scholarly journals Mediterranean-type diet and brain structural change from 73 to 76 years in a Scottish cohort

Neurology ◽  
2017 ◽  
Vol 88 (5) ◽  
pp. 449-455 ◽  
Author(s):  
Michelle Luciano ◽  
Janie Corley ◽  
Simon R. Cox ◽  
Maria C. Valdés Hernández ◽  
Leone C.A. Craig ◽  
...  

Objective:To assess the association between Mediterranean-type diet (MeDi) and change in brain MRI volumetric measures and mean cortical thickness across a 3-year period in older age (73–76 years).Methods:We focused on 2 longitudinal brain volumes (total and gray matter; n = 401 and 398, respectively) plus a longitudinal measurement of cortical thickness (n = 323), for which the previous cross-sectional evidence of an association with the MeDi was strongest. Adherence to the MeDi was calculated from data gathered from a food frequency questionnaire at age 70, 3 years prior to the baseline imaging data collection.Results:In regression models adjusting for relevant demographic and physical health indicators, we found that lower adherence to the MeDi was associated with greater 3-year reduction in total brain volume (explaining 0.5% of variance, p < 0.05). This effect was half the size of the largest covariate effect (i.e., age). Cross-sectional associations between MeDi and baseline MRI measures in 562 participants were not significant. Targeted analyses of meat and fish consumption did not replicate previous associations with total brain volume or total gray matter volume.Conclusions:Lower adherence to the MeDi in an older Scottish cohort is predictive of total brain atrophy over a 3-year interval. Fish and meat consumption does not drive this change, suggesting that other components of the MeDi or, possibly, all of its components in combination are responsible for the association.

Stroke ◽  
2019 ◽  
Vol 50 (4) ◽  
pp. 783-788 ◽  
Author(s):  
Jeremy P. Berman ◽  
Faye L. Norby ◽  
Thomas Mosley ◽  
Elsayed Z. Soliman ◽  
Rebecca F. Gottesman ◽  
...  

Background and Purpose— Atrial fibrillation (AF) is associated with dementia independent of clinical stroke. The mechanisms underlying this association remain unclear. In a community-based cohort, the ARIC study (Atherosclerosis Risk in Communities), we evaluated (1) the longitudinal association of incident AF and (2) the cross-sectional association of prevalent AF with brain magnetic resonance imaging (MRI) abnormalities. Methods— The longitudinal analysis included 963 participants (mean age, 73±4.4 years; 62% women; 51% black) without prevalent stroke or AF who underwent a brain MRI in 1993 to 1995 and a second MRI in 2004 to 2006 (mean, 10.6±0.8 years). Outcomes included subclinical cerebral infarctions, sulcal size, ventricular size, and, for the cross-sectional analysis, white matter hyperintensity volume and total brain volume. Results— In the longitudinal analysis, 29 (3.0%) participants developed AF after the first brain MRI. Those who developed AF had higher odds of increase in subclinical cerebral infarctions (odds ratio [OR], 3.08; 95% CI, 1.39–6.83), worsening sulcal grade (OR, 3.56; 95% CI, 1.04–12.2), and worsening ventricular grade (OR, 9.34; 95% CI, 1.24–70.2). In cross-sectional analysis, of 969 participants, 35 (3.6%) had prevalent AF at the time of the 2004 to 2006 MRI scan. Those with AF had greater odds of higher sulcal (OR, 3.9; 95% CI, 1.7–9.1) and ventricular grade (OR, 2.4; 95% CI, 1.0–5.7) after multivariable adjustment and no difference in white matter hyperintensity or total brain volume. Conclusions— AF is independently associated with increase in subclinical cerebral infarction and worsening sulcal and ventricular grade—morphological changes associated with aging and dementia. More research is needed to define the mechanisms underlying AF-related neurodegeneration.


2022 ◽  
Vol 15 ◽  
Author(s):  
Eilidh MacNicol ◽  
Paul Wright ◽  
Eugene Kim ◽  
Irene Brusini ◽  
Oscar Esteban ◽  
...  

Age-specific resources in human MRI mitigate processing biases that arise from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue's relative contribution to total brain volume would change with age in the adult rat. Data from a longitudinal study of rats at 3, 5, 11, and 17 months old were used to test this hypothesis. Tissue volume was estimated from high resolution structural images using a priori information from tissue probability maps. However, existing tissue probability maps generated inaccurate gray matter probabilities in subcortical structures, particularly the thalamus. To address this issue, gray matter, white matter, and CSF tissue probability maps were generated by combining anatomical and signal intensity information. The effects of age on volumetric estimations were then assessed with mixed-effects models. Results showed that herein estimation of gray matter volumes better matched histological evidence, as compared to existing resources. All tissue volumes increased with age, and the tissue proportions relative to total brain volume varied across adulthood. Consequently, a set of rat brain templates and tissue probability maps from across the adult lifespan is released to expand the preclinical MRI community's fundamental resources.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 976-976
Author(s):  
Kemar V. Prussien ◽  
Bruce E. Compas ◽  
Rachel Siciliano ◽  
R. Sky Jones ◽  
Abagail E. Ciriegio ◽  
...  

Abstract Introduction: Individuals with sickle cell anemia (SCA) are at increased risk for deficits in multiple domains of neurocognitive functioning, including executive functions. In addition to assessing the effects of silent cerebral infarcts (SCI) and stroke on cognition, prior research has focused on hemoglobin and transcranial Doppler velocity as hemodynamic correlates. Recent studies have begun to use more precise measures of blood delivery to the brain (e.g., cerebral blood flow; CBF) to determine more sensitive indicators of cognitive risk prior to neurological injury. Nevertheless, empirical and meta-analytic findings suggest that these deficits increase with age, which can have broad impact on psychosocial functioning, including self-management and navigation through the transition from pediatric to adult medical care. This study aimed to assess brain volume as a mediator of the association between CBF and executive functioning in a sample of individuals with SCA. The secondary aim was to assess age as a moderator of hemodynamic and structural correlates of executive function. Methods: Children, adolescents, and young adults with SCA were enrolled prospectively. Each participant received a 3-Tesla non-contrast magnetic resonance imaging and magnetic resonance angiography of the brain, and a neurological examination by the study neurologist. Gray matter CBF was calculated from pseudo-continuous arterial spin labeling using the solution to the flow-modified Bloch equation after correcting for individual hematocrit. Three measures of brain volume were also computed from 3D-T1 images using Freesurfer version 7.1.1: total brain volume, gray matter volume, and white matter volume was calculated as the difference between the two. At a separate study visit, participants completed an age-appropriate Wechsler Working Memory Index (WMI). Pearson correlations assessed bivariate associations among variables, SPSS PROCESS macro was used to test gray matter volume as a mediator in the relation between CBF and working memory, and multiple linear regression analyses tested age as a moderator of the impact of CBF and brain volume on working memory. Results: Twenty-nine children and adolescents (ages 6 to 17 years) and 25 adults (ages 18 to 31 years) were enrolled. Five participants were excluded from analyses due to history of overt stroke that resulted in significant brain volume loss. Of 49 included participants, 20 had SCIs. Working memory was inversely correlated with age (r = -.30, p = .037) and CBF (r = -.36, p = .013), such that WMI decreased cross-sectionally with older age and higher CBF. Working memory was positively correlated with gray matter volume (r = .42, p = .002); however, it was not related to white matter volume (r = -.05, p = .715) or total brain volume (r = -.07, p = .642). Finally, patient age was positively correlated with CBF (r = .36, p = .014), but the association of age with gray matter volume did not reach statistical significance (r = -.27, p = .065). Analyses in Figure 1 show that although CBF and gray matter were directly related to working memory (path c and path b, respectively), gray matter volume did not mediate the association between CBF and working memory (path a*b). However, regression analyses (Table 1) showed that age moderated the association between gray matter volume and working memory, such that there was only a significant relation in children and adolescents. This association did not exist for young adults (Figure 2). Conclusions: Neurocognitive assessments has been cited as an important standard of care for children and adolescents with SCA. Given the increase in deficits with age, and the increase in mortality after transferring from pediatric to adult care, monitoring executive function abilities and potential impact on self-management should continue into adulthood. Findings from the current study provide preliminary evidence that cerebral hemodynamic compensation with elevated CBF may be insufficient to prevent gray matter volume loss in children and adolescents and decline in working memory ability. Some limitations of the current study include small sample size and whole brain gray and white matter volumes as opposed to specific regions relevant to executive functions (e.g., prefrontal cortex); however, findings from global measures provide promising evidence for future research on hemodynamic and structural predictors of executive function in SCA. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.


2020 ◽  
Vol 4 (s1) ◽  
pp. 45-46
Author(s):  
Carol Tran ◽  
Orit Glenn ◽  
Christopher Hess ◽  
Andreas Rauschecker

OBJECTIVES/GOALS: We seek to develop an automated deep learning-based method for segmentation and volumetric quantification of the fetal brain on T2-weighted fetal MRIs. We will evaluate the performance of the algorithm by comparing it to gold standard manual segmentations. The method will be used to create a normative sample of brain volumes across gestational ages. METHODS/STUDY POPULATION: We will adapt a U-Net convolutional neural network architecture for fetal brain MRIs using 3D volumes. After re-sampling 2D fetal brain acquisitions to 3mm3 3D volumes using linear interpolation, the network will be trained to perform automated brain segmentation on 40 randomly-sampled, normal fetal brain MRI scans of singleton pregnancies. Training will be performed in 3 acquisition planes (axial, coronal, sagittal). Performance will be evaluated on 10 test MRIs (in 3 acquisition planes, 30 total test samples) using Dice scores, compared to radiologists’ manual segmentations. The algorithm’s performance on measuring total brain volume will also be evaluated. RESULTS/ANTICIPATED RESULTS: Based on the success of prior U-net architectures for volumetric segmentation tasks in medical imaging (e.g. Duong et al., 2019), we anticipate that the convolutional neural network will accurately provide segmentations and associated volumetry of fetal brains in fractions of a second. We anticipate median Dice scores greater than 0.8 across our test sample. Once validated, the method will retrospectively generate a normative database of over 1500 fetal brain volumes across gestational ages (18 weeks to 30 weeks) collected at our institution. DISCUSSION/SIGNIFICANCE OF IMPACT: Quantitative estimates of brain volume, and deviations from normative data, would be a major advancement in objective clinical assessments of fetal MRI. Such data can currently only be obtained through laborious manual segmentations; automated deep learning methods have the potential to reduce the time and cost of this process.


2015 ◽  
Vol 145 (8) ◽  
pp. 1817-1823 ◽  
Author(s):  
Elske M Brouwer-Brolsma ◽  
Nikita L van der Zwaluw ◽  
Janneke P van Wijngaarden ◽  
Rosalie A Dhonukshe-Rutten ◽  
Paulette H in 't Veld ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teija Kujala ◽  
Aleksi J. Sihvonen ◽  
Anja Thiede ◽  
Peter Palo-oja ◽  
Paula Virtala ◽  
...  

AbstractDevelopmental dyslexia (DD) is the most prevalent neurodevelopmental disorder with a substantial negative influence on the individual’s academic achievement and career. Research on its neuroanatomical origins has continued for half a century, yielding, however, inconsistent results, lowered total brain volume being the most consistent finding. We set out to evaluate the grey matter (GM) volume and cortical abnormalities in adult dyslexic individuals, employing a combination of whole-brain voxel- and surface-based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing. Whilst controlling for age, sex, total intracranial volume, and performance IQ, we found both decreased GM volume and cortical thickness in the left insula in participants with DD. Moreover, they had decreased GM volume in left superior temporal gyrus, putamen, globus pallidus, and parahippocampal gyrus. Higher GM volumes and cortical thickness in these areas correlated with better reading and phonological skills, deficits of which are pivotal to DD. Crucially, total brain volume did not influence our results, since it did not differ between the groups. Our findings demonstrating abnormalities in brain areas in individuals with DD, which previously were associated with phonological processing, are compatible with the leading hypotheses on the neurocognitive origins of DD.


2019 ◽  
Vol 20 (7) ◽  
pp. 1744
Author(s):  
Danni Li ◽  
Jeffrey Misialek ◽  
Clifford Jack ◽  
Michelle Mielke ◽  
David Knopman ◽  
...  

Background: Plasma metabolites are associated with cognitive and physical function in the elderly. Because cerebral small vessel disease (SVD) and neurodegeneration are common causes of cognitive and physical function decline, the primary objective of this study was to investigate the associations of six plasma metabolites (two plasma phosphatidylcholines [PCs]: PC aa C36:5 and PC aa 36:6 and four sphingomyelins [SMs]: SM C26:0, SM [OH] C22:1, SM [OH] C22:2, SM [OH] C24:1) with magnetic resonance imaging (MRI) features of cerebral SVD and neurodegeneration in older adults. Methods: This study included 238 older adults in the Atherosclerosis Risk in Communities study at the fifth exam. Multiple linear regression was used to assess the association of each metabolite (log-transformed) in separate models with MRI measures except lacunar infarcts, for which binary logistic regression was used. Results: Higher concentrations of plasma PC aa C36:5 had adverse associations with MRI features of cerebral SVD (odds ratio of 1.69 [95% confidence interval: 1.01, 2.83] with lacunar infarct, and beta of 0.16 log [cm3] [0.02, 0.30] with log [White Matter Hyperintensities (WMH) volume]) while higher concentrations of 3 plasma SM (OH)s were associated with higher total brain volume (beta of 12.0 cm3 [5.5, 18.6], 11.8 cm3 [5.0, 18.6], and 7.3 cm3 [1.2, 13.5] for SM [OH] C22:1, SM [OH] C22:2, and SM [OH] C24:1, respectively). Conclusions: This study identified associations between certain plasma metabolites and brain MRI measures of SVD and neurodegeneration in older adults, particularly higher SM (OH) concentrations with higher total brain volume.


2021 ◽  
Author(s):  
Teija Kujala ◽  
Aleksi Sihvonen ◽  
Anja Thiede ◽  
Peter Palo-Oja ◽  
Paula Virtala ◽  
...  

Abstract Developmental dyslexia (DD) is the most prevalent neurodevelopmental disorder with a substantial negative influence on the individual’s academic achievement and career. Research on its neuroanatomical origins has continued for half a century, yielding, however, inconsistent results, lowered total brain volume being the most consistent finding. We set out to evaluate the grey matter (GM) volume and cortical abnormalities in adult dyslexic individuals, employing a combination of whole-brain voxel- and surface-based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing. Whilst controlling for age, sex, total intracranial volume, and performance IQ, we found both decreased GM volume and cortical thickness in the left insula in participants with DD. Moreover, they had decreased GM volume in left superior temporal gyrus, putamen, globus pallidus, and parahippocampal gyrus. Higher GM volumes and cortical thickness in these areas correlated with better reading and phonological skills, deficits of which are pivotal to DD. Crucially, total brain volume did not influence our results, since it did not differ between the groups. Our findings demonstrating abnormalities in brain areas in individuals with DD, which previously were associated with phonological processing, are compatible with the leading hypotheses on the neurocognitive origins of DD.


2019 ◽  
Author(s):  
SR Cox ◽  
SJ Ritchie ◽  
C Fawns-Ritchie ◽  
EM Tucker-Drob ◽  
IJ Deary

AbstractThe associations between indices of brain structure and measured intelligence are not clear. In part, this is because the evidence to date comes from mostly small and heterogenous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall N = 29,004, with N = 18,363 participants providing both brain MRI and cognitive data, and a minimum N = 7318 providing the MRI data alongside a complete four-test battery. Participants’ age range was 44-81 years (M = 63.13, SD = 7.48). A general factor of intelligence (g) was extracted from four varied cognitive tests, accounting for one third of the variance in the cognitive test scores. The association between (age-and sex-corrected) total brain volume and a latent factor of general intelligence is r = 0.275, 95% C.I. = [0.252, 0.299]. A model that incorporated multiple global measures of grey and white matter macro-and microstructure accounted for more than double the g variance in older participants compared to those in middle-age (13.4% and 5.9%, respectively). There were no sex differences in the magnitude of associations between g and total brain volume or other global aspects of brain structure. The largest brain regional correlates of g were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices, thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor.


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