Biology subjects

Cox, S. R.

Publications and source records attributed to Cox, S. R..

9 recordsLinked to original sources

bioRxiv2018

Hierarchical Complexity of the Adult Human Structural Connectome

The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.

systems biology↗

bioRxiv2018

Brain peak width of skeletonised mean diffusivity (PSMD), processing speed, and other cognitive domains

It is suggested that the brain's peak width of skeletonised water mean diffusivity (PSMD) is a neuro-biomarker of processing speed, a crucial contributor to cognitive ageing. We tested whether PSMD is more strongly correlated with processing speed than with other cognitive domains, and more strongly than other structural brain MRI indices. Participants were 731 Lothian Birth Cohort 1936 members, mean age 73 years (SD=0.7); analytical sample was 656-680. Cognitive domains tested were: processing speed (5 tests), visuospatial (3), memory (3), and verbal (3). Brain-imaging variables included PSMD, white matter diffusion parameters and hyperintensity volumes, grey and white matter volumes, and perivascular spaces. PSMD was significantly associated with all processing speed tests; absolute standardised beta values were 0.11 to 0.23 (mean = 0.17). Other structural brain-imaging variables correlated as or more strongly. PSMD was significantly associated with processing speed (-0.27), visuospatial (-0.23), memory (-0.17), and general cognitive ability (-0.25). PSMD correlated with processing speed: but not more strongly than with other cognitive domains; and not more strongly than other brain-imaging measures.

neuroscience↗

bioRxiv2018

Polygenic predictors of age-related decline in cognitive ability

Polygenic scores can be used to distil the knowledge gained in genome-wide association studies for prediction of health, lifestyle, and environmental factors in independent samples. In this preregistered study, we used fourteen polygenic scores to predict variation in cognitive ability level at age 70 and cognitive change from age 70 to age 79 in the longitudinal Lothian Birth Cohort 1936 study. The polygenic scores were created for phenotypes that have been suggested as risk or protective factors for cognitive ageing. Cognitive abilities within old age were indexed using a latent general factor estimated from thirteen varied cognitive tests taken at four waves, each three years apart (initial n = 1,091 age 70; final n = 550 age 79). The general factor indexed over two-thirds of the variance in longitudinal cognitive change. We also ran an additional analysis using an age-11 intelligence test to index cognitive change from age 11 to age 70. Several polygenic scores were associated with the level of cognitive ability at age-70 baseline (range of standardized {beta}-values = -178 to .264), and the score for education was associated with cognitive change from childhood to age 70 (standardized = .102). None was statistically significantly associated with variation in cognitive change between ages 70 and 79. APOE e4 status made a significant prediction of cognitive decline from age 70 to 79 (standardized {beta} = -319 for carriers vs. non-carriers). The results suggest that the predictive validity for cognitive ageing of polygenic scores derived from genome-wide association study summary statistics is not yet on a par with APOE e4, a more well-established predictor.

genomics↗

bioRxiv2017

Is there association between APOE e4 genotype and structural brain ageing phenotypes, and does that association increase in older age in UK Biobank? (N = 8,395)

Apolipoprotein (APOE) e4 genotype is a purported risk factor for accelerated cognitive ageing and dementia, though its neurostructural substrates are unclear. The deleterious effects of this genotype on brain structure may increase in magnitude into older age. This study aimed to investigate in UK Biobank the association between APOE e4 allele presence vs. absence and brain imaging variables that have been associated with worse cognitive abilities; and whether this association varies by cross-sectional age. We used brain magnetic resonance imaging (MRI) and genetic data from a general-population cohort: the UK Biobank (N=8,395). We adjusted for the covariates of age in years, sex, Townsend social deprivation scores, smoking history and cardiometabolic diseases. There was a statistically significant association between APOE e4 genotype and increased (i.e. worse) white matter (WM) hyperintensity volumes (standardised beta = 0.088, 95 confidence intervals = 0.036 to 0.139, P = 0.001), a marker of poorer cerebrovascular health. There were no associations with left or right hippocampal, total grey matter (GM) or WM volumes, or WM tract integrity indexed by fractional anisotropy (FA) and mean diffusivity (MD). There were no statistically significant interactions with age. Future research in UK Biobank utilising intermediate phenotypes and longitudinal imaging hold significant promise for this area, particularly pertaining to APOE e4s potential link with cerebrovascular contributions to cognitive ageing.

genetics↗

bioRxiv2017

Resting-state connectivity and its association with cognitive performance, educational attainment, and household income in UK Biobank (N = 3,950)

Cognitive ability is an important predictor of lifelong physical and mental well-being and its impairments are associated with many psychiatric disorders. Higher cognitive ability is also associated with greater educational attainment and increased household income. Understanding neural mechanisms underlying cognitive ability is therefore of crucial importance for determining the nature of these associations. In the current study, we examined the spontaneous activity of the brain at rest to investigate its relationships with not only cognitive ability, but also educational attainment and household income. We used a large sample of resting-state neuroimaging data from UK Biobank (N=3,950). Firstly, analysis at the whole-brain level showed that connections involving the default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON) were significantly positively associated with levels of cognitive performance assessed by a verbal-numerical reasoning test (standardised {beta} ranged from 0.054 to 0.097). Connections associated with higher levels of cognitive performance were also significantly positively associated with educational attainment (r=0.48, N=4,160) and household income (r=0.38, N=3,793). Further, analysis on the coupling of functional networks showed that better cognitive performance was associated with more positive DMN-CON connections, decreased cross-hemisphere connections between homotopic network in CON and FPN, and stronger CON-FPN connections (absolute {beta} ranged from 0.034 to 0.063). The present study finds that variation in brain resting state functional connectivity associated with individual differences in cognitive ability, largely involving DMN and lateral prefrontal networks. Additionally, we provide further evidence of shared neural associations of cognitive ability, educational attainment, and household income.

neuroscience↗

bioRxiv2017

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 combatting ageing-related cognitive decline. Using propensity score matching on two independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age 92 years (n = 42) to very similar participants at mean age 73 (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in grey 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 ageing, in which brains from the eighth and tenth decades of life differ widely despite the same cognitive, socio-economic, and brain-volumetric starting points.

neuroscience↗

bioRxiv2017

Sex Differences In The Adult Human Brain: Evidence From 5,216 UK Biobank Participants

Sex differences in the human brain are of interest, for example because of sex differences in the observed prevalence of psychiatric disorders and in some psychological traits. We report the largest single-sample study of structural and functional sex differences in the human brain (2,750 female, 2,466 male participants; 44-77 years). Males had higher volumes, surface areas, and white matter fractional anisotropy; females had thicker cortices and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume or height. There was generally greater male variance across structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

neuroscience↗

bioRxiv2017

Improving data availability for brain image biobanking in healthy subjects: practice-based suggestions from an international multidisciplinary working group

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining normality); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function.

neuroscience↗

bioRxiv2017

Genetic contributions to trail making test performance in UK Biobank

The Trail Making Test is a widely used test of executive function and has been thought to be strongly associated with general cognitive function. We examined the genetic architecture of the trail making test and its shared genetic aetiology with other tests of cognitive function in 23 821 participants from UK Biobank. The SNP-based heritability estimates for trail-making measures were 7.9 % (part A), 22.4 % (part B), and 17.6 % (part B - part A). Significant genetic correlations were identified between trail-making measures and verbal-numerical reasoning (rg > 0.6), general cognitive function (rg > 0.6), processing speed (rg > 0.7), and memory (rg > 0.3). Polygenic profile analysis indicated considerable shared genetic aetiology between trail making, general cognitive function, processing speed, and memory (standardized {beta} between 0.03 and 0.08). These results suggest that trail making is both phenotypically and genetically strongly associated with general cognitive function and processing speed.

genetics↗