnderstanding the neurodevelopmental trajectory of psychiatric symptoms is important for improving early identification, intervention, and prevention of mental disorders.ObjectiveTo test whether the strength of the coupling of activation between specific brain regions, as measured by resting-state functional magnetic resonance imaging (fMRI), predicted individual children's developmental trajectories in terms of attentional problems characteristic of attention-deficit/hyperactivity disorder and internalizing problems characteristics of major depressive disorder (MDD).Design, setting, and participantsA community cohort of 94 children was recruited from Vanderbilt University between 2010 and 2013. They were followed up longitudinally for 4 years and the data were analyzed from 2016 to 2019. Based on preregistered hypotheses and an analytic plan, we examined whether specific brain connectivity patterns would be associated with longitudinal changes in scores on the Child Behavior Checklist (CBCL), a parental-report assessment used to screen for emotional, behavioral, and social problems and to predict psychiatric illnesses.Main outcomes and measuresWe used the strength of resting-state fMRI connectivity at age 7 years to predict subsequent changes in CBCL measures 4 years later and investigated the mechanisms of change by associating brain connectivity changes with changes in the CBCL.ResultsWe analyzed data from a longitudinal brain development study involving children assessed at age 7 years (n = 94; 41 girls [43.6%]) and 11 years (n = 54; 32 girls [59.3%]). As predicted, less positive coupling at age 7 years between the medial prefrontal cortex and dorsolateral prefrontal cortex (DLPFC) was associated with a decrease in attentional symptoms by age 11 years (t49 = 2.38; P = .01; β = 0.32). By contrast, a less positive coupling between a region implicated in mood, the subgenual anterior cingulate cortex (sgACC), and DLPFC at age 7 years was associated with an increase in internalizing (eg, anxiety/depression) behaviors by age 11 years (t49 = -2.4; P = .01; β = -0.30). Logistic regression analyses revealed that sgACC-DLPFC connectivity was a more accurate predictor than baseline CBCL measures for progression to a subclinical score on internalization (t50 = -2.61; P = .01; β = -0.29). We then replicated and extended the sgACC-DLPFC result in an independent sample of children with (n = 25) or without (n = 18) familial risk for MDD.Conclusions and relevanceThese resting-state fMRI metrics are promising biomarkers for the early identification of children at risk of developing MDD or attention-deficit/hyperactivity disorder

Cingulum-Callosal White-Matter Microstructure Associated with Emotional Dysregulation in Children: A Diffusion Tensor Imaging Study

© 2020 The Author(s) Emotional dysregulation symptoms in youth frequently predispose individuals to increased risk for mood disorders and other mental health difficulties. These symptoms are also known as a behavioral risk marker in predicting pediatric mood disorders. The underlying neural mechanism of emotional dysregulation, however, remains unclear. This study used the diffusion tensor imaging (DTI) technique to identify anatomically specific variation in white-matter microstructure that is associated with pediatric emotional dysregulation severity. Thirty-two children (mean age 9.53 years) with varying levels of emotional dysregulation symptoms were recruited by the Massachusetts General Hospital and underwent the DTI scans at Massachusetts Institute of Technology. Emotional dysregulation severity was measured by the empirically-derived Child Behavior Checklist Emotional Dysregulation Profile that includes the Attention, Aggression, and Anxiety/Depression subscales. Whole-brain voxel-wise regression tests revealed significantly increased radial diffusivity (RD) and decreased fractional anisotropy (FA) in the cingulum-callosal regions linked to greater emotional dysregulation in the children. The results suggest that microstructural differences in cingulum-callosal white-matter pathways may manifest as a neurodevelopmental vulnerability for pediatric mood disorders as implicated in the clinical phenotype of pediatric emotional dysregulation. These findings may offer clinically and biologically relevant neural targets for early identification and prevention efforts for pediatric mood disorders