12 research outputs found

    Striatal morphology and neurocognitive dysfunction in Huntington disease: The IMAGE-HD study

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    We aimed to investigate the relationship between striatal morphology in Huntington disease (HD) and measures of motor and cognitive dysfunction. MRI scans, from the IMAGE-HD study, were obtained from 36 individuals with pre-symptomatic HD (pre-HD), 37 with early symptomatic HD (symp-HD), and 36 healthy matched controls. The neostriatum was manually segmented and a surface-based parametric mapping protocol derived two pointwise shape measures: thickness and surface dilation ratio. Significant shape differences were detected between all groups. Negative associations were detected between lower thickness and surface area shape measure and CAG repeats, disease burden score, and UHDRS total motor score. In symp-HD, UPSIT scores were correlated with higher thickness in left caudate tail and surface dilation ratio in left posterior putamen; Stroop scores were positively correlated with the thickness of left putamen head and body. Self-paced tapping (slow) was correlated with higher thickness and surface dilation ratio in the right caudate in symp-HD and with bilateral putamen in pre-HD. Self-paced tapping (fast) was correlated with higher surface dilation ratio in the right anterior putamen in symp-HD. Shape changes correlated with functional measures subserved by corticostriatal circuits, suggesting that the neostriatum is a potentially useful structural basis for characterisation of endophenotypes of HD.This work was supported by the CHDI Foundation, Inc. (USA) (grant number A – 3433); the National Health and Medical Research Council (NHMRC) (grant number 606650); the RANZCP New Investigator grant 2013 (FAW); and the University of Melbourne – computer and software support

    Deformation phenotypes.

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    <p>During the affine registration process, native space images are skewed (sheared) to ‘correct’ hemispheric asymmetry and align the images to the symmetric template. The magnitude of the skewing is a quantitative measure of hemispheric asymmetry. The arrows in each panel indicate the direction volume is shifted during image registration. The asymmetric distribution of volume in the native space (non-deformed) image is therefore opposite to the direction of the arrows. The skews have been exaggerated to emphasize the otherwise subtle distortions introduced by the registration process. Panel A: A positive skew in the transverse plane corresponds to an anterior shift of voxels in the left hemisphere and a posterior shift of voxels in the right hemisphere during registration to the symmetric template. Panel B: A positive skew in the coronal plane leads to a ventral shift of voxels in the left hemisphere and a dorsal shift of voxels in the right hemisphere during registration to the symmetric template. Panel C shows the distributions of the normalized phenotypes.</p

    Cingulate sulcus asymmetry.

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    <p>Transverse Slices showing the relative position of the left and right ascending ramus of the cingulate sulcus. The left panel shows an image that was consistently scored as +2, the middle panel shows an image scored as symmetric (score = 0), and the right panel shows an image scored as −2.</p

    Correlation coefficients of cerebral widths for each pair of regions.

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    <p>The Pearson's correlation is shown in the upper right triangle of the matrix and the p-value determined from permutation testing is shown in the lower left triangle of the matrix.</p

    Phenotype correlations among the asymmetry measures.

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    <p>The correlation estimate is shown in the upper right triangle of the matrix and the p-value based on permutation testing is shown in the lower left triangle of the matrix.</p

    Genetic (<b>ρ<sub>G</sub></b>) and environmental (<b>ρ<sub>E</sub></b>) correlations for cerebral width phenotypes.

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    <p>The estimate of the proportion of common genetic sources contributing to the phenotypic covariance of each pair of cerebral width is shown in the upper triangle of the table and the proportion of common environmental sources contributing to the covariance between traits is shown in the lower triangle of the table. The standard error of the estimate is in parentheses.</p

    Cerebral Widths and Asymmetry Quotient Distributions.

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    <p>Left panel shows an example of a traverse slice dorsal to the corpus callosum with cerebral widths indicated on the right hemisphere. Right panel shows the distributions of the asymmetry quotients for hemisphere volume and each cerebral width.</p

    Brain structure–function associations in multi-generational families genetically enriched for bipolar disorder

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    Recent theories regarding the pathophysiology of bipolar disorder suggest contributions of both neurodevelopmental and neurodegenerative processes. While structural neuroimaging studies indicate disease-associated neuroanatomical alterations, the behavioural correlates of these alterations have not been well characterized. Here, we investigated multi-generational families genetically enriched for bipolar disorder to: (i) characterize neurobehavioural correlates of neuroanatomical measures implicated in the pathophysiology of bipolar disorder; (ii) identify brain–behaviour associations that differ between diagnostic groups; (iii) identify neurocognitive traits that show evidence of accelerated ageing specifically in subjects with bipolar disorder; and (iv) identify brain–behaviour correlations that differ across the age span. Structural neuroimages and multi-dimensional assessments of temperament and neurocognition were acquired from 527 (153 bipolar disorder and 374 non-bipolar disorder) adults aged 18–87 years in 26 families with heavy genetic loading for bipolar disorder. We used linear regression models to identify significant brain–behaviour associations and test whether brain–behaviour relationships differed: (i) between diagnostic groups; and (ii) as a function of age. We found that total cortical and ventricular volume had the greatest number of significant behavioural associations, and included correlations with measures from multiple cognitive domains, particularly declarative and working memory and executive function. Cortical thickness measures, in contrast, showed more specific associations with declarative memory, letter fluency and processing speed tasks. While the majority of brain–behaviour relationships were similar across diagnostic groups, increased cortical thickness in ventrolateral prefrontal and parietal cortical regions was associated with better declarative memory only in bipolar disorder subjects, and not in non-bipolar disorder family members. Additionally, while age had a relatively strong impact on all neurocognitive traits, the effects of age on cognition did not differ between diagnostic groups. Most brain–behaviour associations were also similar across the age range, with the exception of cortical and ventricular volume and lingual gyrus thickness, which showed weak correlations with verbal fluency and inhibitory control at younger ages that increased in magnitude in older subjects, regardless of diagnosis. Findings indicate that neuroanatomical traits potentially impacted by bipolar disorder are significantly associated with multiple neurobehavioural domains. Structure–function relationships are generally preserved across diagnostic groups, with the notable exception of ventrolateral prefrontal and parietal association cortex, volumetric increases in which may be associated with cognitive resilience specifically in individuals with bipolar disorder. Although age impacted all neurobehavioural traits, we did not find any evidence of accelerated cognitive decline specific to bipolar disorder subjects. Regardless of diagnosis, greater global brain volume may represent a protective factor for the effects of ageing on executive functioning.National Institute of Health/[R01MH075007]/NIH/Estados UnidosNational Institute of Health/[R01MH095454]/NIH/Estados UnidosNational Institute of Health/[P30NS062691]/NIH/Estados UnidosNational Institute of Health/[K23MH074644-01]/NIH/Estados UnidosNational Institute of Health/[R01HG006695]/NIH/Estados UnidosNational Institute of Health/[K08MH086786]/NIH/Estados UnidosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM
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