Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort

Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual residual fluid intelligence scores from cortical grey matter morphology

We predicted residual fluid intelligence scores from T1-weighted MRI data available as part of the ABCD NP Challenge 2019, using morphological similarity of grey-matter regions across the cortex. Individual structural covariance networks (SCN) were abstracted into graph-theory metrics averaged over nodes across the brain and in data-driven communities/modules. Metrics included degree, path length, clustering coefficient, centrality, rich club coefficient, and small-worldness. These features derived from the training set were used to build various regression models for predicting residual fluid intelligence scores, with performance evaluated both using cross-validation within the training set and using the held-out validation set. Our predictions on the test set were generated with a support vector regression model trained on the training set. We found minimal improvement over predicting a zero residual fluid intelligence score across the sample population, implying that structural covariance networks calculated from T1-weighted MR imaging data provide little information about residual fluid intelligence.Comment: 8 pages plus references, 3 figures, 2 tables. Submission to the ABCD Neurocognitive Prediction Challenge at MICCAI 201

Profiles of physical, emotional and psychosocial wellbeing in the Lothian birth cohort 1936

<p>Abstract</p> <p>Background</p> <p>Physical, emotional, and psychosocial wellbeing are important domains of function. The aims of this study were to explore the existence of separable groups among 70-year olds with scores representing physical function, perceived quality of life, and emotional wellbeing, and to characterise any resulting groups using demographic, personality, cognition, health and lifestyle variables.</p> <p>Methods</p> <p>We used latent class analysis (LCA) to identify possible groups.</p> <p>Results</p> <p>Results suggested there were 5 groups. These included High (n = 515, 47.2% of the sample), Average (n = 417, 38.3%), and Poor Wellbeing (n = 37, 3.4%) groups. The two other groups had contrasting patterns of wellbeing: one group scored relatively well on physical function, but low on emotional wellbeing (Good Fitness/ Low Spirits,n = 60, 5.5%), whereas the other group showed low physical function but relatively well emotional wellbeing (Low Fitness/Good Spirits, n = 62, 5.7%). Salient characteristics that distinguished all the groups included smoking and drinking behaviours, personality, and illness.</p> <p>Conclusions</p> <p>Despite there being some evidence of these groups, the results also support a largely one-dimensional construct of wellbeing in old age—for the domains assessed here—though with some evidence that some individuals have uneven profiles.</p

Early life characteristics and late life burden of cerebral small vessel disease in the Lothian Birth Cohort 1936

It is unknown whether relations between early-life factors and overall health in later life apply to burden of cerebral small vessel disease (cSVD), a major cause of stroke and dementia. We explored relations between early-life factors and cSVD in the Lothian Birth Cohort, a healthy aging cohort. Participants were recruited at age 70 (N = 1091); most had completed a test of cognitive ability at age 11 as part of the Scottish Mental Survey of 1947. Of those, 700 participants had brain MRI that could be rated for cSVD conducted at age 73. Presence of lacunes, white matter hyperintensities, microbleeds, and perivascular spaces were summed in a score of 0-4 representing all MRI cSVD features. We tested associations with early-life factors using multivariate logistic regression. Greater SVD score was significantly associated with lower age-11 IQ (OR higher SVD score per SD age-11 IQ = .78, 95%CI 0.65-.95, p=.01). The associations between SVD score and own job class (OR higher job class, .64 95%CI .43-.95, p=.03), age-11 deprivation index (OR per point deprivation score, 1.08, 95%CI 1.00-1.17, p=.04), and education (OR some qualifying education, .60 95%CI .37-.98, p=.04) trended towards significance (p<.05 for all) but did not meet thresholds for multiple testing. No early-life factor was significantly associated with any one individual score component. Early-life factors may contribute to age-73 burden of cSVD. These relations, and the potential for early social interventions to improve brain health, deserve further study

A protocol for precise comparisons of small vessel disease lesions between ex vivo magnetic resonance imaging and histopathology

pp. 310-32La neuroimagen y los estudios clínicos han definido la enfermedad cerebral de los vasos pequeños humanos, pero la fisiopatología sigue siendo relativamente poco comprendida. Para desarrollar terapias eficaces y estrategias preventivas, debemos comprender mejor la heterogeneidad y el desarrollo de la enfermedad de los vasos pequeños a nivel celular.S

Patterns and associates of cognitive function, psychosocial wellbeing and health in the Lothian Birth Cohort 1936

BACKGROUND: Cognitive function, psychosocial wellbeing and health are important domains of function. Consistencies and inconsistencies in patterns of wellbeing across these domains may be informative about wellbeing in old age and the ways it is manifested amongst individuals. In this study we investigated whether there were groups of individuals with different profiles of scores across these domains. We also aimed to identify characteristics of any evident groups by comparing them on variables that were not used in identifying the groups. METHODS: The sample was the Lothian Birth Cohort 1936, which included 1091 participants born in 1936. They are a community-dwelling, narrow-age-range sample of 70-year-olds. Most had taken part in the Scottish Mental Survey 1947 at an average age of 11, making available a measure of childhood intelligence. We used latent class analysis (LCA) to explore possible profiles using 9 variables indicating cognitive functioning, psychosocial wellbeing and health status. Demographic, personality, and lifestyle variables – none of which were used in the LCA – were used to characterize the resulting profile groups. RESULTS: We accepted a 3-group solution, which we labeled High Wellbeing (65.3%), Low Cognition (20.3%), and Low Bio-Psychosocial (14.5%). Notably, the High Wellbeing group had significantly higher childhood IQ, lower Neuroticism scores, and a lower percentage of current smokers than the other 2 groups. CONCLUSION: The majority of individuals were functioning generally well; however, there was evidence of the presence of groups with different profiles, which may be explained in part in terms of cognitive ability differences. Results suggested that higher life-long intelligence, personality traits associated with less mental distress, and basic health practices such as avoiding smoking are important associates of wellbeing in old age

DNA methylation and the epigenetic clock in relation to physical frailty in older people:The Lothian Birth Cohort 1936

Background: The biological mechanisms underlying frailty in older people are poorly understood. There is some evidence to suggest that DNA methylation patterns may be altered in frail individuals. Methods: Participants were 791 people aged 70 years from the Lothian Birth Cohort 1936. DNA methylation was measured in whole blood. Biological age was estimated using two measures of DNA methylation-based age acceleration - extrinsic and intrinsic epigenetic age acceleration. We carried out an epigenome-wide association study of physical frailty, as defined by the Fried phenotype. Multinomial logistic regression was used to calculate relative risk ratios for being physically frail or pre-frail according to epigenetic age acceleration. Results: There was a single significant (P=1.16x10-7) association in the epigenome-wide association study comparing frail versus not frail. The same CpG was not significant when comparing pre-frail versus not frail. Greater extrinsic epigenetic age acceleration was associated with an increased risk of being physically frail, but not of being pre-frail. For a year increase in extrinsic epigenetic age acceleration, age- and sex-adjusted relative risk ratios (95% CI) for being physically frail or pre-frail were 1.06 (1.02, 1.10) and 1.02 (1.00, 1.04) respectively. After further adjustment for smoking and chronic disease, the association with physical frailty remained significant. Intrinsic epigenetic age acceleration was not associated with physical frailty status.Conclusions: People who are biologically older, as indexed by greater extrinsic epigenetic age acceleration, are more likely to be physically frail. Future research will need to investigate whether epigenetic age acceleration plays a causal role in the onset of physical frailty

Using Extended Genealogy to Estimate Components of Heritability for 23 Quantitative and Dichotomous Traits

Important knowledge about the determinants of complex human phenotypes can be obtained from the estimation of heritability, the fraction of phenotypic variation in a population that is determined by genetic factors. Here, we make use of extensive phenotype data in Iceland, long-range phased genotypes, and a population-wide genealogical database to examine the heritability of 11 quantitative and 12 dichotomous phenotypes in a sample of 38,167 individuals. Most previous estimates of heritability are derived from family-based approaches such as twin studies, which may be biased upwards by epistatic interactions or shared environment. Our estimates of heritability, based on both closely and distantly related pairs of individuals, are significantly lower than those from previous studies. We examine phenotypic correlations across a range of relationships, from siblings to first cousins, and find that the excess phenotypic correlation in these related individuals is predominantly due to shared environment as opposed to dominance or epistasis. We also develop a new method to jointly estimate narrow-sense heritability and the heritability explained by genotyped SNPs. Unlike existing methods, this approach permits the use of information from both closely and distantly related pairs of individuals, thereby reducing the variance of estimates of heritability explained by genotyped SNPs while preventing upward bias. Our results show that common SNPs explain a larger proportion of the heritability than previously thought, with SNPs present on Illumina 300K genotyping arrays explaining more than half of the heritability for the 23 phenotypes examined in this study. Much of the remaining heritability is likely to be due to rare alleles that are not captured by standard genotyping arrays

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

&lt;p&gt;Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.&lt;/p&gt; &lt;p&gt;Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.&lt;/p&gt; &lt;p&gt;Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p&#60;5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.&lt;/p&gt; &lt;p&gt;Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.&lt;/p&gt

Failure of Working Memory Training to Enhance Cognition or Intelligence

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.National Institutes of Health (U.S.) (Blueprint for Neuroscience Research (T90DA022759/R90DA023427)United States. Defense Advanced Research Projects Agency (government contract no. NBCHC070105)United States. Dept. of Defense (National Defense Science and Engineering Fellowship)Massachusetts Institute of Technology (Sheldon Razin (1959) Fellowship