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Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.
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Envelhecimento , Encéfalo , Imageamento por Ressonância Magnética , Humanos , Adolescente , Feminino , Idoso , Adulto , Criança , Adulto Jovem , Masculino , Encéfalo/diagnóstico por imagem , Encéfalo/anatomia & histologia , Encéfalo/crescimento & desenvolvimento , Idoso de 80 Anos ou mais , Pré-Escolar , Pessoa de Meia-Idade , Envelhecimento/fisiologia , Imageamento por Ressonância Magnética/métodos , Neuroimagem/métodos , Neuroimagem/normas , Tamanho da AmostraRESUMO
Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
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Transtorno Bipolar , Imageamento por Ressonância Magnética , Obesidade , Análise de Componente Principal , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/tratamento farmacológico , Transtorno Bipolar/patologia , Adulto , Feminino , Masculino , Imageamento por Ressonância Magnética/métodos , Pessoa de Meia-Idade , Obesidade/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/patologia , Esquizofrenia/tratamento farmacológico , Esquizofrenia/fisiopatologia , Córtex Cerebral/diagnóstico por imagem , Córtex Cerebral/patologia , Análise por Conglomerados , Adulto Jovem , Encéfalo/diagnóstico por imagem , Encéfalo/patologiaRESUMO
Exposure to early life adversity is associated with both increased risk of developing schizophrenia and poorer performance on measures of social cognitive functioning. In this study, we examined whether interleukin-6 (IL-6) and Corpus Callosum (CC) microstructure mediated the association between childhood physical neglect and social cognition. Fifty-eight patients with a diagnosis of schizophrenia were included. The CANTAB emotion recognition task (unbiased hit rate) was used to assess social cognition. We found that the microstructural organization of the CC significantly mediated the association between physical neglect and emotion recognition. Furthermore, in a sequential mediation analysis that also considered the role of inflammatory response, the association between physical neglect, and lower emotion recognition performance was sequentially mediated by higher IL-6 and lower fractional anisotropy of the CC. This mediating effect of IL-6 was only present when simultaneously considering the effects of CC microstructural organization and remained significant while controlling for the effects of sex, BMI and medication dosage (but not age). Overall, the findings suggest that the association between physical neglect and poorer emotion recognition in schizophrenia occurs, at least in part, via its association with white matter microstructure.
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Esquizofrenia , Substância Branca , Humanos , Criança , Corpo Caloso/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Cognição Social , Interleucina-6 , Cognição/fisiologia , AnisotropiaRESUMO
Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN)-a recently developed analytic approach for tractography-to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls.Clinical Relevance- BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.
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Transtorno Bipolar , Substância Branca , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/complicações , Transtorno Bipolar/genética , Projetos Piloto , Imagem de Tensor de Difusão , Encéfalo/diagnóstico por imagem , Substância Branca/diagnóstico por imagemRESUMO
We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).
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Brain disorders comprise several psychiatric and neurological disorders which can be characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and neurodegeneration. Clinical diagnoses primarily rely on a combination of life history information and questionnaires, with a distinct lack of discriminative biomarkers in use for psychiatric disorders. Symptoms across brain conditions are associated with functional alterations of cognitive and emotional processes, which can correlate with anatomical variation; structural magnetic resonance imaging (MRI) data of the brain are therefore an important focus of research, particularly for predictive modelling. With the advent of large MRI data consortia (such as the Alzheimer's Disease Neuroimaging Initiative) facilitating a greater number of MRI-based classification studies, convolutional neural networks (CNNs)-deep learning models well suited to image processing tasks-have become increasingly popular for research into brain conditions. This has resulted in a myriad of studies reporting impressive predictive performances, demonstrating the potential clinical value of deep learning systems. However, methodologies can vary widely across studies, making them difficult to compare and/or reproduce, potentially limiting their clinical application. Here, we conduct a qualitative systematic literature review of 55 studies carrying out CNN-based predictive modelling of brain disorders using MRI data and evaluate them based on three principles-modelling practices, transparency, and interpretability. We propose several recommendations to enhance the potential for the integration of CNNs into clinical care.
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Doença de Alzheimer , Imageamento por Ressonância Magnética , Humanos , Imageamento por Ressonância Magnética/métodos , Redes Neurais de Computação , Neuroimagem/métodos , Encéfalo/diagnóstico por imagem , Espectroscopia de Ressonância MagnéticaRESUMO
OBJECTIVE: The Corona Radiata (CR) is a large white matter tract in the brain comprising of the anterior CR (aCR), superior CR (sCR), and posterior CR (pCR), which have associations with cognition, self-regulation, and, in schizophrenia, positive symptom severity. This study tested the hypothesis that the microstructural organisation of the aCR, as measured by Fractional Anisotropy (FA) using Diffusion Tensor Imaging (DTI), would relate to poorer social cognitive outcomes and higher positive symptom severity for people with schizophrenia, when compared to healthy participants. We further hypothesised that increased positive symptoms would relate to poorer social cognitive outcomes. METHODS: Data were derived from n = 178 healthy participants (41 % females; 36.11 ± 12.36 years) and 58 people with schizophrenia (30 % females; 42.4 ± 11.1 years). The Positive and Negative Symptom Severity Scale measured clinical symptom severity. Social Cognition was measured using the Reading the Mind in the Eyes Test (RMET) Total Score, as well as the Positive, Neutral, and Negative stimuli valence. The ENIGMA-DTI protocol tract-based spatial statistics (TBSS) was used. RESULTS: There was a significant difference in FA for the CR, in individuals with schizophrenia compared to healthy participants. On stratification, both the aCR and pCR were significantly different between groups, with patients showing reduced white matter tract microstructural organisation. Significant negative correlations were observed between positive symptomatology and reduced microstructural organisation of the aCR. Performance for RMET negative valence items was significantly correlated bilaterally with the aCR, but not the sCR or pCR, and no relationship to positive symptoms was observed. CONCLUSIONS: These data highlight specific and significant microstructural white-matter differences for people with schizophrenia, which relates to positive clinical symptomology and poorer performance on social cognition stimuli. While reduced FA is associated with higher positive symptomatology in schizophrenia, this study shows the specific associated with anterior frontal white matter tracts and reduced social cognitive performance. The aCR may have a specific role to play in frontal-disconnection syndromes, psychosis, and social cognitive profile within schizophrenia, though further research requires more sensitive, specific, and detailed consideration of social cognition outcomes.
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Esquizofrenia , Substância Branca , Feminino , Humanos , Masculino , Substância Branca/diagnóstico por imagem , Imagem de Tensor de Difusão/métodos , Esquizofrenia/complicações , Esquizofrenia/diagnóstico por imagem , Cognição Social , Encéfalo , AnisotropiaRESUMO
Investigating alterations in brain circuitry associated with bipolar disorder (BD) may offer a valuable approach to discover brain biomarkers for genetic and interventional studies of the disorder and related mental illnesses. Some diffusion MRI studies report evidence of microstructural abnormalities in white matter regions of interest, but we lack a fine-scale spatial mapping of brain microstructural differences along tracts in BD. We also lack large-scale studies that integrate tractometry data from multiple sites, as larger datasets can greatly enhance power to detect subtle effects and assess whether effects replicate across larger international datasets. In this multisite diffusion MRI study, we used BUndle ANalytics (BUAN, Chandio 2020), a recently developed analytic approach for tractography, to extract, map, and visualize profiles of microstructural abnormalities on 3D models of fiber tracts in 148 participants with BD and 259 healthy controls from 6 independent scan sites. Modeling site differences as random effects, we investigated along-tract white matter (WM) microstructural differences between diagnostic groups. QQ plots showed that group differences were gradually enhanced as more sites were added. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic, interhemispheric, and posterior pathways; higher FA was also noted in posterior bundles, relative to controls. By integrating tractography and anatomical information, BUAN effectively captures unique effects along white matter (WM) tracts, providing valuable insights into anatomical variations that may assist in the classification of diseases.
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Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN), a recently developed analytic approach for tractography, to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean Fractional Anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls. BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.
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BACKGROUND: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
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It has been reported that childhood trauma (CT) is associated with reductions in fractional anisotropy (FA) in individuals with schizophrenia (SZ). Here, we hypothesized that SZ with high levels of CT will show the greatest reductions in FA in frontolimbic and frontoparietal regions compared to healthy controls (HC) with high trauma levels and participants with no/low levels of CT. Thirty-seven SZ and 129 HC with CT experience were dichotomized into groups of 'none/low' or 'high' levels. Participants underwent diffusion-weighted MRI, and Tract-based spatial statistics were employed to assess the main effect of diagnosis, main effect of CT severity irrespective of diagnosis, and interaction between diagnosis and CT severity. SZ showed FA reductions in the corpus callosum and corona radiata compared to HC. Irrespective of a diagnosis, high CT levels (n = 48) were related to FA reductions in frontolimbic and frontoparietal regions compared to those with none/low levels of CT (n = 118). However, no significant interaction between diagnosis and high levels of CT was found (n = 13). Across all participants, we observed effects of CT on late developing frontolimbic and frontoparietal regions, suggesting that the effects of CT severity on white matter organization may be independent of schizophrenia.
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Experiências Adversas da Infância , Esquizofrenia , Substância Branca , Humanos , Esquizofrenia/complicações , Imagem de Tensor de Difusão , Imagem de Difusão por Ressonância MagnéticaRESUMO
BACKGROUND: Analyzing cortical folding may provide insight into the biological underpinnings of neurodevelopmental diseases. A neurodevelopmental subtype of bipolar disorders (BD-ND) has been characterized by the combination of early age of onset and psychotic features. We investigate potential cortical morphology differences associated with this subtype. We analyze, for the first time in bipolar disorders, the sulcal pits, the deepest points in each fold of the cerebral cortex. METHODS: We extracted the sulcal pits from anatomical MRI among 512 participants gathered from 7 scanning sites. We compared the number of sulcal pits in each hemisphere as well as their regional occurrence and depth between the BD-ND subgroup (N = 184), a subgroup without neurodevelopmental features (BD, N = 77) and a group of healthy controls (HC, N = 251). RESULTS: In whole brain analysis, BD-ND group have a higher number of sulcal pits in comparison to the BD group. The local analysis revealed, after correction for multiple testing, a higher occurrence of sulcal pits in the left premotor cortex among the BD-ND subgroup compared to the BD and the HC groups. CONCLUSION: Our findings confirm that BD-ND is associated with a specific brain morphology revealed by the analysis of sulcal pits. These markers may help to better understand neurodevelopment in mood disorder and stratify patients according to a pathophysiological hypothesis.
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Transtorno Bipolar , Córtex Motor , Transtornos do Neurodesenvolvimento , Humanos , Transtorno Bipolar/diagnóstico por imagem , Córtex Cerebral/diagnóstico por imagem , Encéfalo , Imageamento por Ressonância MagnéticaRESUMO
INTRODUCTION: Alcohol use in bipolar disorder (BD) is associated with mood lability and negative illness trajectory, while also impacting functional networks related to emotion, cognition, and introspection. The adverse impact of alcohol use in BD may be explained by its additive effects on these networks, thereby contributing to a poorer clinical outcome. METHODS: Forty BD-I (DSM-IV-TR) and 46 psychiatrically healthy controls underwent T1 and resting state functional MRI scanning and the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) to assess alcohol use. Functional images were decomposed using spatial independent component analysis into 14 resting state networks (RSN), which were examined for effect of alcohol use and diagnosis-by-alcohol use accounting for age, sex, and diagnosis. RESULTS: Despite the groups consuming similar amounts of alcohol (BD: mean score ± SD 3.63 ± 3; HC 4.72 ± 3, U = 713, p = .07), for BD participants, greater alcohol use was associated with increased connectivity of the paracingulate gyrus within a default mode network (DMN) and reduced connectivity within an executive control network (ECN) relative to controls. Independently, greater alcohol use was associated with increased connectivity within an ECN and reduced connectivity within a DMN. A diagnosis of BD was associated with increased connectivity of a DMN and reduced connectivity of an ECN. CONCLUSION: Affective symptomatology in BD is suggested to arise from the aberrant functionality of networks subserving emotive, cognitive, and introspective processes. Taken together, our results suggest that during euthymic periods, alcohol can contribute to the weakening of emotional regulation and response, potentially explaining the increased lability of mood and vulnerability to relapse within the disorder.
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Alcoolismo , Transtorno Bipolar , Humanos , Alcoolismo/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Emoções , Cognição , Encéfalo , Mapeamento EncefálicoRESUMO
Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
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Estudo de Associação Genômica Ampla , Longevidade , Envelhecimento/genética , Encéfalo , Humanos , Longevidade/genética , Imageamento por Ressonância MagnéticaRESUMO
BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.
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Transtorno do Deficit de Atenção com Hiperatividade , Transtorno do Espectro Autista , Transtorno Bipolar , Transtorno Depressivo Maior , Nascimento Prematuro , Transtorno do Espectro Autista/genética , Transtorno do Espectro Autista/patologia , Córtex Cerebral , Criança , Transtorno Depressivo Maior/patologia , Feminino , Humanos , Recém-Nascido , Imageamento por Ressonância Magnética/métodos , Gravidez , Nascimento Prematuro/patologiaRESUMO
BACKGROUND: Current treatment options for the management of depressive episodes in bipolar disorder are often sub-optimal, with some treatments either noted to be only partially effective or to require long durations of treatment prior to a therapeutic response. Therefore, pharmaco-therapeutic options that reduce depressive symptoms in a more rapid manner might provide a viable therapeutic option for some people. Intravenous (IV) scopolamine, a pan muscarinic antagonist, has been demonstrated in a number of studies to confer a rapid antidepressant effect, albeit no study to date has exclusively evaluated its potential therapeutic effect in a cohort consisting solely of individuals with bipolar disorder. METHODS: Individuals with bipolar disorder who are currently experiencing a depressive episode of at least moderate severity will be included in this study. Eligible participants will undergo a screening and placebo-run in visit and will be randomised at visit 3 to the treatment or placebo group. Participants will receive the three blinded infusions over the course of 2 weeks, with two subsequent follow-up visits, 1 and 3 weeks after the last infusion visit. The total duration of the study will be approximately 6 weeks. Patients will continue their regular treatment regime in addition to study medication. Objective and subjective mood questionnaires, cognitive assessments and other psychometric instruments will be administered and recorded. DISCUSSION: To our knowledge, this is the first study to investigate the antidepressant effects of IV scopolamine in an exclusively bipolar disorder cohort. Trial findings will contribute to the evidence base regarding the cholinergic hypothesis of mood disorders and specifically might result in an additional safe therapeutic option for the management of depressive episodes in bipolar disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT04211961 . December 26, 2019. EudraCT Number 2017-003112-39.
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Transtorno Bipolar , Antidepressivos/efeitos adversos , Transtorno Bipolar/diagnóstico , Transtorno Bipolar/tratamento farmacológico , Transtorno Bipolar/psicologia , Método Duplo-Cego , Humanos , Transtornos do Humor/tratamento farmacológico , Ensaios Clínicos Controlados Aleatórios como Assunto , Escopolamina/efeitos adversos , Resultado do TratamentoRESUMO
Introduction: Structural alterations in cortical thickness and the microstructural organization of white matter are independently associated with non-dependent alcohol consumption and bipolar disorder (BD). Identifying their interactive and network-level effects on brain topology may identify the impact of alcohol on reward and emotion circuitry, and its contribution to relapse in BD. Materials and Methods: Thirty-four BD-I (DSM-IV-TR) and 38 healthy controls (HC) underwent T1 and diffusion-weighted magnetic resonance imaging scanning, and the Alcohol Use Disorders Identification Test-Consumption to assess alcohol use. Connectomes comprising 34 cortical and 9 subcortical nodes bilaterally (Freesurfer v5.3) connected by fractional anisotropy-weighted edges derived from non-tensor based deterministic constrained spherical deconvolution tractography (ExploreDTI v4.8.6) underwent permutation-based topological analysis (NBS v1.2) and were examined for the effects of alcohol use and diagnosis-by-alcohol use accounting for age, sex, and diagnosis. Results: Alcohol was significantly related to a subnetwork, encompassing connections between fronto-limbic, basal ganglia, and temporal nodes (Frange = 5-8.4, p = 0.031) and it was not detected to have an effect on global brain integration or segregation. A portion of this network (18%), involving cortico-limbic and basal ganglia connections, was differentially impacted by alcohol in the BD relative to the control group (Frange = 5-8.8, p = 0.033), despite the groups' consuming similar amounts of alcohol (BD: mean ± standard deviation 4.95 ± 3.0; HC 3.62 ± 3.0, T = 1.88, p = 0.06). Discussion: Non-dependent alcohol use impacts brain architectural organization and connectivity within salience, reward, and affective circuitry. The relationship between alcohol use and topology of the network in BD suggests an interactive effect between specific biological vulnerability and alcohol use, which may explain the susceptibility to an increased risk of relapse in the disorder. Impact statement The association between non-dependent alcohol use and neural architecture in bipolar disorder (BD) is unknown, despite the poor clinical trajectory and increased likelihood of relapse associated with alcohol use in BD. We demonstrate that together alcohol and a diagnosis of BD is associated with a subnetwork involving nodes of the cortico-limbic and reward networks. This subnetwork, demonstrated in BD and absent in controls, differentially involves nodes that are specific to reward and emotion processes. This suggests a diagnosis-specific biological vulnerability for alcohol use and may be consistent with known mood lability and thus relapse associated with alcohol use in BD.
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Alcoolismo , Transtorno Bipolar , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/psicologia , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Alcoolismo/diagnóstico por imagem , Alcoolismo/patologia , Consumo de Bebidas Alcoólicas , Recidiva , Imageamento por Ressonância Magnética/métodosRESUMO
The muscarinic-cholinergic system is involved in the pathophysiology of bipolar disorder (BD), and contributes to attention and the top-down and bottom-up cognitive and affective mechanisms of emotional processing, functionally altered in BD. Emotion processing can be assessed by the ability to inhibit a response when the content of the image is emotional. Impaired regulatory capacity of cholinergic neurotransmission conferred by reduced M2-autoreceptor availability is hypothesized to play a role in elevated salience of negative emotional distractors in euthymic BD relative to individuals with no history of mood instability. Thirty-three euthymic BD type-I (DSM-V-TR) and 50 psychiatrically-healthy controls underwent functional magnetic resonance imaging (fMRI) and an emotion-inhibition paradigm before and after intravenous cholinergic challenge using the acetylcholinesterase inhibitor, physostigmine (1 mg), or placebo. Mood, accuracy, and reaction time on either recognizing or inhibiting a response associated with an image involving emotion and regional functional activation were examined for effects of cholinergic challenge physostigmine relative to placebo, prioritizing any interaction with the diagnostic group. Analyses revealed that (1) at baseline, impaired behavioral performance was associated with lower activation in the anterior cingulate cortex in BD relative to controls during emotion processing; (2) physostigmine (vs. placebo) affected behavioral performance during the inhibition of negative emotions, without altering mood, and increased activation in the posterior cingulate cortex in BD (vs. controls); (3) In BD, lower accuracy observed during emotion inhibition of negative emotions was remediated by physostigmine and was associated with cingulate cortex overactivation. Our findings implicate abnormal regulation of cholinergic neurotransmission in the cingulate cortices in BD, which may mediate exaggerated emotional salience processing, a core feature of BD.
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Transtorno Bipolar , Giro do Cíngulo , Acetilcolinesterase/farmacologia , Transtorno Bipolar/complicações , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/tratamento farmacológico , Estudos de Casos e Controles , Colinérgicos/farmacologia , Emoções/fisiologia , Humanos , Imageamento por Ressonância Magnética/métodos , Fisostigmina/farmacologia , Transmissão SinápticaRESUMO
AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.