Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936.

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (ß = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (ß = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (ß = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (ß = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (ß = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (ß = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (ß = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.

Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI.

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Are neuropsychiatric symptoms a marker of small vessel disease progression in older adults? Evidence from the Lothian Birth Cohort 1936.

BACKGROUND: Neuropsychiatric symptoms could form part of an early cerebral small vessel disease prodrome that is detectable before stroke or dementia onset. We aimed to identify whether apathy, depression, anxiety, and subjective memory complaints associate with longitudinal white matter hyperintensity (WMH) progression. METHODS: Community-dwelling older adults from the observational Lothian Birth Cohort 1936 attended three visits at mean ages 73, 76, and 79 years, repeating MRI, Mini-Mental State Examination, neuropsychiatric (Dimensional Apathy Scale, Hospital Anxiety and Depression Scale), and subjective memory symptoms. We ran regression and mixed-effects models for symptoms and normalised WMH volumes (cube root of WMH:ICV × 10). RESULTS: At age 73, 76, and 79, m = 672, n = 476, and n = 382 participants attended MRI respectively. Worse apathy at age 79 was associated with WMH volume increase (ß = 0.27, p = 0.04) in the preceding 6 years. A 1SD increase in apathy score at age 79 associated with a 0.17 increase in WMH (ß = 0.17 normalised WMH percent ICV, p = 0.009). In apathy subscales, executive (ß = 0.13, p = 0.05) and emotional (ß = 0.13, p = 0.04) scores associated with increasing WMH more than initiation scores (ß = 0.11, p = 0.08). Increasing WMH also associated with age (ß = 0.40, p = 0.002) but not higher depression (ß = -0.01, p = 0.78), anxiety (ß = 0.05, p = 0.13) scores, or subjective memory complaints (ß = 1.12, p = 0.75). CONCLUSIONS: Apathy independently associates with preceding longitudinal WMH progression, while depression, anxiety, and subjective memory complaints do not. Patients with apathy should be considered for enrolment to small vessel disease trials.

Coupled changes in brain white matter microstructure and fluid intelligence in later life.

Understanding aging-related cognitive decline is of growing importance in aging societies, but relatively little is known about its neural substrates. Measures of white matter microstructure are known to correlate cross-sectionally with cognitive ability measures, but only a few small studies have tested for longitudinal relations among these variables. We tested whether there were coupled changes in brain white matter microstructure indexed by fractional anisotropy (FA) and three broad cognitive domains (fluid intelligence, processing speed, and memory) in a large cohort of human participants with longitudinal diffusion tensor MRI and detailed cognitive data taken at ages 73 years (n = 731) and 76 years (n = 488). Longitudinal changes in white matter microstructure were coupled with changes in fluid intelligence, but not with processing speed or memory. Individuals with higher baseline white matter FA showed less subsequent decline in processing speed. Our results provide evidence for a longitudinal link between changes in white matter microstructure and aging-related cognitive decline during the eighth decade of life. They are consistent with theoretical perspectives positing that a corticocortical "disconnection" partly explains cognitive aging.

Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects.

BACKGROUND AND PURPOSE: We assessed cross-sectional and longitudinal relationships between whole brain white matter hyperintensity (WMH) volume and regional cortical thickness. METHODS: We measured WMH volume and regional cortical thickness on magnetic resonance imaging at ≈73 and ≈76 years in 351 community-dwelling subjects from the Lothian Birth Cohort 1936. We used multiple linear regression to calculate cross-sectional and longitudinal associations between regional cortical thickness and WMH volume controlling for age, sex, Mini Mental State Examination, education, intelligence quotient at age 11, and vascular risk factors. RESULTS: We found cross-sectional associations between WMH volume and cortical thickness within and surrounding the Sylvian fissure at 73 and 76 years (rho=-0.276, Q=0.004). However, we found no significant longitudinal associations between (1) baseline WMH volume and change in cortical thickness; (2) baseline cortical thickness and change in WMH volume; or (3) change in WMH volume and change in cortical thickness. CONCLUSIONS: Our results show that WMH volume and cortical thinning both worsen with age and are associated cross-sectionally within and surrounding the Sylvian fissure. However, changes in WMH volume and cortical thinning from 73 to 76 years are not associated longitudinally in these relatively healthy older subjects. The underlying cause(s) of WMH growth and cortical thinning have yet to be fully determined.

Beyond a bigger brain: Multivariable structural brain imaging and intelligence.

People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in their seventies (n = 672) who were administered a comprehensive cognitive test battery. Using structural equation modelling, we related six common magnetic resonance imaging-derived brain variables that represent normal and abnormal features-brain volume, cortical thickness, white matter structure, white matter hyperintensity load, iron deposits, and microbleeds-to g and to fluid intelligence. As expected, brain volume accounted for the largest portion of variance (~ 12%, depending on modelling choices). Adding the additional variables, especially cortical thickness (+~ 5%) and white matter hyperintensity load (+~ 2%), increased the predictive value of the model. Depending on modelling choices, all neuroimaging variables together accounted for 18-21% of the variance in intelligence. These results reveal which structural brain imaging measures relate to g over and above the largest contributor, total brain volume. They raise questions regarding which other neuroimaging measures might account for even more of the variance in intelligence.

Potential effect of skull thickening on the associations between cognition and brain atrophy in ageing.

BACKGROUND: intracranial volume (ICV) is commonly used as a marker of premorbid brain size in neuroimaging studies as it is thought to remain fixed throughout adulthood. However, inner skull table thickening would encroach on ICV and could mask actual brain atrophy. OBJECTIVE: we investigated the effect that thickening might have on the associations between brain atrophy and cognition. METHODS: the sample comprised 57 non-demented older adults who underwent structural brain MRI at mean age 72.7 ± 0.7 years and were assessed on cognitive ability at mean age 11 and 73 years. Principal component analysis was used to derive factors of general cognitive ability (g), information processing speed and memory from the recorded cognitive ability data. The total brain tissue volume and ICV with (estimated original ICV) and without (current ICV) adjusting for the effects of inner table skull thickening were measured. General linear modelling was used to test for associations. RESULTS: all cognitive ability variables were significantly (P < 0.01) associated with percentage total brain volume in ICV measured without adjusting for skull thickening (g: η(2) = 0.177, speed: η(2) = 0.264 and memory: η(2) = 0.132). After accounting for skull thickening, only speed was significantly associated with percentage total brain volume in ICV (η(2) = 0.085, P = 0.034), not g or memory. CONCLUSIONS: not accounting for skull thickening when computing ICV can distort the association between brain atrophy and cognitive ability in old age. Larger samples are required to determine the true effect.

ADRB2, brain white matter integrity and cognitive ageing in the Lothian Birth Cohort 1936.

The non-synonymous mutations arg16gly (rs1042713) and gln27glu (rs1042714) in the adrenergic ß-2 receptor gene (ADRB2) have been associated with cognitive function and brain white matter integrity. The current study aimed to replicate these findings and expand them to a broader range of cognitive and brain phenotypes. The sample used is a community-dwelling group of older people, the Lothian Birth Cohort 1936. They had been assessed cognitively at age 11 years, and undertook further cognitive assessments and brain diffusion MRI tractography in older age. The sample size range for cognitive function variables was N = 686-765, and for neuroimaging variables was N = 488-587. Previously-reported findings with these genetic variants did not replicate in this cohort. Novel, nominally significant associations were observed; notably, the integrity of the left arcuate fasciculus mediated the association between rs1042714 and the Digit Symbol Coding test of information processing speed. No significant associations of cognitive and brain phenotypes with ADRB2 variants survived correction for false discovery rate. Previous findings may therefore have been subject to type 1 error. Further study into links between ADRB2, cognitive function and brain white matter integrity is required.

Life-course neighbourhood deprivation and brain structure in older adults: The Lothian Birth Cohort 1936.

Neighbourhood disadvantage may be associated with brain health but the importance at different stages of the life course is poorly understood. Utilizing the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and regional neuroimaging measures at age 73. We found that residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (ß=-0.06; SE=0.02; n=390) and grey matter volume (ß=-0.11; SE=0.03; n=390), thinner cortex (ß=-0.15; SE=0.06; n=379), and lower general white matter fractional anisotropy (ß=-0.19; SE=0.06; n=388). Regional analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower occupational social classes, the brain-neighbourhood associations were stronger, with the impact of neighbourhood deprivation accumulating across the life course. Our findings suggest that living in deprived neighbourhoods is associated with adverse brain morphologies, with occupational social class adding to the vulnerability.

Blood-based epigenome-wide analyses of cognitive abilities.

BACKGROUND: Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia. RESULTS: Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes. CONCLUSIONS: As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines.

BACKGROUND: Aging-related cognitive decline is a primary risk factor for Alzheimer's disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias. METHODS: Using structural and diffusion brain magnetic resonance imaging data from the UK Biobank (n = 8185; age range, 45-78 years), we examined aging of regional gray matter volumes (nodes) and white matter structural connectivity (edges) within 9 well-characterized networks of interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (n = 534; all 73 years of age), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function before and after controlling for early-life cognitive ability. RESULTS: In the UK Biobank, age differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = .420; |redges| = .583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In the Lothian Birth Cohort 1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the central executive network were disproportionately predictive of late-life cognitive function relative to the network's small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability. CONCLUSIONS: These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The central executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

Relationship between inferior frontal sulcal hyperintensities on brain MRI, ageing and cerebral small vessel disease.

Raised signal in cerebrospinal fluid (CSF) on fluid-attenuated inversion recovery (FLAIR) may indicate raised CSF protein or debris and is seen in inferior frontal sulci on routine MRI. To explore its clinical relevance, we assessed the association of inferior frontal sulcal hyperintensities (IFSH) on FLAIR with demographics, risk factors, and small vessel disease markers in three cohorts (healthy volunteers, n=44; mild stroke patients, n=105; older community-dwelling participants from Lothian birth cohort 1936, n=101). We collected detailed clinical data, scanned all subjects on the same 3T MRI scanner and 3-dimensional FLAIR sequence and developed a scale to rate IFSH. In adjusted analyses, the IFSH score increased with age (per 10-year increase; OR 1.69; 95% CI, 1.42-2.02), and perivascular spaces score in centrum semiovale in stroke patients (OR 1.73; 95% CI, 1.13-2.69). Since glymphatic CSF clearance declines with age and drains partially via the cribriform plate to the nasal lymphatics, IFSH on 3T MRI may be a non-invasive biomarker of altered CSF clearance and justifies further research in larger, more diverse samples.

Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3.

BACKGROUND: Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood-brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease.Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood-brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. SUMMARY: Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy.

Dietary patterns, cognitive function, and structural neuroimaging measures of brain aging.

OBJECTIVE: To examine the cross-sectional associations between dietary patterns and cognitive and neuroimaging indices of brain health concurrently in the same sample of healthy older adults. METHODS: Dietary patterns were derived from a 130-item food frequency questionnaire for 511 individuals in the Lothian Birth Cohort 1936 (mean age 79.3 ± 0.6 years). Composite scores for global cognitive function, visuospatial ability, processing speed, memory, and verbal ability were assessed. Brain volumes and white matter microstructure were assessed in participants (n = 358) who also underwent structural magnetic resonance imaging. RESULTS: A Mediterranean-style dietary pattern and a processed dietary pattern were identified using principal component analysis of food frequency questionnaire items. In fully-adjusted linear regression models, adherence to the Mediterranean-style pattern was associated with better verbal ability (ß = 0.121, P = 0.002). Associations with global cognitive function (ß = 0.094, P = 0.043), visuospatial ability (ß = 0.113, P = 0.019), and memory (ß = 0.105, P = 0.029) did not survive correction for multiple comparisons. Associations between the processed pattern and lower cognitive scores were attenuated by around 50% following adjustment for prior (childhood) cognitive ability; only an association with verbal ability remained (ß = -0.130, P = 0.001). Neither dietary pattern was associated with brain volumes or white matter microstructure. Specific Mediterranean diet features-green leafy vegetables and a low intake of red meat-were associated with better cognitive functioning. CONCLUSIONS: These observational findings suggest that adherence to a Mediterranean-style diet is associated with better cognitive functioning, but not better brain structural integrity, in older adults.

Cerebral small vessel disease genomics and its implications across the lifespan.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.

Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936.

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

Predictors of gait speed and its change over three years in community-dwelling older people.

We aimed to assess whether and how changes in brain volume and increases in white matter hyperintensity (WMH) volume over three years predict gait speed and its change independently of demographics, vascular risk factors and physical status. We analyzed 443 individuals from the Lothian Birth Cohort 1936, at mean age 73 and 76 years. Gait speed at age 76 was predicted by age, grip strength and body mass index at mean age 73, three-year brain volume decrease and WMH volume increase, explaining 26.1% of variance. Decline in gait speed to age 76 was predicted by the same five variables explaining 40.9% of variance. In both analyses, grip strength and body mass index explained the most variance. A clinically significant decline in gait speed (≥ 0.1 m/s per year) occurred in 24.4%. These individuals had more structural brain changes. Brain volume and WMH changes were independent predictors of gait dysfunction and its three-year change, but the impact of malleable physical factors such as grip strength or body mass index was greater.

Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume.

Fully characterizing age differences in the brain is a key task for combating aging-related cognitive decline. Using propensity score matching on 2 independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age of 92 years (n = 42) to very similar participants at mean age of 73 years (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in gray and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and general cognitive ability (tissue volumes and cortical thickness were not significant mediators in this analysis). These findings provide an unusual and valuable perspective on neurostructural aging, in which brains from the 8th and 10th decades of life differ widely despite the same cognitive, socioeconomic, and brain-volumetric starting points.

Brain white matter structure and information processing speed in healthy older age.

Cognitive decline, especially the slowing of information processing speed, is associated with normal ageing. This decline may be due to brain cortico-cortical disconnection caused by age-related white matter deterioration. We present results from a large, narrow age range cohort of generally healthy, community-dwelling subjects in their seventies who also had their cognitive ability tested in youth (age 11 years). We investigate associations between older age brain white matter structure, several measures of information processing speed and childhood cognitive ability in 581 subjects. Analysis of diffusion tensor MRI data using Tract-based Spatial Statistics (TBSS) showed that all measures of information processing speed, as well as a general speed factor composed from these tests (g speed), were significantly associated with fractional anisotropy (FA) across the white matter skeleton rather than in specific tracts. Cognitive ability measured at age 11 years was not associated with older age white matter FA, except for the g speed-independent components of several individual processing speed tests. These results indicate that quicker and more efficient information processing requires global connectivity in older age, and that associations between white matter FA and information processing speed (both individual test scores and g speed), unlike some other aspects of later life brain structure, are generally not accounted for by cognitive ability measured in youth.

3D shape analysis of the brain's third ventricle using a midplane encoded symmetric template model.

BACKGROUND: Structural changes of the brain's third ventricle have been acknowledged as an indicative measure of the brain atrophy progression in neurodegenerative and endocrinal diseases. To investigate the ventricular enlargement in relation to the atrophy of the surrounding structures, shape analysis is a promising approach. However, there are hurdles in modeling the third ventricle shape. First, it has topological variations across individuals due to the inter-thalamic adhesion. In addition, as an interhemispheric structure, it needs to be aligned to the midsagittal plane to assess its asymmetric and regional deformation. METHOD: To address these issues, we propose a model-based shape assessment. Our template model of the third ventricle consists of a midplane and a symmetric mesh of generic shape. By mapping the template's midplane to the individuals' brain midsagittal plane, we align the symmetric mesh on the midline of the brain before quantifying the third ventricle shape. To build the vertex-wise correspondence between the individual third ventricle and the template mesh, we employ a minimal-distortion surface deformation framework. In addition, to account for topological variations, we implement geometric constraints guiding the template mesh to have zero width where the inter-thalamic adhesion passes through, preventing vertices crossing between left and right walls of the third ventricle. The individual shapes are compared using a vertex-wise deformity from the symmetric template. RESULTS: Experiments on imaging and demographic data from a study of aging showed that our model was sensitive in assessing morphological differences between individuals in relation to brain volume (i.e. proxy for general brain atrophy), gender and the fluid intelligence at age 72. It also revealed that the proposed method can detect the regional and asymmetrical deformation unlike the conventional measures: volume (median 1.95ml, IQR 0.96ml) and width of the third ventricle. Similarity measures between binary masks and the shape model showed that the latter reconstructed shape details with high accuracy (Dice coefficient ≥0.9, mean distance 0.5mm and Hausdorff distance 2.7mm). CONCLUSIONS: We have demonstrated that our approach is suitable to morphometrical analyses of the third ventricle, providing high accuracy and inter-subject consistency in the shape quantification. This shape modeling method with geometric constraints based on anatomical landmarks could be extended to other brain structures which require a consistent measurement basis in the morphometry.