scholarly journals Personalized estimates of morphometric similarity in bipolar disorder and schizophrenia

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Gaelle E. Doucet ◽  
Dongdong Lin ◽  
Yuhui Du ◽  
Zening Fu ◽  
David C. Glahn ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Cortical Thickness ◽  
Similarity Index ◽  
Individual Variability ◽  
Healthy Individuals ◽  
Brain Morphometry ◽  
Disease Mechanisms ◽  
Individual Variations ◽  
Group Similarity ◽  
Subcortical Volumes

AbstractBipolar disorder and schizophrenia are associated with brain morphometry alterations. This study investigates inter-individual variability in brain structural profiles, both within diagnostic groups and between patients and healthy individuals. Brain morphometric measures from three independent samples of patients with schizophrenia (n = 168), bipolar disorder (n = 122), and healthy individuals (n = 180) were modeled as single vectors to generated individualized profiles of subcortical volumes and regional cortical thickness. These profiles were then used to compute a person-based similarity index (PBSI) for subcortical volumes and for regional cortical thickness, to quantify the within-group similarity of the morphometric profile of each individual to that of the other participants in the same diagnostic group. There was no effect of diagnosis on the PBSI for subcortical volumes. In contrast, compared to healthy individuals, the PBSI for cortical thickness was lower in patients with schizophrenia (effect size = 0.4, p ≤ 0.0002), but not in patients with bipolar disorder. The results were robust and reproducible across samples. We conclude that disease mechanisms for these disorders produce modest inter-individual variations in brain morphometry that should be considered in future studies attempting to cluster patients in subgroups.

Cortical Thickness and Subcortical Volumes in Schizophrenia and Bipolar Disorder

2010 ◽  
Vol 68 (1) ◽  
pp. 41-50 ◽  
Author(s):  
Lars M. Rimol ◽  
Cecilie B. Hartberg ◽  
Ragnar Nesvåg ◽  
Christine Fennema-Notestine ◽  
Donald J. Hagler ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Cortical Thickness ◽  
Subcortical Volumes

CORTICAL THICKNESS AND SUBCORTICAL VOLUMES IN SCHIZOPHRENIA AND BIPOLAR DISORDER

2010 ◽  
Vol 117 (2-3) ◽  
pp. 459 ◽  
Author(s):  
Lars M. Rimol ◽  
Cecilie Hartberg ◽  
Ragnar Nesvåg ◽  
Christine Fennema-Notestine ◽  
Don Hagler ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Cortical Thickness ◽  
Subcortical Volumes

scholarly journals Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years

2020 ◽  
Author(s):  
Sophia Frangou ◽  
Amirhossein Modabbernia ◽  
Gaelle E Doucet ◽  
Efstathios Papachristou ◽  
Steven CR Williams ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Large Scale ◽  
Meta Analysis ◽  
General Pattern ◽  
Individual Variability ◽  
Anterior Cingulate ◽  
Healthy Individuals ◽  
Large Scale Analysis ◽  
Age Related ◽  
Steep Decrease

AbstractDelineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

Cortical thickness, cortical surface area and subcortical volumes in schizophrenia and bipolar disorder patients with cannabis use

2018 ◽  
Vol 28 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Cecilie Bhandari Hartberg ◽  
Elisabeth H. Lange ◽  
Trine Vik Lagerberg ◽  
Unn K. Haukvik ◽  
Ole A. Andreassen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Surface Area ◽  
Cortical Thickness ◽  
Cannabis Use ◽  
Cortical Surface ◽  
Cortical Surface Area ◽  
Subcortical Volumes

scholarly journals Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

2021 ◽  
pp. 1-12
Author(s):  
Simon Schmitt ◽  
Tina Meller ◽  
Frederike Stein ◽  
Katharina Brosch ◽  
Kai Ringwald ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Mental Disorders ◽  
Cortical Thickness ◽  
Genetic Risk ◽  
Right Hemisphere ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Grey Matter Volume ◽  
Polygenic Risk ◽  
Risk For Depression

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

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