Association Between Food Patterns and Gray Matter Volume.
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ABSTRACT:
SUBMITTER: Kokubun K
PROVIDER: S-EPMC6828934 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Smoking of cigarettes among young adolescents is a pressing public health issue. However, the neural mechanisms underlying smoking initiation and sustenance during adolescence, especially the potential causal interactions between altered brain development and smoking behaviour, remain elusive. Here, using large longitudinal adolescence imaging genetic cohorts, we identify associations between left ventromedial prefrontal cortex (vmPFC) gray matter volume (GMV) and subsequent self-reported smoking initiation, and between right vmPFC GMV and the maintenance of smoking behaviour. Rule-breaking behaviour mediates the association between smaller left vmPFC GMV and smoking behaviour based on longitudinal cross-lagged analysis and Mendelian randomisation. In contrast, smoking behaviour associated longitudinal covariation of right vmPFC GMV and sensation seeking (especially hedonic experience) highlights a potential reward-based mechanism for sustaining addictive behaviour. Taken together, our findings reveal vmPFC GMV as a possible biomarker for the early stages of nicotine addiction, with implications for its prevention and treatment.
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Project description:BackgroundMounting evidence links poor sleep quality with a higher risk of late-life dementia. However, the structural and cognitive correlates of insomnia are still not well understood. The study aims were to characterize the cognitive performance and brain structural pattern of cognitively unimpaired adults at increased risk for Alzheimer's disease (AD) with insomnia.MethodsThis cross-sectional study included 1683 cognitively unimpaired middle/late-middle-aged adults from the ALFA (ALzheimer and FAmilies) study who underwent neuropsychological assessment, T1-weighted structural imaging (n = 366), and diffusion-weighted imaging (n = 334). The World Health Organization's World Mental Health Survey Initiative version of the Composite International Diagnostic Interview was used to define the presence or absence of insomnia. Multivariable regression models were used to evaluate differences in cognitive performance between individuals with and without insomnia, as well as potential interactions between insomnia and the APOE genotype. Voxel-based morphometry and tract-based spatial statistics were used to assess between-group differences and potential interactions between insomnia and the APOE genotype in gray matter volume and white matter diffusion metrics.ResultsInsomnia was reported by 615 out of 1683 participants (36.5%), including 137 out of 366 (37.4%) with T1-weighted structural imaging available and 119 out of 334 (35.6%) with diffusion-weighted imaging. Individuals with insomnia (n = 615) performed worse in executive function tests than non-insomniacs and displayed lower gray matter volume in left orbitofrontal and right middle temporal cortex, bilateral precuneus, posterior cingulate cortex and thalamus, higher gray matter volume in the left caudate nucleus, and widespread reduction of mean and axial diffusivity in right hemisphere white matter tracts. Insomnia interacted with the APOE genotype, with APOE-ε4 carriers displaying lower gray matter volumes when insomnia was present, but higher volumes when insomnia was not present, in several gray matter regions, including the left angular gyrus, the bilateral superior frontal gyri, the thalami, and the right hippocampus.ConclusionsInsomnia in cognitively unimpaired adults at increased risk for AD is associated to poorer performance in some executive functions and volume changes in cortical and subcortical gray matter, including key areas involved in Alzheimer's disease, as well as decreased white matter diffusivity.
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Project description:Purpose The biological mechanisms underlying developmental stuttering remain unclear. In a previous investigation, we showed that there is significant spatial correspondence between regional gray matter structural anomalies and the expression of genes linked to energy metabolism. In the current study, we sought to further examine the relationship between structural anomalies in the brain in children with persistent stuttering and brain regional energy metabolism. Method High-resolution structural MRI scans were acquired from 26 persistent stuttering and 44 typically developing children. Voxel-based morphometry was used to quantify the between-group gray matter volume (GMV) differences across the whole brain. Group differences in GMV were then compared with published values for the pattern of glucose metabolism measured via F18 fluorodeoxyglucose uptake in the brains of 29 healthy volunteers using positron emission tomography. Results A significant positive correlation between GMV differences and F18 fluorodeoxyglucose uptake was found in the left hemisphere (ρ = .36, p < .01), where speech-motor and language processing are typically localized. No such correlation was observed in the right hemisphere (ρ = .05, p = .70). Conclusions Corroborating our previous gene expression studies, the results of the current study suggest a potential connection between energy metabolism and stuttering. Brain regions with high energy utilization may be particularly vulnerable to anatomical changes associated with stuttering. Such changes may be further exacerbated when there are sharp increases in brain energy utilization, which coincides with the developmental period of rapid speech/language acquisition and the onset of stuttering during childhood. Supplemental Material https://doi.org/10.23641/asha.14110454.
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Project description:Advancing age results in altered cognitive and neuroimaging-derived markers of neural integrity. Whether cognitive changes are the result of variations in brain measures remains unclear and relating the two across the lifespan poses a unique set of problems. It must be determined whether statistical associations between cognitive and brain measures truly exist and are not epiphenomenal due solely to their shared relationships with age. The purpose of this study was to determine whether cerebral blood flow (CBF) and gray matter volume (GMV) measures make unique and better predictions of cognition than age alone. Multivariate analyses identified brain-wide covariance patterns from 35 healthy young and 23 healthy older adults using MRI-derived measures of CBF and GMV related to three cognitive composite scores (i.e., memory, fluid ability, and speed/attention). These brain-cognitive relationships were consistent across the age range, and not the result of epiphenomenal associations with age and each imaging modality provided its own unique information. The CBF and GMV patterns each accounted for unique aspects of cognition and accounted for nearly all the age-related variance in the cognitive composite scores. The findings suggest that measures derived from multiple imaging modalities explain larger amounts of variance in cognition providing a more complete understanding of the aging brain.
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Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.
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Project description:Despite evidently distinct symptoms, tension-type headache (TTH) and migraine are highly comorbid and exhibit many similarities in clinical practice. The purpose of this study was to investigate whether both types of headaches are similar in brain morphology.Consecutive patients with TTH and age- and sex-matched patients with migraine and healthy controls were enrolled for brain magnetic resonance imaging examination. Patients with TTH were excluded if they reported any headache features or associated symptoms of migraine. Changes in gray matter (GM) volume associated with headache diagnosis (TTH vs. migraine) and frequency (episodic vs. chronic) were examined using voxel-based morphometry. The correlation with headache profile and the discriminative ability between TTH and migraine were also investigated for these GM changes.In comparison with controls (n?=?43), the patients with TTH (25 episodic and 24 chronic) exhibited a GM volume increase in the anterior cingulate cortex, supramarginal gyrus, temporal pole, lateral occipital cortex, and caudate. The patients with migraine (31 episodic and 25 chronic) conversely exhibited a GM volume decrease in the orbitofrontal cortex. These GM changes did not correlate with any headache profile. A voxel-wise 2?×?2 factorial analysis further revealed the substantial effects of headache types and frequency in the comparison of GM volume between TTH and migraine. Specifically, the migraine group (vs. TTH) had a GM decrease in the superior and middle frontal gyri, cerebellum, dorsal striatum, and precuneus. The chronic group (vs. episodic group) otherwise demonstrated a GM decrease in the bilateral insula and anterior cingulate cortex. In receiver operating characteristic analysis, the GM volumes of the left superior frontal gyrus and right cerebellum V combined had good discriminative ability for distinguishing TTH and migraine (area under the curve?=?0.806).TTH and migraine are separate headache disorders with different characteristics in relation to GM changes. The major morphological difference between the two types of headaches is the relative GM decrease of the prefrontal and cerebellar regions in migraine, which may reflect a higher allostatic load associated with this disabling headache.
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