Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 10 de 10
Filtrar
2.
JMIR Ment Health ; 8(1): e24333, 2021 Jan 12.
Artigo em Inglês | MEDLINE | ID: mdl-33433392

RESUMO

BACKGROUND: Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants' self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowledge about their psychometric properties, especially their validity. OBJECTIVE: The goal of this study is to systematically investigate the validity of smartphone-administered assessments of self-reported affective symptoms using the Remote Monitoring Application in Psychiatry (ReMAP). METHODS: The ReMAP app was distributed to 173 adult participants of ongoing, longitudinal psychiatric phenotyping studies, including healthy control participants, as well as patients with affective disorders and anxiety disorders; the mean age of the sample was 30.14 years (SD 11.92). The Beck Depression Inventory (BDI) and single-item mood and sleep information were assessed via the ReMAP app and validated with non-smartphone-based BDI scores and clinician-rated depression severity using the Hamilton Depression Rating Scale (HDRS). RESULTS: We found overall high comparability between smartphone-based and non-smartphone-based BDI scores (intraclass correlation coefficient=0.921; P<.001). Smartphone-based BDI scores further correlated with non-smartphone-based HDRS ratings of depression severity in a subsample (r=0.783; P<.001; n=51). Higher agreement between smartphone-based and non-smartphone-based assessments was found among affective disorder patients as compared to healthy controls and anxiety disorder patients. Highly comparable agreement between delivery formats was found across age and gender groups. Similarly, smartphone-based single-item self-ratings of mood correlated with BDI sum scores (r=-0.538; P<.001; n=168), while smartphone-based single-item sleep duration correlated with the sleep item of the BDI (r=-0.310; P<.001; n=166). CONCLUSIONS: These findings demonstrate that smartphone-based monitoring of depressive symptoms via the ReMAP app provides valid assessments of depressive symptomatology and, therefore, represents a useful tool for prospective digital phenotyping in affective disorder patients in clinical and research applications.

3.
Eur Neuropsychopharmacol ; 36: 10-17, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32451266

RESUMO

While the hippocampus remains a region of high interest for neuropsychiatric research, the precise contributors to hippocampal morphometry are still not well understood. We and others previously reported a hippocampus specific effect of a tescalcin gene (TESC) regulating single nucleotide polymorphism (rs7294919) on gray matter volume. Here we aimed to replicate and extend these findings. Two complementary morphometric approaches (voxel based morphometry (VBM) and automated volumetric segmentation) were applied in a well-powered cohort from the Marburg-Münster Affective Disorder Cohort Study (MACS) including N=1137 participants (n=636 healthy controls, n=501 depressed patients). rs7294919 homozygous T-allele genotype was significantly associated with lower hippocampal gray matter density as well as with reduced hippocampal volume. Exploratory whole brain VBM analyses revealed no further associations with gray matter volume outside the hippocampus. No interaction effects of rs7294919 with depression nor with childhood trauma on hippocampal morphometry could be detected. Hippocampal subfield analyses revealed similar effects of rs7294919 in all hippocampal subfields. In sum, our results replicate a hippocampus specific effect of rs7294919 on brain structure. Due to the robust evidence for a pronounced association between the reported polymorphism and hippocampal morphometry, future research should consider investigating the potential clinical and functional relevance of the reported association.

4.
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.

5.
Mol Psychiatry ; 25(12): 3422-3431, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30185937

RESUMO

Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery sample of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication sample (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery sample. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication sample. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.

6.
Psychol Med ; 50(5): 849-856, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31010441

RESUMO

BACKGROUND: Electroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of ECT in a non-randomized prospective study focusing on white matter changes over time. METHODS: Twenty-nine severely depressed patients receiving ECT in addition to inpatient treatment, 69 severely depressed patients with inpatient treatment (NON-ECT) and 52 healthy controls (HC) took part in a non-randomized prospective study. Participants were scanned twice, approximately 6 weeks apart, using diffusion tensor imaging, applying tract-based spatial statistics. Additional correlational analyses were conducted in the ECT subsample to investigate the effects of seizure duration and therapeutic response. RESULTS: Mean diffusivity (MD) increased after ECT in the right hemisphere, which was an ECT-group-specific effect. Seizure duration was associated with decreased fractional anisotropy (FA) following ECT. Longitudinal changes in ECT were not associated with therapy response. However, within the ECT group only, baseline FA was positively and MD negatively associated with post-ECT symptomatology. CONCLUSION: Our data suggest that ECT changes white matter integrity, possibly reflecting increased permeability of the blood-brain barrier, resulting in disturbed communication of fibers. Further, baseline diffusion metrics were associated with therapy response. Coherent fiber structure could be a prerequisite for a generalized seizure and inhibitory brain signaling necessary to successfully inhibit increased seizure activity.

7.
Lancet Psychiatry ; 6(4): 318-326, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30904126

RESUMO

BACKGROUND: Childhood maltreatment is a leading environmental risk factor for an unfavourable course of disease in major depressive disorder. Both maltreatment and major depressive disorder are associated with similar brain structural alterations suggesting that brain structural changes could mediate the adverse influence of maltreatment on clinical outcome in major depressive disorder. However, longitudinal studies have not been able to confirm this hypothesis. We therefore aimed to clarify the relationship between childhood trauma, brain structural alterations, and depression relapse in a longitudinal design. METHODS: We recruited participants at the Department of Psychiatry, University of Münster, Germany, from the Münster Neuroimage Cohort for whom 2-year longitudinal clinical data were available. Baseline data acquisition comprised clinical assessments, structural MRI, and retrospective assessment of the extent of childhood maltreatment experiences using the Childhood Trauma Questionnaire. Clinical follow-up assessments were conducted in all participants 2 years after initial recruitment. FINDINGS: Initial recruitment was March 21, 2010-Jan 29, 2016; follow-up reassessment Sept 7, 2012-March 9, 2018. 110 patients with major depressive disorder participated in this study. 35 patients were relapse-free, whereas 75 patients had experienced depression relapse within the 2-year follow-up period. Childhood maltreatment was significantly associated with depression relapse during follow-up (odds ratio [OR] 1·035, 95% CI 1·001-1·070; p=0·045). Both previous childhood maltreatment experiences and future depression relapse were associated with reduced cortical surface area (OR 0·996, 95% CI 0·994-0·999; p=0·001), primarily in the right insula at baseline (r=-0·219, p=0·023). Insular surface area was shown to mediate the association between maltreatment and future depression relapse (indirect effect: coefficient 0·0128, SE 0·0081, 95% CI 0·0024-0·0333). INTERPRETATION: Early life stress has a detrimental effect on brain structure, which increases the risk of unfavourable disease courses in major depression. Clinical and translational research should explore the role of childhood maltreatment as causing a potential clinically and biologically distinct subtype of major depressive disorder. FUNDING: The German Research Foundation, the Interdisciplinary Centre for Clinical Research, and the Deanery of the Medical Faculty of the University of Münster.


Assuntos
Adultos Sobreviventes de Eventos Adversos na Infância/psicologia , Encéfalo/diagnóstico por imagem , Transtorno Depressivo Maior/diagnóstico por imagem , Adolescente , Adulto , Transtorno Depressivo Maior/tratamento farmacológico , Transtorno Depressivo Maior/epidemiologia , Feminino , Seguimentos , Humanos , Interpretação de Imagem Assistida por Computador , Estudos Longitudinais , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Escalas de Graduação Psiquiátrica , Recidiva , Estudos Retrospectivos , Fatores de Risco , Inquéritos e Questionários , Adulto Jovem
8.
Psychoneuroendocrinology ; 100: 18-26, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30268003

RESUMO

Obesity is a clinically relevant and highly prevalent somatic comorbidity of major depression (MDD). Genetic predisposition and history of childhood trauma have both independently been demonstrated to act as risk factors for obesity and to be associated with alterations in reward related brain structure and function. We therefore aimed to investigate the influence of childhood maltreatment and genetic risk for obesity on structural and functional imaging correlates associated with reward processing in MDD. 161 MDD patients underwent structural and functional MRI during a frequently used card guessing paradigm. Main and interaction effects of a polygenic risk score for obesity (PRS) and childhood maltreatment experiences as assessed using the Childhood Trauma Questionnaire (CTQ) were investigated. We found that maltreatment experiences and polygenic risk for obesity significantly interacted on a) body mass index b) gray matter volume of the orbitofrontal cortex as well as on c) BOLD response in the right insula during reward processing. While polygenic risk for obesity was associated with elevated BMI as well as with decreased OFC gray matter and increased insular BOLD response in non-maltreated patients, these associations were absent in patients with a history of childhood trauma. No significant main effect of PRS or maltreatment on gray matter or BOLD response could be detected at the applied thresholds. The present study suggests that childhood maltreatment moderates the influence of genetic load for obesity on BMI as well as on altered brain structure and function in reward related brain circuits in MDD.


Assuntos
Sobreviventes Adultos de Maus-Tratos Infantis/psicologia , Encéfalo/patologia , Encéfalo/fisiopatologia , Transtorno Depressivo Maior , Carga Genética , Obesidade/genética , Recompensa , Adulto , Antidepressivos/uso terapêutico , Índice de Massa Corporal , Encéfalo/diagnóstico por imagem , Criança , Maus-Tratos Infantis/psicologia , Transtorno Depressivo Maior/diagnóstico , Transtorno Depressivo Maior/tratamento farmacológico , Transtorno Depressivo Maior/patologia , Transtorno Depressivo Maior/fisiopatologia , Feminino , Predisposição Genética para Doença , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Obesidade/complicações , Obesidade/psicologia , Estudos Retrospectivos , Fatores de Risco , Inquéritos e Questionários , Adulto Jovem
9.
Psychoneuroendocrinology ; 91: 179-185, 2018 05.
Artigo em Inglês | MEDLINE | ID: mdl-29571075

RESUMO

Obesity has been associated with a variety of neurobiological alterations. Recent neuroimaging research has pointed to the relevance of brain structural and functional alterations in the development of obesity. However, while the role of gray matter atrophy in obesity has been evidenced in several well powered studies, large scale evidence for altered white matter integrity in obese subjects is still absent. With this study, we therefore aimed to investigate potential associations between white matter abnormalities and body mass index (BMI) in two large independent samples of healthy adults. Associations between BMI values and whole brain fractional anisotropy (FA) were investigated in two independent cohorts: A sample of n = 369 healthy subjects from the Münster Neuroimaging Cohort (MNC), as well as a public available sample of n = 1064 healthy subjects of the Humane Connectome Project (HCP) were included in the present study. Tract based spatial statistics (TBSS) analyses of BMI on whole brain FA were conducted including age and sex as nuisance covariates using the FMRIB library (FSL Version 5.0). Threshold-free cluster enhancement was applied to control for multiple comparisons. In both samples higher BMI was significantly associated with strong and widespread FA reductions. These effects were most pronounced in the corpus callosum, bilateral posterior thalamic radiation, bilateral internal capsule and external capsule, bilateral inferior longitudinal fasciculus and inferior fronto-occipital fasciculus. The association was found to be independent of age, sex and other cardiovascular risk factors. No significant positive associations between BMI and FA occurred. With this highly powered study, we provide robust evidence for globally reduced white matter integrity associated with elevated BMI including replication in an independent sample. The present work thus points out the relevance of white matter alterations as a neurobiological correlate of obesity.


Assuntos
Obesidade/fisiopatologia , Substância Branca/fisiologia , Adulto , Anisotropia , Índice de Massa Corporal , Encéfalo/fisiologia , Estudos de Coortes , Conectoma , Imagem de Tensor de Difusão , Feminino , Substância Cinzenta/fisiologia , Voluntários Saudáveis , Humanos , Masculino , Pessoa de Meia-Idade , Obesidade/complicações
10.
PLoS One ; 7(6): e39148, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22720055

RESUMO

Leukemias are exceptionally well studied at the molecular level and a wealth of high-throughput data has been published. But further utilization of these data by researchers is severely hampered by the lack of accessible integrative tools for viewing and analysis. We developed the Leukemia Gene Atlas (LGA) as a public platform designed to support research and analysis of diverse genomic data published in the field of leukemia. With respect to leukemia research, the LGA is a unique resource with comprehensive search and browse functions. It provides extensive analysis and visualization tools for various types of molecular data. Currently, its database contains data from more than 5,800 leukemia and hematopoiesis samples generated by microarray gene expression, DNA methylation, SNP and next generation sequencing analyses. The LGA allows easy retrieval of large published data sets and thus helps to avoid redundant investigations. It is accessible at www.leukemia-gene-atlas.org.


Assuntos
Bases de Dados Genéticas , Leucemia/genética , Humanos , Internet
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...