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1.
Psychol Med ; : 1-12, 2021 Jan 14.
Artigo em Inglês | MEDLINE | ID: mdl-33441206

RESUMO

BACKGROUND: There is still little knowledge of objective suicide risk stratification. METHODS: This study aims to develop models using machine-learning approaches to predict suicide attempt (1) among survey participants in a nationally representative sample and (2) among participants with lifetime major depressive episodes. We used a cohort called the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) that was conducted in two waves and included a nationally representative sample of the adult population in the United States. Wave 1 involved 43 093 respondents and wave 2 involved 34 653 completed face-to-face reinterviews with wave 1 participants. Predictor variables included clinical, stressful life events, and sociodemographic variables from wave 1; outcome included suicide attempt between wave 1 and wave 2. RESULTS: The model built with elastic net regularization distinguished individuals who had attempted suicide from those who had not with an area under the ROC curve (AUC) of 0.89, balanced accuracy 81.86%, specificity 89.22%, and sensitivity 74.51% for the general population. For participants with lifetime major depressive episodes, AUC was 0.89, balanced accuracy 81.64%, specificity 85.86%, and sensitivity 77.42%. The most important predictor variables were a diagnosis of borderline personality disorder, post-traumatic stress disorder, and being of Asian descent for the model in all participants; and previous suicide attempt, borderline personality disorder, and overnight stay in hospital because of depressive symptoms for the model in participants with lifetime major depressive episodes. Random forest and artificial neural networks had similar performance. CONCLUSIONS: Risk for suicide attempt can be estimated with high accuracy.

2.
Transl Psychiatry ; 10(1): 425, 2020 Dec 08.
Artigo em Inglês | MEDLINE | ID: mdl-33293520

RESUMO

It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.

3.
Mol Psychiatry ; 2020 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-33173193

RESUMO

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

4.
Hum Brain Mapp ; 2020 Jun 29.
Artigo em Inglês | MEDLINE | ID: mdl-32596977

RESUMO

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

5.
J Affect Disord ; 273: 592-596, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32560958

RESUMO

BACKGROUND: Neuropsychiatric disorders have been linked to immune mechanisms. Altered peripheral levels of eotaxin-1/CCL11; a cytokine implicated in allergic reactions and aging process; have been reported in bipolar disorder (BD). Several brain areas, especially the temporal lobe, seem to display volume loss and accelerated aging in BD. This study aimed at exploring potential associations between eotaxins and brain volumes in patients with BD compared to controls. METHODS: Twenty-two euthymic patients with BD and 22 controls were enrolled in this study. Serum levels of eotaxin-1/CCL11, eotaxin-2/CCL24 and eotaxin-3/CCL26 were determined alongside brain volumes. RESULTS: There were no differences in the levels of eotaxins between patients and controls. A negative correlation was found between eotaxin-1/CCL11 levels and left-hemisphere's superior-temporal volume only in BD patients, which persisted with covariate adjusted model. CONCLUSION: This study corroborates the emerging evidence of association between inflammation and brain volumes in BD. Our preliminary results also support the hypothesis of a possible role of eotaxin-1/CCL11 in accelerated brain aging in BD.

6.
Mol Psychiatry ; 2020 May 28.
Artigo em Inglês | MEDLINE | ID: mdl-32467648

RESUMO

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

8.
Mol Psychiatry ; 25(9): 2130-2143, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-30171211

RESUMO

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

9.
Bipolar Disord ; 21(7): 582-594, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31465619

RESUMO

OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD. METHOD: A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD. RESULTS: The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding. CONCLUSION: Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings.


Assuntos
Big Data , Transtorno Bipolar/terapia , Tomada de Decisão Clínica , Aprendizado de Máquina , Ideação Suicida , Comitês Consultivos , Transtorno Bipolar/epidemiologia , Ciência de Dados , Humanos , Fenótipo , Prognóstico , Medição de Risco
10.
Am J Geriatr Psychiatry ; 27(12): 1414-1418, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31320246

RESUMO

OBJECTIVES: The authors aim to investigate the association between white matter integrity and accelerated brain aging in late-life depression. METHODS: The authors measured senescence-associated secretory phenotype (SASP) index proteins, cognitive performance, and MRI diffusion tensor imaging (DTI) measures of fractional anisotropy and mean diffusivity-based indices of white matter microstructure measures in 56 older adults with remitted late-life depression. RESULTS: Higher SASP index was significantly correlated with older age (r = 0.42, p = 0.001) and worse executive function performance (r = -0.27, p = 0.04). After controlling for the effect of age, overall cognitive performance, and white matter hyperintensities, the association between SASP and left and right cingulate bundle mean diffusivity remained statistically significant. CONCLUSIONS: Our data suggest that, in the context of late-life depression, SASP proteins are associated with microstructural abnormalities in white matter tracts in brain and worse executive function performance.


Assuntos
Senescência Celular , Cognição , Transtorno Depressivo Maior/diagnóstico por imagem , Função Executiva , Giro do Cíngulo/diagnóstico por imagem , Substância Branca/diagnóstico por imagem , Fatores Etários , Idoso , Transtorno Depressivo Maior/metabolismo , Transtorno Depressivo Maior/psicologia , Imagem de Difusão por Ressonância Magnética , Feminino , Humanos , Masculino
11.
IEEE/ACM Trans Comput Biol Bioinform ; 16(5): 1508-1514, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31135366

RESUMO

Genome-wide association studies (GWAS) link full genome data to a handful of traits. However, in neuroimaging studies, there is an almost unlimited number of traits that can be extracted for full image-wide big data analyses. Large populations are needed to achieve the necessary power to detect statistically significant effects, emphasizing the need to pool data across multiple studies. Neuroimaging consortia, e.g., ENIGMA and CHARGE, are now analyzing MRI data from over 30,000 individuals. Distributed processing protocols extract harmonized features at each site, and pool together only the cohort statistics using meta analysis to avoid data sharing. To date, such MRI projects have focused on single measures such as hippocampal volume, yet voxelwise analyses (e.g., tensor-based morphometry; TBM) may help better localize statistical effects. This can lead to $10^{13}$1013 tests for GWAS and become underpowered. We developed an analytical framework for multi-site TBM by performing multi-channel registration to cohort-specific templates. Our results highlight the reliability of the method and the added power over alternative options while preserving single site specificity and opening the doors for well-powered image-wide genome-wide discoveries.


Assuntos
Biologia Computacional/métodos , Estudo de Associação Genômica Ampla/métodos , Neuroimagem/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/genética , Encéfalo/diagnóstico por imagem , Bases de Dados Factuais , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Metanálise como Assunto , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único/genética , Adulto Jovem
12.
Braz. J. Psychiatry (São Paulo, 1999, Impr.) ; 41(3): 254-256, May-June 2019. tab
Artigo em Inglês | LILACS | ID: biblio-1039095

RESUMO

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


Assuntos
Humanos , Masculino , Feminino , Adulto , Adulto Jovem , Transtorno Bipolar/patologia , Giro do Cíngulo/patologia , Hipocampo/patologia , Transtorno Bipolar/genética , Imagem por Ressonância Magnética , Família , Estudos de Casos e Controles , Endofenótipos , Pessoa de Meia-Idade
13.
Cogn Neuropsychiatry ; 24(2): 93-107, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30774035

RESUMO

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


Assuntos
Transtorno Bipolar/diagnóstico , Transtorno Bipolar/psicologia , Transtornos Cognitivos/diagnóstico , Transtornos Cognitivos/psicologia , Testes Neuropsicológicos , Adolescente , Criança , Cognição/fisiologia , Feminino , Humanos , Estudos Longitudinais , Masculino , Memória/fisiologia , Pais/psicologia
14.
J Neuroimaging ; 29(3): 323-330, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30784130

RESUMO

BACKGROUND AND PURPOSE: Assessment of the effects of microgravity on astronauts' brains using microstructural measures by utilizing quantitative MRI, before and after spaceflight would help understand the structural changes. METHODS: Quantitative MRI data sets in 19 astronauts were acquired before and after space missions. Both diffusion tensor metrics and volumetric measures were analyzed in the brain regions involved in the visual function. RESULTS: The fractional anisotropy was reduced in the right posterior thalamic radiations (P = .0009) and remained significant after a false discovery rate (FDR) correction (P = .03). A trend of increase in the mean diffusivities of different subregions of the occipital cortex on the right side, including calcarine, middle occipital, inferior occipital, and fusiform gyri, was noted and became insignificant after FDR correction. Similarly, there was a trend of cortical thinning involving the right occipital lobe and bilateral fusiform gyri, volume reduction of the left thalamus, and increase in lateral ventricular volume in the postflight scans. CONCLUSION: Gray and white matter alterations are detected by quantitative MRI before and after space flight. Our findings may be used to understand the neuroanatomical mechanisms of possible brain dysfunction or neuroplasticity in microgravity condition in the future studies.


Assuntos
Astronautas , Encéfalo/diagnóstico por imagem , Voo Espacial , Ausência de Peso , Substância Branca/diagnóstico por imagem , Adulto , Imagem de Difusão por Ressonância Magnética , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Tamanho do Órgão
15.
PLoS One ; 14(1): e0199729, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30625144

RESUMO

Chronic cocaine and alcohol use impart significant stress on biological and cognitive systems, resulting in changes consistent with an allostatic load model of neurocognitive impairment. The present study measured potential markers of allostatic load in individuals with comorbid cocaine/alcohol use disorders (CUD/AUD) and control subjects. Measures of brain white matter (WM), telomere length, and impulsivity/attentional bias were obtained. WM (CUD/AUD only) was indexed by diffusion tensor imaging metrics, including radial diffusivity (RD) and fractional anisotropy (FA). Telomere length was indexed by the telomere to single copy gene (T/S) ratio. Impulsivity and attentional bias to drug cues were measured via eye-tracking, and were also modeled using the Hierarchical Diffusion Drift Model (HDDM). Average whole-brain RD and FA were associated with years of cocaine use (R2 = 0.56 and 0.51, both p < .005) but not years of alcohol use. CUD/AUD subjects showed more anti-saccade errors (p < .01), greater attentional bias scores (p < .001), and higher HDDM drift rates on cocaine-cue trials (Bayesian probability CUD/AUD > control = p > 0.99). Telomere length was shorter in CUD/AUD, but the difference was not statistically significant. Within the CUD/AUD group, exploratory regression using an elastic-net model determined that more years of cocaine use, older age, larger HDDM drift rate differences and shorter telomere length were all predictive of WM as measured by RD (model R2 = 0.79). Collectively, the results provide modest support linking CUD/AUD to putative markers of allostatic load.


Assuntos
Alcoolismo , Encéfalo , Transtornos Relacionados ao Uso de Cocaína , Imagem de Tensor de Difusão , Homeostase do Telômero , Telômero/metabolismo , Substância Branca , Adulto , Idoso , Alcoolismo/diagnóstico por imagem , Alcoolismo/metabolismo , Encéfalo/diagnóstico por imagem , Encéfalo/metabolismo , Transtornos Relacionados ao Uso de Cocaína/diagnóstico por imagem , Transtornos Relacionados ao Uso de Cocaína/metabolismo , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Telômero/patologia , Substância Branca/diagnóstico por imagem , Substância Branca/metabolismo
16.
Braz J Psychiatry ; 41(3): 254-256, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30540025

RESUMO

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


Assuntos
Transtorno Bipolar/patologia , Giro do Cíngulo/patologia , Hipocampo/patologia , Adulto , Transtorno Bipolar/genética , Estudos de Casos e Controles , Endofenótipos , Família , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Adulto Jovem
17.
Cereb Cortex ; 29(1): 202-214, 2019 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-29202177

RESUMO

No neuroanatomical substrates for distinguishing between depression of bipolar disorder (dBD) and major depressive disorder (dMDD) are currently known. The aim of the current multicenter study was to identify neuroanatomical patterns distinct to depressed patients with the two disorders. Further analysis was conducted on an independent sample to enable generalization of results. We directly compared MR images of these subjects using voxel-based morphometry (VBM) and a support vector machine (SVM) algorithm using 1531 participants. The VBM analysis showed significantly reduced gray matter volumes in the bilateral dorsolateral prefrontal (DLPFC) and anterior cingulate cortices (ACC) in patients with dBD compared with those with dMDD. Patients with the two disorders shared small gray matter volumes for the right ACC and left inferior frontal gyrus when compared with healthy subjects. Voxel signals in these regions during SVM analysis contributed to an accurate classification of the two diagnoses. The VBM and SVM results in the second cohort also supported these results. The current findings provide new evidence that gray matter volumes in the DLPFC and ACC are core regions in displaying shared and distinct neuroanatomical substrates and can shed light on elucidation of neural mechanism for depression within the bipolar/major depressive disorder continuum.


Assuntos
Transtorno Bipolar/diagnóstico por imagem , Transtorno Depressivo Maior/diagnóstico por imagem , Giro do Cíngulo/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Córtex Pré-Frontal/diagnóstico por imagem , Adulto , Transtorno Bipolar/psicologia , Estudos de Coortes , Transtorno Depressivo Maior/psicologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
18.
Front Neurol ; 9: 930, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30459704

RESUMO

Background: Psychotic symptoms have been under-investigated in Huntington's disease (HD) and research is needed in order to elucidate the characteristics linked to the unique phenotype of HD patients presenting with psychosis. Objective: To evaluate the frequency and factors associated with psychosis in HD. Methods: Cross-sectional study including manifest individuals with HD from the Enroll-HD database. Both conventional statistical analysis (Stepwise Binary Logistic Regression) and five machine learning algorithms [Least Absolute Shrinkage and Selection Operator (LASSO); Elastic Net; Support Vector Machines (SVM); Random Forest; and class-weighted SVM] were used to describe factors associated with psychosis in manifest HD patients. Results: Approximately 11% of patients with HD presented history of psychosis. Logistic regression analysis indicated that younger age at HD clinical diagnosis, lower number of CAG repeats, history of [alcohol use disorders, depression, violent/aggressive behavior and perseverative/obsessive behavior], lower total functional capacity score, and longer time to complete trail making test-B were associated with psychosis. All machine learning algorithms were significant (chi-square p < 0.05) and capable of distinguishing individual HD patients with history of psychosis from those without a history of psychosis with prediction accuracy around 71-73%. The most relevant variables were similar to those found in the conventional analyses. Conclusions: Psychiatric and behavioral symptoms as well as poorer cognitive performance were related to psychosis in HD. In addition, psychosis was associated with lower number of CAG repeats and younger age at clinical diagnosis of HD, suggesting that these patients may represent a unique phenotype in the HD spectrum.

19.
Schizophr Bull ; 44(3): 552-559, 2018 04 06.
Artigo em Inglês | MEDLINE | ID: mdl-29897598

RESUMO

Background: Hippocampal abnormalities have been largely reported in patients with schizophrenia and bipolar disorder, and are considered to be involved in the pathophysiology of the psychosis. The hippocampus consists of several subfields but it remains unclear their involvement in the early stages of psychosis. Aim: The aim of this study was to investigate volumetric alterations in hippocampal subfields in patients at the first-episode psychosis (FEP). Methods: Magnetic resonance imaging (MRI) data were collected in 134 subjects (58 FEP patients; 76 healthy controls [HC]). A novel automated hippocampal segmentation algorithm was used to segment the hippocampal subfields, based on an atlas constructed from ultra-high resolution imaging on ex vivo hippocampal tissue. The general linear model was used to investigate volume differences between FEP patients and HC, with age, gender and total intracranial volume as covariates. Results: We found significantly lower volumes of bilateral CA1, CA4, and granule cell layer (GCL), and of left CA3, and left molecular layer (ML) in FEP patients compared to HC. Only the volumes of the left hippocampus and its subfields were significantly lower in FEP than HC at the False Discovery Rate (FDR) of 0.1. No correlation was found between hippocampal subfield volume and duration of illness, age of onset, duration of medication, and Positive and Negative Syndrome Scale (PANSS). Conclusion: We report abnormally low volumes of left hippocampal subfields in patients with FEP, sustaining its role as a putative neural marker of psychosis onset.


Assuntos
Transtorno Bipolar/patologia , Hipocampo/patologia , Processamento de Imagem Assistida por Computador/métodos , Imagem por Ressonância Magnética/métodos , Transtornos Psicóticos/patologia , Esquizofrenia/patologia , Transtorno da Personalidade Esquizotípica/patologia , Adulto , Transtorno Bipolar/diagnóstico por imagem , Região CA1 Hipocampal/diagnóstico por imagem , Região CA1 Hipocampal/patologia , Região CA3 Hipocampal/diagnóstico por imagem , Região CA3 Hipocampal/patologia , Feminino , Hipocampo/diagnóstico por imagem , Humanos , Masculino , Pessoa de Meia-Idade , Transtornos Psicóticos/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Transtorno da Personalidade Esquizotípica/diagnóstico por imagem , Adulto Jovem
20.
Psychiatry Res Neuroimaging ; 278: 65-68, 2018 08 30.
Artigo em Inglês | MEDLINE | ID: mdl-29907438

RESUMO

Sodium valproate (VPA) has well-established neuroprotective effects and is recommended as treatment in bipolar disorder patients. The neural effects of VPA in pediatric bipolar disorder (PBD) have yet to be established. This preliminary study explored the effects of VPA on brain structure in PBD. Fourteen PBD patients (10 males; mean = 13.43 ± 3.05 years old) underwent a structural MRI before and after a 6-week VPA treatment period. Bayesian linear mixed modeling explored seven brain region volumes as a function of dichotomous pre/post time. Results showed a decrease in amygdala volume over time. These findings need to be confirmed by large-scale, longitudinal studies.


Assuntos
Transtorno Bipolar/tratamento farmacológico , Encéfalo/efeitos dos fármacos , Ácido Valproico/administração & dosagem , Adolescente , Tonsila do Cerebelo/diagnóstico por imagem , Tonsila do Cerebelo/efeitos dos fármacos , Tonsila do Cerebelo/patologia , Teorema de Bayes , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/patologia , Encéfalo/diagnóstico por imagem , Encéfalo/crescimento & desenvolvimento , Criança , Feminino , Humanos , Imagem por Ressonância Magnética/métodos , Masculino
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