Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.

BACKGROUND: The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet mental health needs. Accurate ED revisit prediction could aid early intervention and ensure efficient healthcare resource allocation. We examine the potential increased accuracy and performance of graph neural network (GNN) machine learning models compared to recurrent neural network (RNN), and baseline conventional machine learning and regression models for predicting ED revisit in electronic health record (EHR) data. METHODS: This study used EHR data for children and youth aged 4-17 seeking services at McMaster Children's Hospital's Child and Youth Mental Health Program outpatient service to develop and evaluate GNN and RNN models to predict whether a child/youth with an ED visit had an ED revisit within 30 days. GNN and RNN models were developed and compared against conventional baseline models. Model performance for GNN, RNN, XGBoost, decision tree and logistic regression models was evaluated using F1 scores. RESULTS: The GNN model outperformed the RNN model by an F1-score increase of 0.0511 and the best performing conventional machine learning model by an F1-score increase of 0.0470. Precision, recall, receiver operating characteristic (ROC) curves, and positive and negative predictive values showed that the GNN model performed the best, and the RNN model performed similarly to the XGBoost model. Performance increases were most noticeable for recall and negative predictive value than for precision and positive predictive value. CONCLUSIONS: This study demonstrates the improved accuracy and potential utility of GNN models in predicting ED revisits among children and youth, although model performance may not be sufficient for clinical implementation. Given the improvements in recall and negative predictive value, GNN models should be further explored to develop algorithms that can inform clinical decision-making in ways that facilitate targeted interventions, optimize resource allocation, and improve outcomes for children and youth.

Impact of maternal adverse childhood experiences on child socioemotional function in rural Kenya: Mediating role of maternal mental health.

Mothers in low- and middle-income countries (LMIC) suffer heightened vulnerability for adverse childhood experiences (ACEs), which is exacerbated by the multitude of risk factors associated with poverty and may lead to increased risk of psychiatric disorder. The constellation of complex, co-occurring biological, environmental, social, economic and psychological risk factors are in turn transmitted to her child, conferring vulnerability for adverse development. This study examines the association between maternal intra- and extra-familial ACEs, maternal education and the mental health of her child, mediated by maternal mental health. Mother-child dyads (n = 121) in Machakos, Kenya were examined cross-sectionally using self-report measures of ACEs, maternal mental health and child internalizing and externalizing mental health problems. The four models proposed to examine the relationship between intra- and extra-familial maternal ACEs and child internalizing and externalizing problems demonstrated indirect pathways through maternal mental health. These effects were found to be conditional on levels of maternal education, which served as a protective factor at lower levels of maternal ACEs. These models demonstrate how the impact of ACEs persists across the lifespan resulting in a negative impact on maternal mental health and conferring further risk to subsequent generations. Elucidating the association between ACEs and subsequent intergenerational sequelae, especially in LMIC where risk is heightened, may improve targeted caregiver mental health programs for prevention and intervention.

Association of functioning and quality of life with objective and subjective measures of sleep and biological rhythms in major depressive and bipolar disorder.

OBJECTIVE: Disruptions in biological rhythms and sleep are a core aspect of mood disorders, with sleep and rhythm changes frequently occurring prior to and during mood episodes. Wrist-worn actigraphs are increasingly utilized to measure ambulatory activity rhythm and sleep patterns. METHODS: A comprehensive study using subjective and objective measures of sleep and biological rhythms was conducted in 111 participants (40 healthy volunteers [HC], 38 with major depressive disorder [MDD] and 33 with bipolar disorder [BD]). Participants completed 15-day actigraphy and first-morning urine samples to measure 6-sulfatoxymelatonin levels. Sleep and biological rhythm questionnaires were administered: Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN), Munich Chronotype Questionnaire (MCTQ), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). Actigraph data were analyzed for sleep and daily activity rhythms, light exposure and likelihood of transitioning between rest and activity states. RESULTS: Mood groups had worse subjective sleep quality (PSQI) and biological rhythm disruption (BRIAN) and higher objective mean nighttime activity than controls. Participants with BD had longer total sleep time, higher circadian quotient and lower 6-sulfatoxymelatonin levels than HC group. The MDD group had longer sleep onset latency and higher daytime probability of transitioning from rest to activity than HCs. Mood groups displayed later mean timing of light exposure. Multiple linear regression analysis with BRIAN scores, circadian quotient, mean nighttime activity during rest and daytime probability of transitioning from activity to rest explained 43% of variance in quality-of-life scores. BRIAN scores, total sleep time and probability of transitioning from activity to rest explained 52% of variance in functioning (all p < 0.05). CONCLUSIONS: Disruption in biological rhythms is associated with poorer functioning and quality of life in bipolar and MDD. Investigating biological rhythms and sleep using actigraphy variables, urinary 6-sulfatoxymelatonin and subjective measures provide evidence of widespread sleep and circadian system disruptions in mood disorders.

Cortical thickness in bipolar disorder: a systematic review.

OBJECTIVES: Bipolar disorder (BD) is a debilitating illness, the psychopathology of which is associated with aberrant structural and functional differences in the brain. Despite the many advances in psychiatric research, our understanding of the complex neurobiological underpinnings of BD remains incomplete. The aim of this review was to critically examine all available published magnetic resonance imaging (MRI) research reporting cortical thickness in BD with respect to a healthy population and/or other psychiatric samples. METHODS: The systematic search encompassed all relevant studies published until November 2014. Relevant papers were identified through an online search of select databases (MEDLINE and EMBASE) using key terms bipolar disorder or mania, and cortical thickness. Two independent raters determined the eligibility of papers and performed separate data extraction to ensure quality and accuracy of reporting. RESULTS: A total of 17 papers met the criteria and were included in this review. Compared to a healthy population, the majority of studies reported decreased cortical thickness in the left anterior cingulate/paracingulate and the left superior temporal gyrus, as well as several prefrontal regions bilaterally in patients with BD. Studies also show consistency of cortical thinning in individuals with BD and schizophrenia in frontal and temporal regions, suggesting some common neuropathology. CONCLUSIONS: This systematic review further supports a link between specific structural brain abnormalities and BD. Future studies should investigate cortical thickness with respect to at-risk populations to determine whether these neuropathologies develop before or after the onset of BD.

Gray matter volumes in symptomatic and asymptomatic offspring of parents diagnosed with bipolar disorder.

Children of parents diagnosed with bipolar disorder (BD), termed high-risk offspring (HRO), are at greater risk of developing psychiatric disorders compared to healthy children of healthy parents (HCO). Gray matter volume (GMV) abnormalities have been observed in HRO, however, these reports are inconsistent. We posit that this variability may be attributed to differences in methodology among offspring studies; in particular, the presence of psychiatric symptoms in HRO. Here, we directly compared GMVs between symptomatic and asymptomatic HRO, and HCO. High-resolution T1-weighted MR images were collected from 31 HRO (18 symptomatic and 13 asymptomatic) and 20 age- and sex-matched HCO. HRO had at least one parent diagnosed with BD. Symptomatic HRO were defined as having a psychiatric diagnosis other than BD, while asymptomatic HRO were required to be free of any psychiatric diagnosis. Scans were processed using voxel-based morphometry methods and between group analyses were performed in SPM. Compared to HCO, the HRO group showed decreased GMV in the right inferior orbitofrontal, right middle frontal, and bilateral superior and middle temporal regions. Both symptomatic and asymptomatic HRO groups showed decreased GMV in these regions separately when compared to HCO. When comparing symptomatic and asymptomatic HRO, GMVs were comparable in all regions except the lateral occipital cortex. Our study compared symptomatic and asymptomatic HRO directly. In doing so, we provided further support for the presence of discrete GMV deficits in HRO, and confirmed that these deficits are present irrespective of the presence of symptoms in HRO.

Alterations in circadian rhythms are associated with increased lipid peroxidation in females with bipolar disorder.

Disturbances in both circadian rhythms and oxidative stress systems have been implicated in the pathophysiology of bipolar disorder (BD), yet no studies have investigated the relationship between these systems in BD. We studied the impact of circadian rhythm disruption on lipid damage in 52 depressed or euthymic BD females, while controlling for age, severity of depressive symptoms and number of psychotropic medications, compared to 30 healthy controls. Circadian rhythm disruption was determined by a self-report measure (Biological Rhythm Interview of Assessment in Neuropsychiatry; BRIAN), which measures behaviours such as sleep, eating patterns, social rhythms and general activity. Malondialdehyde (MDA) levels were measured as a proxy of lipid peroxidation. We also measured the activity of total and extracellular superoxide dismutase (SOD), catalase (CAT) and glutathione S-transferase (GST). Multiple linear regressions showed that circadian rhythm disturbance was independently associated with increased lipid peroxidation in females with BD (p < 0.05). We found decreased extracellular SOD (p < 0.05), but no differences in total SOD, CAT or GST activity between bipolar females and controls. Circadian rhythms were not associated with lipid peroxidation in healthy controls, where aging was the only significant predictor. These results suggest an interaction between the circadian system and redox metabolism, in that greater disruption in daily rhythms was associated with increased lipid peroxidation in BD only. Antioxidant enzymes have been shown to follow a circadian pattern of expression, and it is possible that disturbance of sleep and daily rhythms experienced in BD may result in decreased antioxidant defence and therefore increased lipid peroxidation. This study provides a basis for further investigation of the links between oxidative stress and circadian rhythms in the neurobiology of BD.

Serotonin transporter (5-HTT) gene network moderates the impact of prenatal maternal adversity on orbitofrontal cortical thickness in middle childhood.

In utero, the developing brain is highly susceptible to the environment. For example, adverse maternal experiences during the prenatal period are associated with outcomes such as altered neurodevelopment and emotion dysregulation. Yet, the underlying biological mechanisms remain unclear. Here, we investigate whether the function of a network of genes co-expressed with the serotonin transporter in the amygdala moderates the impact of prenatal maternal adversity on the structure of the orbitofrontal cortex (OFC) in middle childhood and/or the degree of temperamental inhibition exhibited in toddlerhood. T1-weighted structural MRI scans were acquired from children aged 6-12 years. A cumulative maternal adversity score was used to conceptualize prenatal adversity and a co-expression based polygenic risk score (ePRS) was generated. Behavioural inhibition at 18 months was assessed using the Early Childhood Behaviour Questionnaire (ECBQ). Our results indicate that in the presence of a low functioning serotonin transporter gene network in the amygdala, higher levels of prenatal adversity are associated with greater right OFC thickness at 6-12 years old. The interaction also predicts temperamental inhibition at 18 months. Ultimately, we identified important biological processes and structural modifications that may underlie the link between early adversity and future deviations in cognitive, behavioural, and emotional development.

Examining resting-state network connectivity in children exposed to perinatal maternal adversity using anatomically weighted functional connectivity (awFC) analyses; A preliminary report.

Introduction: Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain's underlying structural architecture. For instance, functional connectivity can be mediated by the presence of direct or indirect anatomical pathways. Such evidence warrants the use of structural and functional imaging in tandem to study network maturation. Accordingly, this study examines the impact of poor maternal mental health and socioeconomic context during the perinatal period on network connectivity in middle childhood using an anatomically weighted functional connectivity (awFC) approach. awFC is a statistical model that identifies neural networks by incorporating information from both structural and functional imaging data. Methods: Resting-state fMRI and DTI scans were acquired from children aged 7-9 years old. Results: Our results indicate that maternal adversity during the perinatal period can affect offspring's resting-state network connectivity during middle childhood. Specifically, in comparison to controls, children of mothers who had poor perinatal maternal mental health and/or low socioeconomic status exhibited greater awFC in the ventral attention network. Discussion: These group differences were discussed in terms of the role this network plays in attention processing and maturational changes that may accompany the consolidation of a more adult-like functional cortical organization. Furthermore, our results suggest that there is value in using an awFC approach as it may be more sensitive in highlighting connectivity differences in developmental networks associated with higher-order cognitive and emotional processing, as compared to stand-alone FC or SC analyses.

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study.

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term ß = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

A detailed manual segmentation procedure for the hypothalamus for 3T T1-weighted MRI.

The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to maximize segmentation accuracy. Here, we provide a detailed step-by-step method outlining the procedures to manually segment the hypothalamus using anatomical T1w images from 3T scanners, which many neuroimaging studies collect as a standard anatomical reference image. We compared volumes generated by manual segmentation and those generated by an automatic algorithm, observing a significant difference between automatically and manually segmented hypothalamus volumes on both sides (left: U = 222842, p-value < 2.2e-16; right: U = 218520, p- value < 2.2e-16).•Significant difference exists between existing automatic segmentation methods and the manual segmentation procedure.•We discuss potential drift effects, segmentation quality issues, and suggestions on how to mitigate them.•We demonstrate that the present manual segmentation procedure using standard T1-weighted MRI may be significantly more accurate than automatic segmentation outputs.

Accelerated brain aging in major depressive disorder and antidepressant treatment response: A CAN-BIND report.

OBJECTIVES: Previous studies suggest that major depressive disorder (MDD) may be associated with volumetric indications of accelerated brain aging. This study investigated neuroanatomical signs of accelerated aging in MDD and evaluated whether a brain age gap is associated with antidepressant response. METHODS: Individuals in a major depressive episode received escitalopram treatment (10-20 mg/d) for 8 weeks. Depression severity was assessed at baseline and at weeks 8 and 16 using the Montgomery-Asberg Depression Rating Scale (MADRS). Response to treatment was characterized by a significant reduction in the MADRS (≥50%). Nonresponders received adjunctive aripiprazole treatment (2-10 mg/d) for a further 8 weeks. The brain-predicted age difference (brain-PAD) at baseline was determined using machine learning methods trained on 3377 healthy individuals from seven publicly available datasets. The model used features from all brain regions extracted from structural magnetic resonance imaging data. RESULTS: Brain-PAD was significantly higher in older MDD participants compared to younger MDD participants [t(147.35) = -2.35, p < 0.03]. BMI was significantly associated with brain-PAD in the MDD group [r(155) = 0.19, p < 0.03]. Response to treatment was not significantly associated with brain-PAD. CONCLUSION: We found an elevated brain age gap in older individuals with MDD. Brain-PAD was not associated with overall treatment response to escitalopram monotherapy or escitalopram plus adjunctive aripiprazole.

Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report.

Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ2 = 77.25, p < 0.0001) and NR3C1 (χ2 = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.

Examining the predictive association of irritability with borderline personality disorder in a clinical sample of female adolescents.

OBJECTIVES: Borderline personality disorder (BPD) is a disorder associated with emotion dysregulation and is common in clinical samples of adolescents. The identification and delineation of BPD from other disorders is important, yet methods for effectively screening for BPD are lacking. Here, we examine whether irritability can be used as a screening item for BPD in adolescents at risk for the disorder. METHODS: We assessed Diagnostic Interview for Borderline-Revised and Development of Well-Being Assessment scores in a clinical sample of female adolescents ages 12-17 (n = 78) to identify BPD and group cases into 'irritable' and 'non-irritable' mood types, respectively. We then examined the prevalence of irritability and its predictive association with BPD. RESULTS: The prevalence of BPD was 26% (n = 20). There was a significant association between irritable mood and BPD, specifically (χ2 (1) = 17.740, p < 0.001). Irritability was endorsed in all (n = 20) BPD cases (sensitivity: 100%), while in non-BPD cases (n = 58), irritability was endorsed in 27 (specificity: 53%; positive predictive value: 0.33; and negative predictive value: 1.0). CONCLUSION: Irritability is a highly sensitive screening item for BPD in adolescents. The absence of irritability in an adolescent may be an important clinical tool to rule out BPD. © 2020 John Wiley & Sons, Ltd.

An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report.

Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment. 181 MDD and 95 healthy comparison (HC) participants were studied. After 8 weeks of escitalopram treatment (10-20 mg/d, flexible dosage), responders (>50% decrease in Montgomery-Åsberg Depression Scale score) were continued on escitalopram; non-responders received adjunctive aripiprazole (2-10 mg/d, flexible dosage). MDD participants were classified into subgroups according to their response profiles at weeks 8 and 16. Baseline group differences in cortical thickness were analyzed with FreeSurfer between HC and MDD groups as well as between response groups. Two-stage longitudinal processing was used to investigate 8-week escitalopram treatment-related changes in cortical thickness. Compared to HC, the MDD group exhibited thinner cortex in the left rostral middle frontal cortex [MNI(X,Y,Z=-29,9,54.5,-7.7); CWP=0.0002]. No baseline differences in cortical thickness were observed between responders and non-responders based on week-8 or week-16 response profile. No changes in cortical thickness was observed after 8 weeks of escitalopram monotherapy. In a two-step 16-week sequential clinical trial we found that baseline cortical thickness does not appear to be associated to clinical response to pharmacotherapy at 8 or 16 weeks.

Orbitofrontal cortex gray matter volumes in bipolar disorder patients: a region-of-interest MRI study.

OBJECTIVES: Functional and postmortem studies suggest that the orbitofrontal cortex (OFC) is involved in the pathophysiology of bipolar disorder (BD). This anatomical magnetic resonance imaging (MRI) study examined whether BD patients have smaller OFC gray matter volumes compared to healthy comparison subjects (HC). METHODS: Twenty-eight BD patients were compared to 28 age- and gender-matched HC. Subjects underwent a 1.5T MRI with 3D spoiled gradient recalled acquisition. Total OFC and medial and lateral subdivisions were manually traced by a blinded examiner. Images were segmented and gray matter volumes were calculated using an automated method. RESULTS: Analysis of covariance, with intracranial volume as covariate, showed that BD patients and HC did not differ in gray matter volumes of total OFC or its subdivisions. However, total OFC gray matter volume was significantly smaller in depressed patients (n = 10) compared to euthymic patients (n = 18). Moreover, total OFC gray matter volumes were inversely correlated with depressive symptom intensity, as assessed by the Hamilton Depression Rating Scale. OFC gray matter volumes were not related to lithium treatment, age at disease onset, number of episodes, or family history of mood disorders. CONCLUSIONS: Our results suggest that abnormal OFC gray matter volumes are not a pervasive characteristic of BD, but may be associated with specific clinical features of the disorder.

Impact of a structured, group-based running programme on clinical, cognitive and social function in youth and adults with complex mood disorders: a 12-week pilot study.

BACKGROUND: Individuals with mood disorders often report lingering health-related quality of life (HRQOL) and social and cognitive impairments even after mood symptoms have improved. Exercise programmes improve mood symptoms in patients, but whether exercise improves functional outcomes in patients with difficult-to-treat mood disorders remains unknown. DESIGN: We evaluated the impact of a 12-week structured running programme on cognitive, social and quality-of-life outcomes in participants with difficult-to-treat mood disorders. METHODS: In a prospective, open-label study, patients referred to the St Joseph's Healthcare Hamilton Team Unbreakable running programme for youth and adults with mood disorders completed a comprehensive assessment battery before and after the 12-week exercise intervention. RESULTS: We collected preintervention and postintervention data from 18 participants who improved on the general health, vitality, role of emotions, social functioning and mental health (all p≤0.01) HRQOL subscales. Performance improved on cognitive tests that assessed working memory and processing speed (p≤0.04); there were no improvements in complex executive functioning tasks. Regression analyses indicated that younger age, shorter illness duration and reduced bodily pain predicted social and cognitive outcomes. CONCLUSION: Participation in a group-based, structured running programme was associated with improved HRQOL and social and cognitive function.

Symptomatic and Functional Outcomes and Early Prediction of Response to Escitalopram Monotherapy and Sequential Adjunctive Aripiprazole Therapy in Patients With Major Depressive Disorder: A CAN-BIND-1 Report.

OBJECTIVE: To report the symptomatic and functional outcomes in patients with major depressive disorder (MDD) during a 2-phase treatment trial and to estimate the value of early improvement after 2 weeks in predicting clinical response to escitalopram and subsequently to adjunctive treatment with aripiprazole. METHODS: Participants with MDD (N = 211) identified with the Montgomery-Asberg Depression Rating Scale (MADRS) and confirmed with the Mini-International Neuropsychiatric Interview were recruited from 6 outpatient centers across Canada (August 2013 through December 2016) and treated with open-label escitalopram (10-20 mg) for 8 weeks (Phase 1). Clinical and functional outcomes were evaluated using the MADRS, Quick Inventory of Depressive Symptomatology-Self-Rated (QIDS-SR), Sheehan Disability Scale (SDS), and Lam Employment Absence and Productivity Scale (LEAPS). Participants were evaluated at 8 and 16 weeks for clinical and functional response and remission. Phase 1 responders continued escitalopram while nonresponders received adjunctive aripiprazole (2-10 mg) for a further 8 weeks (Phase 2). RESULTS: After Phase 1, MADRS response (≥ 50% decrease from baseline) and remission (score ≤ 10) were, respectively, 47% and 31%, and SDS response (score ≤ 12) and remission (score ≤ 6) were, respectively, 53% and 24%. Response to escitalopram was maintained in 91% of participants at week 16, while 61% of the adjunctive aripiprazole group achieved MADRS response during Phase 2. Response and remission rates with the QIDS-SR were lower than with the MADRS. The LEAPS demonstrated significant occupational improvement (P < .05). Early symptomatic improvement predicted outcomes with modest accuracy. CONCLUSIONS: This study demonstrates comparable symptomatic and functional outcomes to those of other large practical-design studies. There was a high response rate with the adjunctive use of aripiprazole in escitalopram nonresponders. Given the limited value of early clinical improvement to predict outcome, integration of clinical and biological markers deserves further exploration. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01655706.

Three-dimensional mapping of hippocampal anatomy in unmedicated and lithium-treated patients with bipolar disorder.

Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder (21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients (by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis 1 subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.

MRI study of the cerebellum in young bipolar patients.

Prior studies demonstrate structural abnormalities of cerebellar vermis in adult bipolar patients. Cerebella of 16 young bipolar patients (mean age+/-S.D.=15.5+/-3.4) and 21 healthy controls (mean age+/-S.D.=16.9+/-3.8) were examined using magnetic resonance imaging. The volumes of right, left and total cerebellum, vermis, and areas of vermal regions V1 (lobules I-V), V2 (lobules VI-VII), and V3 (lobules VIII-X) were measured. Analysis of covariance, with age, gender, and intra-cranial brain volume as covariates, revealed no significant differences in cerebellum or vermis measures between patients and controls; however, there was a trend to smaller vermis V2 areas in patients (p=0.06). The number of previous affective episodes and vermis area V2 were inversely correlated (partial correlation coefficient=-0.97, P=0.001) in the male bipolar patient group. Our results are preliminary, but consistent with the findings from studies in adult bipolar patients suggesting the involvement of structural changes in cerebellar vermis in the pathophysiology of bipolar disorder.

Effects of a 12-week running programme in youth and adults with complex mood disorders.

OBJECTIVE: Although numerous studies suggest a salutary effect of exercise on mood, few studies have explored the effect of exercise in patients with complex mental illness. Accordingly, we evaluated the impact of running on stress, anxiety and depression in youth and adults with complex mood disorders including comorbid diagnoses, cognitive and social impairment and high relapse rates. METHODS: Participants were members of a running group at St Joseph Healthcare Hamilton's Mood Disorders Program, designed for clients with complex mood disorders. On a weekly basis, participants completed Cohen's Perceived Stress Scale, Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) questionnaires, providing an opportunity to evaluate the effect of running in this population. RESULTS: Data collected for 46 participants from April 2012 to July 2015 indicated a significant decrease in depression (p<0.0001), anxiety (p<0.0001) and stress (p=0.01) scores. Whereas younger participant age, younger age at onset of illness and higher perceived levels of friendship with other running group members (ps≤0.04) were associated with lower end-of-study depression, anxiety and stress scores, higher attendance was associated with decreasing BDI and BAI (ps≤0.01) scores over time. CONCLUSIONS: Aerobic exercise in a supportive group setting may improve mood symptoms in youth and adults with complex mood disorders, and perceived social support may be an important factor in programme's success. Further research is required to identify specifically the mechanisms underlying the therapeutic benefits associated with exercise-based therapy programmes.