Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Altered neurochemistry in the anterior white matter of bipolar children and adolescents: a multivoxel 1H MRS study.

Abnormalities within frontal lobe gray and white matter of bipolar disorder (BD) patients have been consistently reported in adult and pediatric studies, yet little is known about the neurochemistry of the anterior white matter (AWM) in pediatric BD and how medication status may affect it. The present cross-sectional 3T 1H MRS study is the first to use a multivoxel approach to study the AWM of BD youth. Absolute metabolite levels from four bilateral AWM voxels were collected from 49 subjects between the ages of 8 and 18 (25 healthy controls (HC); 24 BD) and quantified. Our study found BD subjects to have lower levels of N-acetylaspartate (NAA) and glycerophosphocholine plus phosphocholine (GPC + PC), metabolites that are markers of neuronal viability and phospholipid metabolism and have also been implicated in adult BD. Further analysis indicated that the observed patterns were mostly driven by BD subjects who were medicated at the time of scanning and had an ADHD diagnosis. Although limited by possible confounding effects of mood state, medication, and other mood comorbidities, these findings serve as evidence of altered neurochemistry in BD youth that is sensitive to medication status and ADHD comorbidity.

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders : Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

The use of component-wise gradient boosting to assess the possible role of cognitive measures as markers of vulnerability to pediatric bipolar disorder.

BACKGROUND AND AIMS: Cognitive impairments are primary hallmarks symptoms of bipolar disorder (BD). Whether these deficits are markers of vulnerability or symptoms of the disease is still unclear. This study used a component-wise gradient (CGB) machine learning algorithm to identify cognitive measures that could accurately differentiate pediatric BD, unaffected offspring of BD parents, and healthy controls. METHODS: 59 healthy controls (HC; 11.19 ± 3.15 yo; 30 girls), 119 children and adolescents with BD (13.31 ± 3.02 yo, 52 girls) and 49 unaffected offspring of BD parents (UO; 9.36 ± 3.18 yo; 22 girls) completed the CANTAB cognitive battery. RESULTS: CGB achieved accuracy of 73.2% and an AUROC of 0.785 in classifying individuals as either BD or non-BD on a dataset held out for validation for testing. The strongest cognitive predictors of BD were measures of processing speed and affective processing. Measures of cognition did not differentiate between UO and HC. CONCLUSIONS: Alterations in processing speed and affective processing are markers of BD in pediatric populations. Longitudinal studies should determine whether UO with a cognitive profile similar to that of HC are at less or equal risk for mood disorders. Future studies should include relevant measures for BD such as verbal memory and genetic risk scores.

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an individual subject level. We suggest a strong clinical utility of the proposed approach in defining and validating biologically meaningful and less heterogeneous clinical sub-phenotypes of major psychiatric disorders.

Interaction of BDNF with cytokines in chronic schizophrenia.

Brain-derived neurotrophic factor (BDNF) interacts with cytokines. Although both BDNF and cytokines occur at abnormal levels in schizophrenia patients, their interactions have not yet been examined. We therefore compared serum BDNF, TNF-α, interleukin (IL)-2, IL-6, and IL-8 levels in 92 chronically medicated schizophrenia patients and 60 healthy controls. We correlated these serum levels within these subject groups with each other and with clinical symptoms assessed according to the Positive and Negative Syndrome Scale (PANSS). Compared to the control group, the schizophrenia patients had significantly lower BDNF and TNF-α levels, and higher IL-2, IL-6, and IL-8 levels. The patients also showed a significant positive correlation between BDNF and both IL-2 and IL-8 levels, and low BDNF and TNF-α levels together were associated with poor performance on the PANSS cognitive factor. Thus, an interaction between cytokines and neurotrophic factors may be implicated in the pathophysiology of chronic schizophrenia. In particular, the cytokine TNF-α may interact with BNDF causing cognitive impairment.

Development and validation of a brain maturation index using longitudinal neuroanatomical scans.

BACKGROUND: Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of neuroanatomical measurements may reliably identify individual subjects deviating from a normative neurodevelopmental trajectory. However, while recent studies have shown great promise in developing accurate brain maturation indices using neuroimaging data and multivariate machine learning techniques, this approach has not been validated using a large sample of longitudinal data from children and adolescents. METHODS: T1-weighted scans from 303 healthy subjects aged 4.88 to 18.35years were acquired from the National Institute of Health (NIH) pediatric repository (http://www.pediatricmri.nih.gov). Out of the 303 subjects, 115 subjects were re-scanned after 2years. The least absolute shrinkage and selection operator algorithm (LASSO) was 'trained' to integrate neuroanatomical changes across chronological age and predict each individual's brain maturity. The resulting brain maturation index was developed using first-visit scans only, and was validated using second-visit scans. RESULTS: We report a high correlation between the first-visit chronological age and brain maturation index (r=0.82, mean absolute error or MAE=1.69years), and a high correlation between the second-visit chronological age and brain maturation index (r=0.83, MAE=1.71years). The brain maturation index captured neuroanatomical volume changes between the first and second visits with an MAE of 0.27years. CONCLUSIONS: The brain maturation index developed in this study accurately predicted individual subjects' brain maturation longitudinally. Due to its strong clinical potentials in identifying individuals with an abnormal brain maturation trajectory, the brain maturation index may allow timely clinical interventions for individuals at risk for psychiatric disorders.

The management of cognitive impairment in bipolar disorder: current status and perspectives.

Bipolar disorder (BD) is associated with important cognitive deficits that persist during the periods of remission. Although these deficits seem to play an important role in the functional impairment experienced by bipolar patients, evidence regarding their clinical management is scant. We revised the databases PubMed, MEDLINE, and clinicaltrials.gov, searching for studies focusing on the pharmacological and nonpharmacological treatment of cognitive deficits among bipolar patients. In addition, a manual search of bibliographical cross-references was performed. Currently, there is no Food and Drug Administration-approved pharmacological agent for the management of cognitive deficits in BD. A number of agents have been tested in the treatment of cognitive deficits in BD, with mixed results. Nonpharmacological interventions, such as cognitive remediation and noninvasive brain stimulation techniques, seem promising, but their role has not yet been properly explored among bipolar patients. Additional studies, aiming at evaluating the efficacy of interventions combining cognitive rehabilitation and biological treatments, are highly desirable.

Prediction of pediatric bipolar disorder using neuroanatomical signatures of the amygdala.

OBJECTIVES: Pediatric bipolar disorder is currently diagnosed based on signs and symptoms, and without objective diagnostic biomarkers. In the present study, we investigated the utility of structural neuroanatomical signatures of the amygdala to objectively differentiate individual subjects with pediatric bipolar disorder from matched healthy controls. METHODS: Structural T1 -weighted neuroimaging scans were obtained from 16 children and adolescents with unmedicated DSM-IV bipolar disorder (11 males, five females) and 16 matched healthy controls (11 males, five females). Voxel-based gray matter morphometric features extracted from a bilateral region-of-interest within the amygdala were used to develop a multivariate pattern analysis model which was utilized in predicting novel or 'unseen' individual subjects as either bipolar disorder or healthy controls. RESULTS: The model assigned 25 out of 32 subjects the correct label (bipolar disorder/healthy) translating to a 78.12% diagnostic accuracy, 81.25% sensitivity, 75.00% specificity, 76.47% positive predictive value, and 80.00% negative predictive value and an area under the receiver operating characteristic curve (ROC) of 0.81. The predictions were significant at p = 0.0014 (χ(2) test p-value). CONCLUSIONS: These results reaffirm previous reports on the existence of neuroanatomical abnormalities in the amygdala of pediatric patients with bipolar disorder. Remarkably, the present study also demonstrates that neuroanatomical signatures of the amygdala can predict individual subjects with bipolar disorder with a relatively high specificity and sensitivity. To the best of our knowledge, this is the first study to present a proof-of-concept diagnostic marker of pediatric bipolar disorder based on structural neuroimaging scans of largely medication-naïve patients.

Impulsivity in children and adolescents with mood disorders and unaffected offspring of bipolar parents.

OBJECTIVE: Increased impulsivity seems to be present across all phases of bipolar disorder (BD). Impulsivity may therefore represent an endophenotype for BD, if it is also found among normal individuals at high genetic risk for mood disorders. In this study, we assessed impulsivity across four different groups of children and adolescents: patients with BD, major depressive disorder (MDD) patients, unaffected offspring of bipolar parents (UO), and healthy controls (HC). SUBJECTS AND METHODS: 52 patients with BD, 31 with MDD, 20 UO, and 45 HC completed the Barratt Impulsiveness Scale (BIS-11), an instrument designed to measure trait impulsivity. RESULTS: UO displayed significantly higher total BIS-11 impulsivity scores than HC (p=0.02) but lower scores than BD patients (F=27.12, p<0.01). Multiple comparison analysis revealed higher BIS-11 total scores among BD patients when compared to HC (p<0.01) and UO (p<0.01). MDD patients had higher BIS-11 scores when compared to HC (p<0.01). Differences between MDD patients and UO, as well as between MDD and BD patients, were not statistically significant. CONCLUSION: Our findings suggest that trait impulsivity is increased among children and adolescents with mood disorders, as well as in unaffected individuals at high genetic risk for BD.

Trait impulsivity is increased in bipolar disorder patients with comorbid alcohol use disorders.

BACKGROUND: Up to 60% of bipolar disorder (BD) patients develop alcohol use disorders (AUD) at some point in their lives. The causes of this highly prevalent comorbidity are unknown. High trait impulsivity characterizes both isolated BD and AUD and may be a link to explain the association between BD and AUD. In this study, our aims were to investigate whether BD patients with comorbid AUD would present higher trait impulsivity levels compared to BD patients without comorbid AUD, and whether trait impulsivity levels differ within subgroups of BD according to the subcategory of AUD (abuse vs. dependence, alcoholism alone vs. alcoholism plus drug use disorders). SAMPLING AND METHODS: Forty-seven outpatients with BD with comorbid AUD (alcoholic BD group) were compared to 66 outpatients with BD alone (nonalcoholic BD group) and to 90 healthy controls (HC). BD and AUD diagnoses were obtained using the Structured Clinical Interview for DSM-IV diagnoses. Impulsivity was assessed using the Barratt Impulsiveness Scale (BIS-11), a self-report instrument that measures trait impulsivity in three domains: nonplanning, attentional and motor. RESULTS: Alcoholic BD patients scored significantly higher than nonalcoholic BD and HC on the total and on each subscale BIS scores. Within the alcoholic BD patients, alcohol abusers and alcohol dependents did not statistically differ from each other on the BIS-11 scores. BD patients with AUD plus drug use disorders presented statistically higher nonplanning impulsivity than BD patients with AUD alone. CONCLUSIONS: This was a cross-sectional study and causal inferences about the relationship between impulsivity and the comorbidity phenomenon cannot be made. Increased impulsivity may be a trait marker for the co-occurrence between BD and AUD, and mediate some severe manifestations of this comorbidity.

Processing speed - A potential candidate cognitive endophenotype for bipolar disorder.

Background: Bipolar disorder (BD) is a chronic multifactorial disorder that presents with cognitive impairment as one of its main features, in patients as well as in their first-degree relatives. However, the profile of cognitive dysfunction in BD patients and their relatives is not yet well defined. Various neurocognitive deficits have been proposed as endophenotypes for BD. In the present study, we explored the susceptibility to neurocognitive deficits in BD patients and their siblings compared to healthy controls. Method: A sample consisting of patients diagnosed with BD (N=37), their unaffected siblings (N=30) and a healthy control group (N=39) was assessed using the Brief Assessment of Cognition for Affective Disorders (BAC-A) battery of tests in various cognitive domains: memory, processing speed, working memory, reasoning and problem solving, and affective processing. Results: Compared to healthy controls, BD patients and their unaffected siblings showed deficits in attention and motor speed, or processing speed as measured by the Symbol coding task (p = 0.008), as well as a similar degree of impairment (p = 1.000). Limitations: The lack of statistically significant findings in the other cognitive domains could be related to differences in task difficulty. Most patients were taking psychotropic medication with varying effects on cognition and being treated as outpatients, implying a currently higher level of functioning, which may limit extrapolation of the sample to the general population of BD patients. Conclusions: These results support the view of considering processing speed as an endophenotype for bipolar disorder.

The Greater Houston Area Bipolar Registry-Clinical and Neurobiological Trajectories of Children and Adolescents With Bipolar Disorders and High-Risk Unaffected Offspring.

The aims of this article are to discuss the rationale, design, and procedures of the Greater Houston Area Bipolar Registry (HBR), which aims at contributing to the effort involved in the investigation of neurobiological mechanisms underlying bipolar disorder (BD) as well as to identify clinical and neurobiological markers able to predict BD clinical course. The article will also briefly discuss examples of other initiatives that have made fundamental contributions to the field. This will be a longitudinal study with participants aged 6-17 at the time of enrollment. Participants will be required to meet diagnostic criteria for BD, or to be offspring of a parent with BD. We will also enroll healthy controls. Besides clinical information, which includes neurocognitive performance, participants will be asked to provide blood and saliva samples as well as to perform neuroimaging exams at baseline and follow-ups. Several studies point to the existence of genetic, inflammatory, and brain imaging alterations between individuals at higher genetic risk for BD compared with healthy controls. Longitudinal designs have shown high conversion rates to BD among high-risk offspring, with attempts to identify clinical predictors of disease onset, as well as clarifying the burden associated with environmental stressors. The HBR will help in the worldwide effort investigating the clinical course and neurobiological mechanisms of affected and high-risk children and adolescents with BD.

Evidence of altered metabolism of cellular membranes in bipolar disorder comorbid with post-traumatic stress disorder.

In proton magnetic resonance spectroscopy (¹H MRS) studies, aberrant levels of choline-containing compounds that include glycerophosphocholine plus phosphocholine (GPC+PC), can signify alterations in the metabolism of cellular membrane phospholipids (MPLs) from a healthy baseline. In a recent ¹H MRS study, we reported increased GPC+PC in cortical and subcortical areas of adult patients with bipolar disorder I (BP-I). Post-traumatic stress disorder (PTSD) can worsen the severity of BP-I, but it is unclear whether the effect of a PTSD comorbidity in BP-I is associated with altered MPL metabolism. The purpose of this study was to re-investigate the ¹H MRS data to determine whether the regional extent of elevated GPC+PC was greater in BP-I patients with PTSD (BP-I/wPTSD) compared to BP-I without comorbid PTSD (BP-I/woPTSD) patients and healthy controls. GPC+PC levels from four brain areas [the anterior cingulate cortex (ACC), anterior-dorsal ACC, caudate, and putamen] were measured in 14 BP-I/wPTSD, 36 BP-I/woPTSD, and 44 healthy controls using a multi-voxel 1H MRS approach on a 3 Tesla system with high spatial resolution and absolute quantification. Results show a significant increase in GPC+PC levels from the caudate and putamen of BP-I/wPTSD patients compared to healthy controls (P<0.05) and in the putamen compared to BP-I/woPTSD patients (P<0.05). These findings are consistent with evidence of elevated degradation of MPLs in the neuropil that is more pronounced in BP-I patients with comorbid PTSD.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Anterior cingulate volumes associated with trait impulsivity in individuals with bipolar disorder.

OBJECTIVE: Impulsivity is associated with the clinical outcome and likelihood of risky behaviors among bipolar disorder (BD) patients. Our previous study showed an inverse relationship between impulsivity and orbitofrontal cortex (OFC) volume in healthy subjects. We hypothesized that BD patients would show an inverse relationship between impulsivity and volumes of the OFC, anterior cingulate cortex (ACC), medial prefrontal cortex, and amygdala, which have been implicated in the pathophysiology of BD. METHODS: Sixty-three BD patients were studied (mean +/- SD age = 38.2 +/- 11.5 years; 79% female). The Barratt Impulsiveness Scale (BIS), version 11A, was used to assess trait impulsivity. Images were processed using SPM2 and an optimized voxel-based morphometry protocol. We examined the correlations between BIS scores and the gray matter (GM) and white matter (WM) volumes of the prespecified regions. RESULTS: Left rostral ACC GM volume was inversely correlated with the BIS total score (t = 3.95, p(corrected) = 0.003) and the BIS motor score (t = 5.22, p(corrected) < 0.001). In contrast to our hypothesis, OFC volumes were not significantly associated with impulsivity in BD. No WM volume of any structure was significantly correlated with impulsivity. No statistical association between any clinical variable and the rostral ACC GM volumes reached significance. CONCLUSIONS: Based on our previous findings and the current results, impulsivity may have a different neural representation in BD and healthy subjects, and the ACC may be involved in the pathophysiology of abnormal impulsivity regulation in BD patients.

Smaller left anterior cingulate cortex in non-bipolar relatives of patients with bipolar disorder.

OBJECTIVE: Bipolar disorder (BD) is highly heritable. The present study aimed at identifying brain morphometric features that could represent markers of BD vulnerability in non-bipolar relatives of bipolar patients. METHODS: In the present study, structural magnetic resonance imaging brain scans were acquired from a total of 93 subjects, including 31 patients with BD, 31 non-bipolar relatives of BD patients, and 31 healthy controls. Volumetric measurements of the anterior cingulate cortex (ACC), lateral ventricles, amygdala, and hippocampus were completed using the automated software FreeSurfer. RESULTS: Analysis of covariance (with age, gender, and intracranial volume as covariates) indicated smaller left ACC volumes in unaffected relatives as compared to healthy controls and BD patients (p = 0.004 and p = 0.037, respectively). No additional statistically significant differences were detected for other brain structures. CONCLUSION: Our findings suggest smaller left ACC volume as a viable biomarker candidate for BD.

MRI acoustic noise-modulated computer animations for patient distraction and entertainment with application in pediatric psychiatric patients.

PURPOSE: To reduce patient anxiety caused by the MRI scanner acoustic noise. MATERIAL AND METHODS: We developed a simple and low-cost system for patient distraction using visual computer animations that were synchronized to the MRI scanner's acoustic noise during the MRI exam. The system was implemented on a 3T MRI system and tested in 28 pediatric patients with bipolar disorder. The patients were randomized to receive noise-synchronized animations in the form of abstract animations in addition to music (n = 13, F/M = 6/7, age = 10.9 ±â€¯2.5 years) or, as a control, receive only music (n = 15, F/M = 7/8, age = 11.6 ±â€¯2.3 years). After completion of the scans, all subjects answered a questionnaire about their scan experience and the perceived scan duration. RESULTS: The scan duration with multisensory input (animations and music) was perceived to be ~15% shorter than in the control group (43 min vs. 50 min, P < 0.05). However, the overall scan experience was scored less favorably (3.9 vs. 4.6 in the control group, P < 0.04). CONCLUSIONS: This simple system provided patient distraction and entertainment leading to perceived shorter scan times, but the provided visualization with abstract animations was not favored by this patient cohort.

Illness duration and total brain gray matter in bipolar disorder: evidence for neurodegeneration?

Previous studies have suggested that bipolar disorder (BD) is associated with alterations in neuronal plasticity, but the effects of the progression of illness on brain anatomy have been poorly investigated. We studied the correlation between length of illness, age, age at onset, and the number of previous episodes and total brain, total gray, and total white matter volumes in BD, unipolar (UP) and healthy control (HC) subjects. Thirty-six BD, 31 UP and 55 HCs underwent a 1.5 T brain magnetic resonance imaging scan, and gray and white matter volumes were manually traced blinded to the subjects' diagnosis. Partial correlation analysis showed that length of illness was inversely correlated with total gray matter volume after adjusting for total intracranial volume in BD (r(p)= -0.51; p=0.003) but not in UP subjects (r(p)= -0.23; p=0.21). Age at illness onset and the number of previous episodes were not significantly correlated with gray matter volumes in BD or UP subjects. No significant correlation with total white matter volume was observed. These results suggest that the progression of illness may be associated with abnormal cellular plasticity. Prospective longitudinal studies are necessary to elucidate the long-term effects of illness progression on brain structure in major mood disorders.