Alaa Houri

A preliminary study of functional connectivity in comorbid adolescent depression

Major depressive disorder (MDD) begins frequently in adolescence and is associated with severe outcomes, but the developmental neurobiology of MDD is not well understood. Research in adults has implicated fronto-limbic neural networks in the pathophysiology of MDD, particularly in relation to the subgenual anterior cingulate cortex (ACC). Developmental changes in brain networks during adolescence highlight the need to examine MDD-related circuitry in teens separately from adults. Using resting state functional magnetic resonance imaging (fMRI), this study examined functional connectivity in adolescents with MDD (n=12) and healthy adolescents (n=14). Seed-based connectivity analysis revealed that adolescents with MDD have decreased functional connectivity in a subgenual ACC-based neural network that includes the supragenual ACC (BA 32), the right medial frontal cortex (BA 10), the left inferior (BA 47) and superior frontal cortex (BA 22), superior temporal gyrus (BA 22), and the insular cortex (BA 13). These preliminary data suggest that MDD in adolescence is associated with abnormal connectivity within neural circuits that mediate emotion processing. Future research in larger, un-medicated samples will be necessary to confirm this finding. We conclude that hypothesis-driven, seed-based analyses of resting state fMRI data hold promise for advancing our current understanding of abnormal development of neural circuitry in adolescents with MDD.

Abnormal Amygdala Resting-State Functional Connectivity in Adolescent Depression

IMPORTANCE Major depressive disorder (MDD) frequently emerges during adolescence and can lead to persistent illness, disability, and suicide. The maturational changes that take place in the brain during adolescence underscore the importance of examining neurobiological mechanisms during this time of early illness. However, neural mechanisms of depression in adolescents have been understudied. Research has implicated the amygdala in emotion processing in mood disorders, and adult depression studies have suggested amygdala-frontal connectivity deficits. Resting-state functional magnetic resonance imaging is an advanced tool that can be used to probe neural networks and identify brain-behavior relationships. OBJECTIVE To examine amygdala resting-state functional connectivity (RSFC) in adolescents with and without MDD using resting-state functional magnetic resonance imaging as well as how amygdala RSFC relates to a broad range of symptom dimensions. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional resting-state functional magnetic resonance imaging study was conducted within a depression research program at an academic medical center. Participants included 41 adolescents and young adults aged 12 to 19 years with MDD and 29 healthy adolescents (frequency matched on age and sex) with no psychiatric diagnoses. MAIN OUTCOMES AND MEASURES Using a whole-brain functional connectivity approach, we examined the correlation of spontaneous fluctuation of the blood oxygen level-dependent signal of each voxel in the whole brain with that of the amygdala. RESULTS Adolescents with MDD showed lower positive RSFC between the amygdala and hippocampus, parahippocampus, and brainstem (z >2.3, corrected P < .05); this connectivity was inversely correlated with general depression (R = -.523, P = .01), dysphoria (R = -.455, P = .05), and lassitude (R = -.449, P = .05) and was positively correlated with well-being (R = .470, P = .03). Patients also demonstrated greater (positive) amygdala-precuneus RSFC (z >2.3, corrected P < .05) in contrast to negative amygdala-precuneus RSFC in the adolescents serving as controls. CONCLUSIONS AND RELEVANCE Impaired amygdala-hippocampal/brainstem and amygdala-precuneus RSFC have not previously been highlighted in depression and may be unique to adolescent MDD. These circuits are important for different aspects of memory and self-processing and for modulation of physiologic responses to emotion. The findings suggest potential mechanisms underlying both mood and vegetative symptoms, potentially via impaired processing of memories and visceral signals that spontaneously arise during rest, contributing to the persistent symptoms experienced by adolescents with depression.

An fMRI study of emotional face processing in adolescent major depression

BACKGROUND Major depressive disorder (MDD) often begins during adolescence when the brain is still maturing. To better understand the neurobiological underpinnings of MDD early in development, this study examined brain function in response to emotional faces in adolescents with MDD and healthy (HC) adolescents using functional magnetic resonance imaging (fMRI). METHOD Thirty-two unmedicated adolescents with MDD and 23 healthy age- and gender-matched controls completed an fMRI task viewing happy and fearful faces. Fronto-limbic regions of interest (ROI; bilateral amygdala, insula, subgenual and rostral anterior cingulate cortices) and whole-brain analyses were conducted to examine between-group differences in brain function. RESULTS ROI analyses revealed that patients had greater bilateral amygdala activity than HC in response to viewing fearful versus happy faces, which remained significant when controlling for comorbid anxiety. Whole-brain analyses revealed that adolescents with MDD had lower activation compared to HC in a right hemisphere cluster comprised of the insula, superior/middle temporal gyrus, and Heschl׳s gyrus when viewing fearful faces. Brain activity in the subgenual anterior cingulate cortex was inversely correlated with depression severity. LIMITATIONS Limitations include a cross-sectional design with a modest sample size and use of a limited range of emotional stimuli. CONCLUSIONS Results replicate previous studies that suggest emotion processing in adolescent MDD is associated with abnormalities within fronto-limbic brain regions. Findings implicate elevated amygdalar arousal to negative stimuli in adolescents with depression and provide new evidence for a deficit in functioning of the saliency network, which may be a future target for early intervention and MDD treatment.

Suicide prevention with adolescents: considering potential benefits and untoward effects of public service announcements.

BACKGROUND/AIMS Suicide is one of the most serious public health challenges; yet determining optimal methods for preventing suicide in adolescents continues to be an elusive goal. The aim of this study was to investigate possible benefits and untoward effects of suicide-prevention public service announcements (PSAs) for adolescents. METHODS Adolescent participants (N = 426; 56% female) were randomly assigned to one of three conditions: (a) a billboard simulation, (b) a 30-s TV ad simulation, and (c) a no-information condition. RESULTS The results of this study suggest some benefits for the information conveyed by the TV ad (e.g., more knowledgeable about depression). Few benefits were noted for adolescents who were exposed to billboard simulation, and the results raised substantial concerns about possible untoward effects, particularly in adolescents who were exhibiting depressive or suicidal symptoms. Billboard viewers were less likely to favor help-seeking attitudes, perceived PSAs as being less useful, and endorsed more maladaptive coping. CONCLUSIONS More research is urgently needed so that well-intended efforts to prevent suicide can more optimally serve the desired goals.

Suicide Prevention with Adolescents

BACKGROUND/AIMS Suicide is one of the most serious public health challenges; yet determining optimal methods for preventing suicide in adolescents continues to be an elusive goal. The aim of this study was to investigate possible benefits and untoward effects of suicide-prevention public service announcements (PSAs) for adolescents. METHODS Adolescent participants (N = 426; 56% female) were randomly assigned to one of three conditions: (a) a billboard simulation, (b) a 30-s TV ad simulation, and (c) a no-information condition. RESULTS The results of this study suggest some benefits for the information conveyed by the TV ad (e.g., more knowledgeable about depression). Few benefits were noted for adolescents who were exposed to billboard simulation, and the results raised substantial concerns about possible untoward effects, particularly in adolescents who were exhibiting depressive or suicidal symptoms. Billboard viewers were less likely to favor help-seeking attitudes, perceived PSAs as being less useful, and endorsed more maladaptive coping. CONCLUSIONS More research is urgently needed so that well-intended efforts to prevent suicide can more optimally serve the desired goals.

Multilevel assessment of the neurobiological threat system in depressed adolescents: Interplay between the limbic system and hypothalamic-pituitary-adrenal axis

Integrative, multilevel approaches investigating neurobiological systems relevant to threat detection promise to advance understanding of the pathophysiology of major depressive disorder (MDD). In this study we considered key neuronal and hormonal systems in adolescents with MDD and healthy controls (HC). The goals of this study were to identify group differences and to examine the association of neuronal and hormonal systems. MDD and HC adolescents (N = 79) aged 12-19 years were enrolled. Key brain measures included amygdala volume and amygdala activation to an emotion face-viewing task. Key hormone measures included cortisol levels during a social stress task and during the brain scan. MDD and HC adolescents showed group differences on amygdala functioning and patterns of cortisol levels. Amygdala activation in response to emotional stimuli was positively associated with cortisol responses. In addition, amygdala volume was correlated with cortisol responses, but the pattern differed in depressed versus healthy adolescents, most notably for unmedicated MDD adolescents. The findings highlight the value of using multilevel assessment strategies to enhance understanding of pathophysiology of adolescent MDD, particularly regarding how closely related biological threat systems function together while undergoing significant developmental shifts.

Executive Attention Impairment in Adolescents With Major Depressive Disorder.

Neural network models that guide neuropsychological assessment practices are increasingly used to explicate depression, though a paucity of work has focused on regulatory systems that are under development in adolescence. The purpose of this study was to evaluate subsystems of attention related to executive functioning including alerting, orienting, and executive attention networks, as well as sustained attention with varying working memory load, in a sample of depressed and well adolescents. Neuropsychological functioning in 99 adolescents diagnosed with major depressive disorder (MDD) and 63 adolescent healthy controls (M = 16.6 years old) was assessed on the Attention Network Test (ANT) and the Continuous Performance Test, Identical Pairs. Adolescents with MDD, particularly those who were not medicated, were slower to process conflict (slower reaction time on the Executive Attention scale of the ANT) compared to controls, particularly for those who were not undergoing psychopharmacological treatment. Tentative evidence also suggests that within the MDD group, orienting performance was more impaired in those with a history of comorbid substance use disorder, and alerting was more impaired in those with a history of a suicide attempt. Adolescents with depression showed impaired executive attention, although cognitive performance varied across subgroups of patients. These findings highlight the importance of examining neurocognitive correlates associated with features of depression and suggest an avenue for future research to help guide the development of interventions.

Abnormal striatal resting-state functional connectivity in adolescents with obsessive–compulsive disorder

Neuroimaging research has implicated abnormalities in cortico-striatal-thalamic-cortical (CSTC) circuitry in pediatric obsessive-compulsive disorder (OCD). In this study, resting-state functional magnetic resonance imaging (R-fMRI) was used to investigate functional connectivity in the CSTC circuitry in adolescents with OCD. Imaging was obtained with the Human Connectome Project (HCP) scanner using newly developed pulse sequences which allow for higher spatial and temporal resolution. Fifteen adolescents with OCD and 13 age- and gender-matched healthy controls (ages 12-19) underwent R-fMRI on the 3T HCP scanner. Twenty-four minutes of resting-state scans (two consecutive 12-min scans) were acquired. We investigated functional connectivity of the striatum using a seed-based, whole brain approach with anatomically-defined seeds placed in the bilateral caudate, putamen, and nucleus accumbens. Adolescents with OCD compared with controls exhibited significantly lower functional connectivity between the left putamen and a single cluster of right-sided cortical areas including parts of the orbitofrontal cortex, inferior frontal gyrus, insula, and operculum. Preliminary findings suggest that impaired striatal connectivity in adolescents with OCD in part falls within the predicted CSTC network, and also involves impaired connections between a key CSTC network region (i.e., putamen) and key regions in the salience network (i.e., insula/operculum). The relevance of impaired putamen-insula/operculum connectivity in OCD is discussed.

Impaired Bottom-Up Effective Connectivity Between Amygdala and Subgenual Anterior Cingulate Cortex in Unmedicated Adolescents with Major Depression: Results from a Dynamic Causal Modeling Analysis

Major depressive disorder (MDD) is a significant contributor to lifetime disability and frequently emerges in adolescence, yet little is known about the neural mechanisms of MDD in adolescents. Dynamic causal modeling (DCM) analysis is an innovative tool that can shed light on neural network abnormalities. A DCM analysis was conducted to test several frontolimbic effective connectivity models in 27 adolescents with MDD and 21 healthy adolescents. The best neural model for each person was identified using Bayesian model selection. The findings revealed that the two adolescent groups fit similar optimal neural models. The best across-groups model was then used to infer upon both within-group and between-group tests of intrinsic and modulation parameters of the network connections. First, for model validation, within-group tests revealed robust evidence for bottom-up connectivity, but less evidence for strong top-down connectivity in both groups. Second, we tested for differences between groups on the validated parameters of the best model. This revealed that adolescents with MDD had significantly weaker bottom-up connectivity in one pathway, from amygdala to sgACC (p=0.008), than healthy controls. This study provides the first examination of effective connectivity using DCM within neural circuitry implicated in emotion processing in adolescents with MDD. These findings aid in advancing understanding the neurobiology of early-onset MDD during adolescence and have implications for future research investigating how effective connectivity changes across contexts, with development, over the course of the disease, and after intervention.

Classification of borderline personality disorder based on spectral power of resting-state fMRI

Borderline personality disorder (BPD) is a serious mental illness that can cause significant suffering and carries a risk of suicide. Assigning an accurate diagnosis is critical to guide treatment. Currently, the diagnosis of BPD is made exclusively through the use of clinical assessment; no objective test is available to assist with its diagnosis. Thus, it is highly desirable to explore quantitative biomarkers to better characterize this illness. In this study, we extract spectral power features from the power spectral density and cross spectral density of resting-state fMRI data, covering 20 brain regions and 5 frequency bands. Machine learning approaches are employed to select the most discriminating features to identify BPD. Following a leave-one-out cross validation procedure, the proposed approach achieves 93.55% accuracy (100% specificity and 90.48% sensitivity) in classifying 21 BPD patients from 10 healthy controls based on the top ranked features. The most discriminating features are selected from the 0.1~0.15Hz frequency band, and are located at the left medial orbitofrontal cortex, the left thalamus, and the right rostral anterior cingulate cortex. The high classification accuracy indicates the discriminating power of the spectral power features in BPD identification. The proposed machine learning approach may be used as an objective test to assist clinical diagnosis of BPD.