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2.
Hum Brain Mapp ; 2020 Dec 27.
Artigo em Inglês | MEDLINE | ID: mdl-33368865

RESUMO

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013-12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi-)genetics. Finally, we highlight points where FreeSurfer-based hippocampal subfield studies may be optimized.

3.
Brain Struct Funct ; 225(7): 2111-2129, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32696074

RESUMO

A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general intelligence remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods - have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling to test whether out-of-sample prediction of individual intelligence scores is possible on the basis of voxel-wise gray matter volume. Features were derived from structural magnetic resonance imaging data (N = 308) using (a) a purely data-driven method (principal component analysis) and (b) a domain knowledge-based approach (atlas parcellation). When using relative gray matter (corrected for total brain size), only the atlas-based approach provided significant prediction, while absolute gray matter (uncorrected) allowed for above-chance prediction with both approaches. Importantly, in all significant predictions, the absolute error was relatively high, i.e., greater than ten IQ points, and in the atlas-based models, the predicted IQ scores varied closely around the sample mean. This renders the practical value even of statistically significant prediction results questionable. Analyses based on the gray matter of functional brain networks yielded significant predictions for the fronto-parietal network and the cerebellum. However, the mean absolute errors were not reduced in contrast to the global models, suggesting that general intelligence may be related more to global than region-specific differences in gray matter volume. More generally, our study highlights the importance of predictive statistical analysis approaches for clarifying the neurobiological bases of intelligence and provides important suggestions for future research using predictive modeling.

4.
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.

5.
Mol Psychiatry ; 2020 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-32424236

RESUMO

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.

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.

7.
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.

8.
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.

9.
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
10.
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
11.
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
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