Cortical Thickness and Surface Area Abnormalities in Bipolar I and II Disorders

Yoonmi Woo ◽  
Wooyoung Kang ◽  
Youbin Kang ◽  
Aram Kim ◽  
Kyu-Man Han ◽  
2020 ◽  
Vol 10 (1) ◽  
Mirjam A. Rinne-Albers ◽  
Charlotte P. Boateng ◽  
Steven J. van der Werff ◽  
Francien Lamers-Winkelman ◽  
Serge A. Rombouts ◽  

2016 ◽  
Vol 37 (6) ◽  
pp. 2027-2038 ◽  
Nandita Vijayakumar ◽  
Nicholas B. Allen ◽  
George Youssef ◽  
Meg Dennison ◽  
Murat Yücel ◽  

2008 ◽  
Vol 29 (2) ◽  
pp. 222-236 ◽  
Alex Fornito ◽  
Stephen J. Wood ◽  
Sarah Whittle ◽  
Jack Fuller ◽  
Chris Adamson ◽  

2014 ◽  
Vol 35 (12) ◽  
pp. 6011-6022 ◽  
Katja Koelkebeck ◽  
Jun Miyata ◽  
Manabu Kubota ◽  
Waldemar Kohl ◽  
Shuraku Son ◽  

2011 ◽  
Vol 17 (6) ◽  
pp. 1080-1093 ◽  
C.B. Hartberg ◽  
K. Sundet ◽  
L.M. Rimol ◽  
U.K. Haukvik ◽  
E.H. Lange ◽  

AbstractRelationships between cortical brain structure and neurocognitive functioning have been reported in schizophrenia, but findings are inconclusive, and only a few studies in bipolar disorder have addressed this issue. This is the first study to directly compare relationships between cortical thickness and surface area with neurocognitive functioning in patients with schizophrenia (n = 117) and bipolar disorder (n = 121) and healthy controls (n = 192). MRI scans were obtained, and regional cortical thickness and surface area measurements were analyzed for relationships with test scores from 6 neurocognitive domains. In the combined sample, cortical thickness in the right rostral anterior cingulate was inversely related to working memory, and cortical surface area in four frontal and temporal regions were positively related to neurocognitive functioning. A positive relationship between left transverse temporal thickness and processing speed was specific to schizophrenia. A negative relationship between right temporal pole thickness and working memory was specific to bipolar disorder. In conclusion, significant cortical structure/function relationships were found in a large sample of healthy controls and patients with schizophrenia or bipolar disorder. The differences that were found between schizophrenia and bipolar may indicate differential relationship patterns in the two disorders, which may be of relevance for understanding the underlying pathophysiology. (JINS, 2011, 17, 1080–1093)

2016 ◽  
Vol 46 (10) ◽  
pp. 2083-2096 ◽  
G. Roberts ◽  
R. Lenroot ◽  
A. Frankland ◽  
P. K. Yeung ◽  
N. Gale ◽  

BackgroundFronto-limbic structural brain abnormalities have been reported in patients with bipolar disorder (BD), but findings in individuals at increased genetic risk of developing BD have been inconsistent. We conducted a study in adolescents and young adults (12–30 years) comparing measures of fronto-limbic cortical and subcortical brain structure between individuals at increased familial risk of BD (at risk; AR), subjects with BD and controls (CON). We separately examined cortical volume, thickness and surface area as these have distinct neurodevelopmental origins and thus may reflect differential effects of genetic risk.MethodWe compared fronto-limbic measures of grey and white matter volume, cortical thickness and surface area in 72 unaffected-risk individuals with at least one first-degree relative with bipolar disorder (AR), 38 BD subjects and 72 participants with no family history of mental illness (CON).ResultsThe AR group had significantly reduced cortical thickness in the left pars orbitalis of the inferior frontal gyrus (IFG) compared with the CON group, and significantly increased left parahippocampal gyral volume compared with those with BD.ConclusionsThe finding of reduced cortical thickness of the left pars orbitalis in AR subjects is consistent with other evidence supporting the IFG as a key region associated with genetic liability for BD. The greater volume of the left parahippocampal gyrus in those at high risk is in line with some prior reports of regional increases in grey matter volume in at-risk subjects. Assessing multiple complementary morphometric measures may assist in the better understanding of abnormal developmental processes in BD.

2016 ◽  
Vol 46 (10) ◽  
pp. 2145-2155 ◽  
L. Haring ◽  
A. Müürsepp ◽  
R. Mõttus ◽  
P. Ilves ◽  
K. Koch ◽  

BackgroundIn studies using magnetic resonance imaging (MRI), some have reported specific brain structure–function relationships among first-episode psychosis (FEP) patients, but findings are inconsistent. We aimed to localize the brain regions where cortical thickness (CTh) and surface area (cortical area; CA) relate to neurocognition, by performing an MRI on participants and measuring their neurocognitive performance using the Cambridge Neuropsychological Test Automated Battery (CANTAB), in order to investigate any significant differences between FEP patients and control subjects (CS).MethodExploration of potential correlations between specific cognitive functions and brain structure was performed using CANTAB computer-based neurocognitive testing and a vertex-by-vertex whole-brain MRI analysis of 63 FEP patients and 30 CS.ResultsSignificant correlations were found between cortical parameters in the frontal, temporal, cingular and occipital brain regions and performance in set-shifting, working memory manipulation, strategy usage and sustained attention tests. These correlations were significantly dissimilar between FEP patients and CS.ConclusionsSignificant correlations between CTh and CA with neurocognitive performance were localized in brain areas known to be involved in cognition. The results also suggested a disrupted structure–function relationship in FEP patients compared with CS.

2020 ◽  
Vol 30 (10) ◽  
pp. 5597-5603 ◽  
Dennis van der Meer ◽  
Oleksandr Frei ◽  
Tobias Kaufmann ◽  
Chi-Hua Chen ◽  
Wesley K Thompson ◽  

Abstract The thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remain unknown. Our ability to identify causal genetic variants can be improved by employing brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, that is, lower polygenicity and higher discoverability. Using Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area, as well as the polygenicity and discoverability of regional measures. We made use of UK Biobank data from 30 880 healthy White European individuals (mean age 64.3, standard deviation 7.5, 52.1% female). We found large genetic overlap between total surface area and mean thickness, sharing 4016 out of 7941 causal variants. Regional surface area was more discoverable (P = 2.6 × 10−6) and less polygenic (P = 0.004) than regional thickness measures. These findings may serve as a roadmap for improved future GWAS studies; knowledge of which measures are most discoverable may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

2020 ◽  
Vol 31 (1) ◽  
pp. 702-715
J Eric Schmitt ◽  
Armin Raznahan ◽  
Siyuan Liu ◽  
Michael C Neale

Abstract The mechanisms underlying cortical folding are incompletely understood. Prior studies have suggested that individual differences in sulcal depth are genetically mediated, with deeper and ontologically older sulci more heritable than others. In this study, we examine FreeSurfer-derived estimates of average convexity and mean curvature as proxy measures of cortical folding patterns using a large (N = 1096) genetically informative young adult subsample of the Human Connectome Project. Both measures were significantly heritable near major sulci and primary fissures, where approximately half of individual differences could be attributed to genetic factors. Genetic influences near higher order gyri and sulci were substantially lower and largely nonsignificant. Spatial permutation analysis found that heritability patterns were significantly anticorrelated to maps of evolutionary and neurodevelopmental expansion. We also found strong phenotypic correlations between average convexity, curvature, and several common surface metrics (cortical thickness, surface area, and cortical myelination). However, quantitative genetic models suggest that correlations between these metrics are largely driven by nongenetic factors. These findings not only further our understanding of the neurobiology of gyrification, but have pragmatic implications for the interpretation of heritability maps based on automated surface-based measurements.

2018 ◽  
Vol 29 (3) ◽  
pp. 1139-1149 ◽  
Shaili C Jha ◽  
Kai Xia ◽  
Mihye Ahn ◽  
Jessica B Girault ◽  
Gang Li ◽  

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