Genomic loci influence patterns of structural covariance in the human brain

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Inflammatory cytokines and white matter microstructure in the acute phase of first-episode psychosis: A longitudinal study

OBJECTIVES

Schizophrenia-related psychosis is associated with abnormalities in white matter (WM) microstructure and structural brain dysconnectivity. However, the pathological process underlying such changes is unknown. We sought to investigate the potential association between peripheral cytokine levels and WM microstructure during the acute phase of first-episode psychosis (FEP) in a cohort of drug-naïve patients.

METHODS

Twenty-five non-affective FEP patients and 69 healthy controls underwent MRI scanning and blood collection at study entry. After achieving clinical remission, 21 FEP were reassessed; 38 age and biological sex-matched controls also had a second assessment. We measured fractional anisotropy (FA) of selected WM regions-of-interest (ROIs) and plasma levels of four cytokines (IL-6, IL-10, IFN-γ, and TNF-α).

RESULTS

At baseline (acute psychosis), the FEP group showed reduced FA relative to controls in half the examined ROIs. Within the FEP group, IL-6 levels were negatively correlated with FA values. Longitudinally, patients showed increments of FA in several ROIs affected at baseline, and such changes were associated with reductions in IL-6 levels.

CONCLUSIONS

A state-dependent process involving an interplay between a pro-inflammatory cytokine and brain WM might be associated with the clinical manifestation of FEP. This association suggests a deleterious effect of IL-6 on WM tracts during the acute phase of psychosis.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population

Importance

Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment.

Objective

To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations.

Design, Setting, and Participants

This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022.

Main Outcomes and Measures

The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations.

Results

Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6).

Conclusions and Relevance

This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Schizophrenia Imaging Signatures and Their Associations With Cognition, Psychopathology, and Genetics in the General Population

OBJECTIVE

The prevalence and significance of schizophrenia-related phenotypes at the population level is debated in the literature. Here, the authors assessed whether two recently reported neuroanatomical signatures of schizophrenia-signature 1, with widespread reduction of gray matter volume, and signature 2, with increased striatal volume-could be replicated in an independent schizophrenia sample, and investigated whether expression of these signatures can be detected at the population level and how they relate to cognition, psychosis spectrum symptoms, and schizophrenia genetic risk.

METHODS

This cross-sectional study used an independent schizophrenia-control sample (N=347; ages 16-57 years) for replication of imaging signatures, and then examined two independent population-level data sets: typically developing youths and youths with psychosis spectrum symptoms in the Philadelphia Neurodevelopmental Cohort (N=359; ages 16-23 years) and adults in the UK Biobank study (N=836; ages 44-50 years). The authors quantified signature expression using support-vector machine learning and compared cognition, psychopathology, and polygenic risk between signatures.

RESULTS

Two neuroanatomical signatures of schizophrenia were replicated. Signature 1 but not signature 2 was significantly more common in youths with psychosis spectrum symptoms than in typically developing youths, whereas signature 2 frequency was similar in the two groups. In both youths and adults, signature 1 was associated with worse cognitive performance than signature 2. Compared with adults with neither signature, adults expressing signature 1 had elevated schizophrenia polygenic risk scores, but this was not seen for signature 2.

CONCLUSIONS

The authors successfully replicated two neuroanatomical signatures of schizophrenia and describe their prevalence in population-based samples of youths and adults. They further demonstrated distinct relationships of these signatures with psychosis symptoms, cognition, and genetic risk, potentially reflecting underlying neurobiological vulnerability.

Lithium increases cortical and subcortical volumes in subjects with bipolar disorder

Bipolar disorder (BD) is a highly variable and burdensome disease for patients and caregivers. A BD diagnosis almost triples the likelihood of developing dementia as the disease progresses. Neurocognitive reserve appears to be one of the most important influences on lifelong functional outcomes and quality of life in BD. Though several prior studies have assessed the effects of lithium on regional gray and white matter volumes in this population, representative cohorts are typically middle-aged, have a more severe pathology, and are not as commonly assessed in the depressive phase (which represents the majority of most patients' lifespans outside of remission). Here we have shown that positive adaptations with lithium can be observed throughout the brain after only six weeks of monotherapy at low-therapeutic serum levels. Importantly, these results remove some confounders seen in prior studies (patients were treatment free at time of enrollment and mostly treatment naïve). This cohort also includes underrepresented demographics in the literature (young adult patients, mostly bipolar II, and exclusively in the depressed phase). These findings bolster the extensive body of evidence in support of long-term lithium therapy in BD, furthering the possibility of its expanded use to wider demographics.

The role of lithium treatment on comorbid anxiety symptoms in patients with bipolar depression

BACKGROUND

Comorbid anxiety is pervasive and carries an immense psychosocial burden for patients with bipolar disorder. Despite this, trials reporting anxiety-related outcomes in this population are uncommon, particularly with regards to monotherapies.

METHODS

Patients (n = 31) with both bipolar I or II disorder in current depressive episodes were enrolled in a six-week, open-label, single-center trial assessing the efficacy of lithium monotherapy in treating symptoms depression and comorbid anxiety. Patients were mostly medication-free and lithium-naïve at baseline.

RESULTS

Significant improvements in depression (HAMD) and anxiety (HAM-A) were observed at the six-week endpoint, with remission and response rates greater than 50%. There was a positive correlation between endpoint HAM-A scores and HAM-D scores, r = 0.80, (p < 0.01). Improvements were realized at low serum lithium concentrations (0.49 ± 0.20 mEq/L).

LIMITATIONS

Lack of placebo control and small sample size warrants validation in larger randomized studies.

CONCLUSIONS

Taken in the context of prior evidence, lithium may have an important role in treating comorbid anxiety in bipolar disorder, both as adjunct and monotherapy. Lower doses of lithium may provide equivalent efficacy and enhance tolerability and compliance.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Greater male than female variability in regional brain structure across the lifespan

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.

Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes

Disease heterogeneity is a significant obstacle to understanding pathological processes and delivering precision diagnostics and treatment. Clustering methods have gained popularity for stratifying patients into subpopulations (i.e., subtypes) of brain diseases using imaging data. However, unsupervised clustering approaches are often confounded by anatomical and functional variations not related to a disease or pathology of interest. Semi-supervised clustering techniques have been proposed to overcome this and, therefore, capture disease-specific patterns more effectively. An additional limitation of both unsupervised and semi-supervised conventional machine learning methods is that they typically model, learn and infer from data using a basis of feature sets pre-defined at a fixed anatomical or functional scale (e.g., atlas-based regions of interest). Herein we propose a novel method, "Multi-scAle heteroGeneity analysIs and Clustering" (MAGIC), to depict the multi-scale presentation of disease heterogeneity, which builds on a previously proposed semi-supervised clustering method, HYDRA. It derives multi-scale and clinically interpretable feature representations and exploits a double-cyclic optimization procedure to effectively drive identification of inter-scale-consistent disease subtypes. More importantly, to understand the conditions under which the clustering model can estimate true heterogeneity related to diseases, we conducted extensive and systematic semi-simulated experiments to evaluate the proposed method on a sizeable healthy control sample from the UK Biobank (N = 4403). We then applied MAGIC to imaging data from Alzheimer's disease (ADNI, N = 1728) and schizophrenia (PHENOM, N = 1166) patients to demonstrate its potential and challenges in dissecting the neuroanatomical heterogeneity of common brain diseases. Taken together, we aim to provide guidance regarding when such analyses can succeed or should be taken with caution. The code of the proposed method is publicly available at https://github.com/anbai106/MAGIC.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

OBJECTIVE

Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

METHODS

We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

RESULTS

There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

CONCLUSION

Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

IMPORTANCE

Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.

OBJECTIVE

To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.

DESIGN, SETTING, AND PARTICIPANTS

Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.

MAIN OUTCOMES AND MEASURES

Interregional profiles of group difference in cortical thickness between cases and controls.

RESULTS

A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.

CONCLUSIONS AND RELEVANCE

In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

METHODS

Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).

RESULTS

No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.

CONCLUSIONS

The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.

Plasma Metabolite Profiles in First Episode Psychosis: Exploring Symptoms Heterogeneity/Severity in Schizophrenia and Bipolar Disorder Cohorts

INTRODUCTION

The first symptoms of psychosis are frequently shared amongst several neuropsychiatry disorders, which makes the differentiation by clinical diagnosis challenging. Early recognition of symptoms is important in the management of psychosis. Therefore, the implementation of molecular biomarkers will be crucial for transforming the currently used diagnostic and therapeutic approach, improving insights into the underlying biological processes and clinical management.

OBJECTIVES

To define a set of metabolites that supports diagnosis or prognosis of schizophrenia (SCZ) and bipolar disorder (BD) at first onset psychosis.

METHODS

Plasma samples from 55 drug-naïve patients, 28 SCZ and 27 BD, and 42 healthy controls (HC). All participants underwent a seminaturalistic treatment regimen, clinically evaluated on a weekly basis until achieving clinical remission. All clinical or sociodemographic aspects considered for this study were equivalent between the groups at first-onset psychosis time point. The plasma samples were analyzed by untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) using reversed-phase and hydrophilic interaction chromatography. The acquired molecular features were analyzed with MetaboAnalyst.

RESULTS

We identified two patient groups with different metabolite profiles. Both groups are composed of SCZ and BD patients. We found differences between these two groups regarding general symptoms of PANSS score after remission (p = 0.008), and the improvement of general symptoms (delta of the score at remission minus the baseline) (-0.50 vs. -0.33, p = 0.019).

CONCLUSION

Our results suggest that plasma metabolite profiles cluster clinical remission phenotypes based on PANSS general psychopathology scores.

Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

OBJECTIVE

Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies.

METHODS

Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707).

RESULTS

In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample.

CONCLUSIONS

Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

10Kin1day: A Bottom-Up Neuroimaging Initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

BACKGROUND

The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.

METHODS

The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.

RESULTS

Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.

CONCLUSIONS

The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Classification of multi-site MR images in the presence of heterogeneity using multi-task learning

With the advent of Big Data Imaging Analytics applied to neuroimaging, datasets from multiple sites need to be pooled into larger samples. However, heterogeneity across different scanners, protocols and populations, renders the task of finding underlying disease signatures challenging. The current work investigates the value of multi-task learning in finding disease signatures that generalize across studies and populations. Herein, we present a multi-task learning type of formulation, in which different tasks are from different studies and populations being pooled together. We test this approach in an MRI study of the neuroanatomy of schizophrenia (SCZ) by pooling data from 3 different sites and populations: Philadelphia, Sao Paulo and Tianjin (50 controls and 50 patients from each site), which posed integration challenges due to variability in disease chronicity, treatment exposure, and data collection. Some existing methods are also tested for comparison purposes. Experiments show that classification accuracy of multi-site data outperformed that of single-site data and pooled data using multi-task feature learning, and also outperformed other comparison methods. Several anatomical regions were identified to be common discriminant features across sites. These included prefrontal, superior temporal, insular, anterior cingulate cortex, temporo-limbic and striatal regions consistently implicated in the pathophysiology of schizophrenia, as well as the cerebellum, precuneus, and fusiform, middle temporal, inferior parietal, postcentral, angular, lingual and middle occipital gyri. These results indicate that the proposed multi-task learning method is robust in finding consistent and reliable structural brain abnormalities associated with SCZ across different sites, in the presence of multiple sources of heterogeneity.

Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10^-21), left fusiform gyrus (d=-0.288; P=8.25 × 10^-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10^-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

Neurobiological support to the diagnosis of ADHD in stimulant-naïve adults: pattern recognition analyses of MRI data

OBJECTIVE

In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning-based pattern classification methods to structural MRI and diffusion tensor imaging (DTI) data obtained from stimulant-naïve adults with childhood-onset ADHD and healthy controls (HC).

METHOD

Sixty-seven ADHD patients and 66 HC underwent high-resolution T1-weighted and DTI acquisitions. A support vector machine (SVM) classifier with a non-linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain.

RESULTS

The discrimination between a mixed-gender ADHD subgroup and individually matched HC (n = 58 each) yielded area-under-the-curve (AUC) and diagnostic accuracy (DA) values of up to 0.71% and 66% (P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% (P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC).

CONCLUSION

Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.

State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis

BACKGROUND

Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated.

METHODS

Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps.

RESULTS

At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected).

CONCLUSIONS

WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging

As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability.

High IQ May "Mask" the Diagnosis of ADHD by Compensating for Deficits in Executive Functions in Treatment-Naïve Adults With ADHD

OBJECTIVE

To evaluate and compare the performance of adults with ADHD with high and standard IQ in executive functions (EF) tasks.

METHOD

We investigated the neuropsychological performance of 51 adults with ADHD, compared with 33 healthy controls (HC) while performing a wide battery of neuropsychological tests that measure executive functioning. Adults with clinical diagnosis of ADHD were divided into two groups according to their IQ level (IQ ≥ 110-ADHD group with more elevated IQ, and IQ < 110-ADHD group with standard IQ).

RESULTS

The ADHD group with standard IQ presented a worse executive functioning compared with the HC group in the following measures: Stroop 2 ( p = .000) and 3 ( p = .000), Trail Making Test (TMT) B ( p = .005), Wisconsin Card-Sorting Test (WCST)-perseverative errors ( p = .022) and failures to maintain set ( p = .020), Continuous Performance Test (CPT)-omission errors ( p = .005) and commission errors ( p = .000), and Frontal Assessment Battery (FAB)-conceptualization ( p = .016). The ADHD group with more elevated IQ presented only impairments in the CPT-commission errors ( p = .019) when compared with the control group.

CONCLUSION

Adults with ADHD and more elevated IQ show less evidence of executive functioning deficits compared with those with ADHD and standard IQ, suggesting that a higher degree of intellectual efficiency may compensate deficits in executive functions, leading to problems in establishing a precise clinical diagnosis.

Challenging Treatment-Resistant Major Depressive Disorder: A Roadmap for Improved Therapeutics

Major depressive disorder (MDD) is associated with a significant burden and costs to the society. As remission of depressive symptoms is achieved in only one-third of the MDD patients after the first antidepressant trial, unsuccessful treatments contribute largely to the observed suffering and social costs of MDD. The present article provides a summary of the therapeutic strategies that have been tested for treatment-resistant depression (TRD). A computerized search on MedLine/PubMed database from 1975 to September 2014 was performed, using the keywords “treatment-resistant depression”, “major depressive disorder”, “adjunctive”, “refractory” and “augmentation”. From the 581 articles retrieved, two authors selected 79 papers. A manual searching further considered relevant articles of the reference lists. The evidence found supports adding or switching to another antidepressant from a different class is an effective strategy in more severe MDD after failure to an initial antidepressant trial. Also, in subjects resistant to two or more classes of antidepressants, some augmentation strategies and antidepressant combinations should be considered, although the overall response and remission rates are relatively low, except for fast acting glutamatergic modulators. The wide range of available treatments for TRD reflects the complexity of MDD, which does not underlie diverse key features of the disorder. Larger and well-designed studies applying dimensional approaches to measure efficacy and effectiveness are warranted.

A Selective Association between Central and Peripheral Lithium Levels in Remitters in Bipolar Depression: A 3T-(7) Li Magnetic Resonance Spectroscopy Study

OBJECTIVE

The objective of this study was to evaluate brain lithium levels using (7) Li magnetic resonance spectroscopy after 6 weeks of lithium therapy in bipolar depression to test the hypothesis that brain and plasma lithium are correlated. It was also tested whether responders and remitters have different pharmacokinetics, blood and brain lithium levels (ratio) compared with those presenting suboptimal antidepressant improvement.

METHOD

Twenty-three patients with bipolar disorder (I and II) during depressive episodes were included and followed up for 6 weeks at the University of Sao Paulo using flexible dose of lithium (450-900 mg/day). Sixteen patients were drug-naïve. At endpoint, patients underwent a (7) Li-MRS scan and brain lithium concentrations were calculated.

RESULTS

A significant association between central and peripheral lithium levels was found only in remitters (r = 0.7, P = 0.004) but not in non-remitters (r = -0.12, P = 0.76). Also, brain lithium (but not plasma) was inversely correlated with age (r = -0.46, P = 0.025). Plasma lithium did not correlate with any clinical outcome, lithium dosage or adverse effects.

CONCLUSION

These findings suggest that non-remitters may not transport lithium properly to the brain, which may underlie treatment resistance to lithium in BD. Future studies with (7) Li-MRS integrated with the evaluation of blood-brain barrier transport mechanisms and longitudinal clinical outcomes in BD and aging are warranted.

A Longitudinal (6-week) 3T (1)H-MRS Study on the Effects of Lithium Treatment on Anterior Cingulate Cortex Metabolites in Bipolar Depression

The anterior cingulate cortex (ACC) is a key area in mood regulation. To date, no longitudinal study has specifically evaluated lithium׳s effects on ACC metabolites using (1)H-MRS, as well as its association with clinical improvement in bipolar depression. This (1)H-MRS (TE=35ms) study evaluated 24 drug-free BD patients during depressive episodes and after lithium treatment at therapeutic levels. Brain metabolite levels (N-acetyl aspartate (NAA), creatine (tCr), choline, myo-inositol, and glutamate levels) were measured in the ACC at baseline (week 0) and after lithium monotherapy (week 6). The present investigation showed that ACC glutamate (Glu/tCr) and glutamate+glutamine (Glx/tCr) significantly increased after six weeks of lithium therapy. Regarding the association with clinical improvement, remitters showed an increase in myoinositol levels (mI/tCr) after lithium treatment compared to non-remitters. The present findings reinforce a role for ACC glutamate-glutamine cycling and myoinositol pathway as key targets for lithium׳s therapeutic effects in BD.

Cytochrome P450 genotypes are not associated with refractoriness to antipsychotic treatment

Evidence validating the influence of the cytochrome P450 (CYP) 2D6 and 2C19 enzymes genetic polymorphisms in the response to antipsychotics is scarce. We examined the hypothesis that a higher prevalence of CYP2D6 and/or CYP2C19 ultra rapid metabolizers might be found among refractory schizophrenia patients. Three groups were studied: refractory and non-refractory schizophrenia patients, and healthy controls. Participants were genotyped for CYP2D6 and CYP2C19 polymorphisms and classified in metabolic phenotypes. No between-group differences in the distribution of the phenotypes were found. Therefore, our findings do not support the CYPs 2D6 and 2C19 genotyping in the prediction of therapeutic response in schizophrenia.

Regulation of leukocyte tricarboxylic acid cycle in drug-naïve Bipolar Disorder

Several lines of evidence suggest a role for mitochondrial dysfunction in the pathophysiology of bipolar disorder (BD). The tricarboxylic acid cycle (TCA cycle) is fundamental for mitochondrial energy production and produces substrates used in oxidative phosphorylation by the mitochondrial electron transport chain. The activity of the key TCA cycle enzymes citrate synthase, malate dehydrogenase, and succinate dehydrogenase has never been evaluated in BD. In the present study, these enzymes were assayed from leukocytes of drug-naïve BD patients in a major depressive episode (n=18) and compared to 24 age-matched healthy controls. Drug-naïve BD patients did not show differences in activities of citrate synthase (p=0.79), malate dehydrogenase (p=0.17), and succinate dehydrogenase (p=0.35) compared with healthy controls. No correlation between any TCA cycle enzyme activity and severity of depressive symptoms was observed. Overall, these data suggest that the activities of the TCA cycle enzymes are not altered in major depressive episodes of recent-onset BD, which may support the concept of illness staging and neuroprogression in BD.

Decreased AKT1/mTOR pathway mRNA expression in short-term bipolar disorder

Strong evidence implicates intracellular signaling cascades dysfunction in the pathophysiology of Bipolar Disorder (BD). Regulation of AKT/mTOR pathway is a critical signaling pathway in synaptic neurotransmission and plasticity, also modulating cell proliferation and migration. Gene expression of the AKT/mTOR pathway was assessed in 25 BD (DSM-IV-TR criteria) unmedicated depressed individuals at baseline and after 6 weeks of lithium therapy and 31 matched healthy controls. Decreases in blood AKT1 and mTOR mRNA expression, as well as in BAD/BCL-2 expression ratio were observed in short-term BD patients during depressive episodes in comparison to healthy controls. There was no significant change in the expression of AKT1, mTOR, BCL-2, BAD and NDUFA6 after lithium therapy in the total group of BD subjects. However, the changes in AKT1 expression after lithium treatment were positively correlated with depression improvement. An integrated activity within this pathway was observed at both baseline and post-treatment. The present results support an integrated AKT/mTOR signaling pathway activity in a similar fashion to the described in previous human postmortem and rodents brain studies. Overall, the results reinforce a role for AKT1 and mTOR in the pathophysiology of BD and support the relevance of blood mRNA expression as a valid surrogate biological source to study brain intracellular signaling cascades changes and convergent molecular pathways in psychiatric disorders.

What determines continuing grey matter changes in first-episode schizophrenia and affective psychosis?

BACKGROUND

Magnetic resonance imaging (MRI) studies have shown that brain abnormalities in psychosis might be progressive during the first years of illness. We sought to determine whether first-episode psychosis (FEP) subjects show progressive regional grey matter (GM) changes compared with controls, and whether those changes are associated with diagnosis, illness course or antipsychotic (AP) use.

METHOD

Thirty-two subjects with first-episode schizophrenia-spectrum disorders (FESZ), 24 patients with first-episode affective psychoses (FEAP) and 34 controls recruited using a population-based design underwent structural MRI scanning at baseline and at a 5-year follow-up. Regional GM volumes were assessed with voxel-based morphometry (VBM). Patients were treated at community settings, and about half of them remained mainly untreated.

RESULTS

No significant progressive changes in GM regional volumes were observed in either the FESZ or FEAP group overall. However, FESZ subjects with a non-remitting course showed GM decrements in the left superior temporal gyrus (STG) and insula relative to remitted FESZ subjects. Non-remitted FEAP subjects exhibited a GM decrease in the dorsolateral prefrontal cortex (DLPFC) bilaterally in comparison to remitted FEAP subjects. Among FESZ subjects, AP use was associated with regional GM decrements in the right insula and increments in the cerebellum.

CONCLUSIONS

Our results suggest that the progression of brain abnormalities in FEP subjects is restricted to those with a poor outcome and differs between diagnosis subgroups. AP intake is associated with a different pattern of GM reductions over time.

Lithium increases platelet serine-9 phosphorylated GSK-3β levels in drug-free bipolar disorder during depressive episodes

BACKGROUND

Glycogen synthase kinase-3 β (GSK3β) is an intracellular enzyme directly implicated in several neural processes relevant to bipolar disorder (BD) pathophysiology. GSK3β is also an important target for lithium and antidepressants. When phosphorylated at serine-9, GSK3β becomes inactive. Few studies evaluated serine-9 phosphorylated GSK3β (phospho-GSK3β) levels in BD subjects in vivo and no study has assessed it specifically in bipolar depression. Also, the effect of lithium monotherapy on GSK3β has never been studied in humans.

METHODS

In 27 patients with bipolar depression, total GSK3β and phospho-GSK3β were assessed in platelets by enzyme immunometric assay. Subjects were evaluated before and after 6 weeks of lithium treatment at therapeutic levels. Healthy subjects (n = 22) were used as a control group.

RESULTS

No differences in phospho-GSK3β or total GSK3β were observed when comparing drug-free BD subjects in depression and healthy controls. Baseline HAM-D scores were not correlated with phospho-GSK3β and total GSK3β levels. From baseline to endpoint, lithium treatment inactivated GSK3β by significantly increasing phospho-GSK3β levels (p = 0.010). Clinical improvement (baseline HAM-D - endpoint HAM-D) negatively correlated with the increase in phospho-GSK3β (p = 0.03).

CONCLUSION

The present results show that lithium inactivates platelet GSK3β in BD during mood episodes. No direct association with pathophysiology of BD was observed. Further studies are needed to clarify the role of GSK3β as a key biomarker in BD and its association with treatment response as well as the relevance of GSK3β in other neuropsychiatric disorders and as a new therapeutic target per se.

Bimodal effect of lithium plasma levels on hippocampal glutamate concentrations in bipolar II depression: a pilot study

BACKGROUND

The hippocampus has been highly implicated in the pathophysiology of bipolar disorder (BD). Nevertheless, no study has longitudinally evaluated hippocampal metabolite levels in bipolar depression under treatment with lithium.

METHODS

Nineteen medication-free BD patients (78.9% treatment-naïve and 73.7% with BD type II) presenting an acute depressive episode and 17 healthy controls were studied. Patients were treated for 6 weeks with lithium in an open-label trial. N-acetyl aspartate (NAA), creatine, choline, myo-Inositol, and glutamate levels were assessed in the left hippocampus before (week 0) and after (week 6) lithium treatment using 3T proton magnetic resonance spectroscopy (1H-MRS). The metabolite concentrations were estimated using internal water as reference and voxel segmentation for partial volume correction.

RESULTS

At baseline, acutely depressed BD patients and healthy controls exhibited similar hippocampal metabolites concentrations, with no changes after 6 weeks of lithium monotherapy. A significant correlation between antidepressant efficacy and increases in NAA concentration over time was observed. Also, there was a significant positive correlation between the changes in glutamate concentrations over follow-up and plasma lithium levels at endpoint. Mixed effects model analysis revealed a bimodal effect of lithium plasma levels in hippocampal glutamate concentrations: levels of 0.2 to 0.49 mmol/L (n=9) were associated with a decrease in glutamate concentrations, whereas the subgroup of BD subjects with "standard" lithium levels (≥ 0.50 mmol/L; n = 10) showed an overall increase in glutamate concentrations over time.

CONCLUSIONS

These preliminary results suggest that lithium has a bimodal action in hippocampal glutamate concentration depending on the plasma levels.

Elevated neurotrophin-3 and neurotrophin 4/5 levels in unmedicated bipolar depression and the effects of lithium

BACKGROUND

Bipolar disorder (BD) has been associated with diverse abnormalities in neural plasticity and cellular resilience. Neurotrophin-3 (NT-3) and neurotrophin-4/5 (NT-4/5) support synaptic neuronal survival and differentiation. NT-3 and NT-4/5 levels were found to be altered in BD, potentially representing a physiological response against cellular stress. However, the use of psychopharmacological agents and heterogeneous mood states may constitute important biases in such studies. Thus, we aimed to assess NT-3 and NT-4/5 levels in medication-free BD type I or II individuals in a current depressive episode, before and after 6 weeks of lithium monotherapy and matched with healthy controls.

METHODS

Twenty-three patients with BD type I or II during a depressive episode and 28 healthy controls were studied. Patients were required to have a 21-item Hamilton Depression Rating Scale score ≥18 and had not undergone any psychopharmacological treatment for at least 6 weeks prior to study entry. Patients were treated with lithium for 6 weeks and plasma NT-3 and NT-4/5 levels were determined at baseline and endpoint using ELISA method.

RESULTS

Baseline plasma levels of both NT-3 and NT-4/5 were significantly increased in acutely depressed BD subjects in comparison to healthy controls (p=0.040 and 0.039, respectively). The NT-3 and NT-4/5 levels did not significantly change after lithium treatment. NT-3 and NT-4/5 levels were positively correlated to illness duration in BD (p=0.032 and 0.034, respectively).

CONCLUSION

Our findings suggest that NT-3 and NT-4/5 levels are increased in the depressive phase of BD, which seems directly associated with illness duration. The increased levels of NT-3 and NT-4/5 may underlie a biological response to cellular stress associated with the course of BD.

Increased plasma levels of soluble TNF receptors 1 and 2 in bipolar depression and impact of lithium treatment

OBJECTIVE

TNF system (TNF and its soluble receptors sTNFR1 and 2) has been investigated as a potential molecular target in bipolar disorder. The aim of the study was to compare plasma levels of these receptors in unmedicated bipolar depressed patients compared with healthy controls, and to evaluate the effects of a 6-week lithium treatment on sTNFR1 and sTNFR2 levels.

METHODS

The study enrolled 29 patients with unmedicated bipolar disorder in a major depressive episode and 27 matched controls. Patients had blood collected at baseline and after 6 weeks of lithium treatment. The concentration of sTNFRs was measured by ELISA.

RESULTS

sTNFR1 and sTNFR2 levels were significantly increased in bipolar depression in comparison with healthy subjects. Lithium treatment did not significantly change sTNFR1 and sTNFR2 levels from baseline to endpoint. There was no correlation between improvement in depressive symptoms and the change in sTNFR1 or sTNFR1 levels.

CONCLUSION

These results reinforce the involvement of an activated immune response system in the pathophysiology of bipolar disorder, with no impact of lithium treatment on the related biomarkers.

Lithium increases leukocyte mitochondrial complex I activity in bipolar disorder during depressive episodes

RATIONALE

Different lines of evidence suggest that mitochondrial dysfunction may be implicated in bipolar disorder (BD) pathophysiology. Mitochondrial electron transport chain (ETC) is a key target to evaluate mitochondrial function, but its activity has never been assessed in unmedicated BD or during mood episodes. Also, lithium has been shown to increase ETC gene expression/activity in preclinical models and in postmortem brains of BD subjects, but to date, no study has evaluated lithium's direct effects on ETC activity in vivo.

OBJECTIVES

This study aims to evaluate leukocyte ETC complexes I-IV activities in acute depressive episode in BD (compared to controls) and the effect of lithium treatment on ETC activity.

METHODS

Subjects with short-term BD during a depressive episode (n=25) were treated for 6 weeks with lithium. Leukocytes were collected at baseline and endpoint and mitochondrial ETC complexes I-IV activities were evaluated and compared to age-matched healthy controls (n=24).

RESULTS

Lithium significantly increased mitochondrial complex I activity from baseline to endpoint (p=0.02), with no changes in other complexes after 6 weeks. Also, plasma lithium levels were significantly correlated to mitochondrial complex I activity after treatment (p=0.003). Mitochondrial complexes I-IV activities did not differ during depressive episodes in BD compared to healthy controls.

CONCLUSIONS

Our findings demonstrate for the first time an increase in mitochondrial ETC complex I activity in vivo after lithium treatment in BD, which was positively associated with plasma lithium levels. Further studies are warranted to clarify the potential role of this target in neuroprotection-related drug development.

Multimodal magnetic resonance imaging study of treatment-naïve adults with attention-deficit/hyperactivity disorder

Background

Attention-Deficit/Hiperactivity Disorder (ADHD) is a prevalent disorder, but its neuroanatomical circuitry is still relatively understudied, especially in the adult population. The few morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) studies available to date have found heterogeneous results. This may be at least partly attributable to some well-known technical limitations of the conventional voxel-based methods usually employed to analyze such neuroimaging data. Moreover, there is a great paucity of imaging studies of adult ADHD to date that have excluded patients with history of use of stimulant medication.

Methods

A newly validated method named optimally-discriminative voxel-based analysis (ODVBA) was applied to multimodal (structural and DTI) MRI data acquired from 22 treatment-naïve ADHD adults and 19 age- and gender-matched healthy controls (HC).

Results

Regarding DTI data, we found higher fractional anisotropy in ADHD relative to HC encompassing the white matter (WM) of the bilateral superior frontal gyrus, right middle frontal left gyrus, left postcentral gyrus, bilateral cingulate gyrus, bilateral middle temporal gyrus and right superior temporal gyrus; reductions in trace (a measure of diffusivity) in ADHD relative to HC were also found in fronto-striatal-parieto-occipital circuits, including the right superior frontal gyrus and bilateral middle frontal gyrus, right precentral gyrus, left middle occipital gyrus and bilateral cingulate gyrus, as well as the left body and right splenium of the corpus callosum, right superior corona radiata, and right superior longitudinal and fronto-occipital fasciculi. Volumetric abnormalities in ADHD subjects were found only at a trend level of significance, including reduced gray matter (GM) in the right angular gyrus, and increased GM in the right supplementary motor area and superior frontal gyrus.

Conclusions

Our results suggest that adult ADHD is associated with neuroanatomical abnormalities mainly affecting the WM microstructure in fronto-parieto-temporal circuits that have been implicated in cognitive, emotional and visuomotor processes.

Lithium efficacy in bipolar depression with flexible dosing: A six-week, open-label, proof-of-concept study

Lithium has a narrow therapeutic index with a subtle balance between effectiveness and adverse effects. Current guidelines recommend the use of lithium as a treatment for acute bipolar depression; however, the therapeutic range for the treatment has not been fully defined. Recently, the adjunctive lower lithium dose in bipolar depression has revealed potential efficacy; however, no study has investigated it predominantly in monotherapy. In this open-label, proof-of-concept study, 31 individuals with bipolar disorder during a depressive episode were randomized and 29 were followed up for six weeks with flexible lithium dosing. All subjects had a 21-item Hamilton Rating Scale for Depression (HAM-D) score of ≥18 at baseline. Subjects were divided into two groups, with higher (Li ≥0.5 mEq/l) or lower (Li <0.5 mEq/l) blood lithium levels. Response and remission rates were evaluated using the HAM-D scores. Following 6 weeks of lithium treatment, the remission rate for all patients was 62.0%. The plasma lithium levels did not impact the clinical response. However, subjects with higher blood lithium levels had an increased prevalence of nausea, restlessness, headaches and cognitive complaints. The results indicate that the lithium dose for the treatment of bipolar depression in an individual should be based on the clinical efficacy and side-effects. In the context of personalized psychiatric treatments, it is necessary to evaluate the therapeutic action of lithium with individual regimens in order to develop more tolerable and effective treatment approaches.

Leukocyte telomerase activity and antidepressant efficacy in bipolar disorder

Telomeres are DNA-protein complexes that cap linear DNA strands, protecting DNA from damage. Recently, shorten telomeres length has been reported in bipolar disorder (BD) and depression. The enzyme telomerase regulates telomeres׳ length, which has been associated with cellular viability; however it is not clear how telomerase may be involved in the pathophysiology and therapeutics of BD. In the present study, leukocyte telomerase activity was assessed in 28 medication-free BD depressed individuals (DSM-IV-TR criteria) at baseline and after 6 weeks of lithium therapy (n=21) also matching with 23 healthy controls. There was no difference between telomerase activity in subjects with BD depression (before or after lithium) and controls. Improvement of depressive symptoms was negatively associated with telomerase activity after 6 weeks of lithium therapy. This is the first study describing telomerase activity in BD research. Overall, telomerase activity seems not directly involved in the pathophysiology of short-term BD. Lithium׳s antidepressant effects may involve regulation at telomerase activity. Further studies with larger samples and long-term illness are also warranted.

Oxidative stress in early stage Bipolar Disorder and the association with response to lithium

BACKGROUND

Several studies have described increased oxidative stress (OxS) parameters and imbalance of antioxidant enzymes in Bipolar Disorder (BD) but few is know about the impact of treatment at these targets. However, no study has evaluated OxS parameters in unmedicated early stage BD and their association with lithium treatment in bipolar depression.

METHODS

Patients with BD I or II (n = 29) in a depressive episode were treated for 6 weeks with lithium. Plasma samples were collected at baseline and endpoint, and were also compared to age-matched controls (n = 28). The thiobarbituric acid reactive substances (TBARS), and the antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities were measured.

RESULTS

Subjects with BD depression at baseline presented a significant increase in CAT (p = 0.005) and GPx (p < 0.001) levels, with lower SOD/CAT ratio (p = 0.001) and no changes on SOD or TBARS compared to healthy controls. Regarding therapeutics, lithium only induced a decrease in TBARS (p = 0.023) and SOD (p = 0.029) levels, especially in BDII. Finally, TBARS levels were significantly lower at endpoint in lithium responders compared to non-responders (p = 0.018) with no difference in any biomarker regarding remission.

CONCLUSION

The present findings suggest a reactive increase in antioxidant enzymes levels during depressive episodes in early stage BD with minimal prior treatment. Also, decreased lipid peroxidation (TBARS) levels were observed, associated with lithium's clinical efficacy. Overall, these results reinforce the role for altered oxidative stress in the pathophysiology of BD and the presence of antioxidant effects of lithium in the prevention of illness progression and clinical efficacy.

Leukocyte mitochondrial DNA copy number in bipolar disorder

BACKGROUND

Evidence supports the role for mitochondrial impairment in the pathophysiology of bipolar disorder (BD). BD has been associated with decreased mitochondrial electron transport chain activity and increased oxidative stress. Also, mitochondrial DNA (mtDNA) encodes mitochondrial electron transport chain proteins and has been associated with altered oxidative stress. Preclinical studies showed that lithium treatment increased mtDNA content, but no study has directly assessed mtDNA content in subjects with BD in vivo. Also, the effects of lithium treatment on mtDNA content have never been evaluated in humans.

METHODS

Leukocyte mtDNA content using real time-PCR was evaluated in subjects with BD (n=23) in a depressive episode (≥18 in the 21-item Hamilton Depression Rating Scale) before and after 6-week lithium treatment versus healthy controls (n=24).

RESULTS

mtDNA content showed no significant difference between subjects with BD at baseline and controls (p=0.46); also no difference was observed when comparing before and after lithium treatment. A trend for decreased mtDNA content was specifically observed in BD type I compared to controls and BD type II (p=0.05). Importantly, endpoint mtDNA copy number was significantly correlated with age.

CONCLUSION

In BD subjects who were younger, unmedicated and had a shorter duration of illness, no change was observed in mtDNA copy number. More studies with larger samples are warranted to evaluate mtDNA content changes in BD and its potential role as a treatment target, especially in BD type I and its association with aging.