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Shenkin, S. D.

Publications and source records attributed to Shenkin, S. D..

3 recordsLinked to original sources

General and specific patterns of cortical gene expression as substrates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given genes expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|{beta}| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

neuroscience↗

Birth weight is associated with brain tissue volumes seven decades later, but not with age-associated changes to brain structure

Birth weight, an indicator of fetal growth, is associated with cognitive outcomes in early life and risk of metabolic and cardiovascular disease across the life course. Cognitive ability in early life is predictive of cognitive ability in later life. Brain health in older age, defined by MRI features, is associated with cognitive performance. However, little is known about how variation in normal birth weight impacts on brain structure in later life. In a community dwelling cohort of participants in their early seventies we tested the hypothesis that birthweight is associated with the following MRI features: total brain (TB), grey matter (GM) and normal appearing white matter (NAWM) volumes; whiter matter hyperintensity (WMH) volume; a general factor of fractional anisotropy (gFA) and peak width skeletonised mean diffusivity (PSMD) across the white matter skeleton. We also investigated the associations of birthweight with cortical surface area, volume and thickness. Birthweight was positively associated with TB, GM and NAWM volumes in later life ({beta} [≥] 0.194), and with regional cortical surface area but not gFA, PSMD, WMH volume, or cortical volume or thickness. These positive relationships appear to be explained by larger intracranial volume rather than by age-related tissue atrophy, and are independent of body height and weight in adulthood. This suggests that larger birthweight is linked to increased brain tissue reserve in older life, rather than a resilience to age-related changes in brain structure, such as tissue atrophy or WMH volume. Significance StatementCognitive brain ageing carries a high personal, societal and financial cost and understanding its developmental origins is important for identifying possible preventative strategies. In a sample of older participants from the Lothian Birth Cohort 1936 we were able to explore the neurobiological correlates of birth weight, which is indicative of the fetal experience. We find that higher birth weight is related to larger brain tissue volumes in later life, but does not modify the trajectory of age-related change. This suggests that early life growth confers preserved differentiation, rather than differential preservation with regards to brain reserve. That these effects are detectable into later life indicates that this variable may be valuable biomarker in the epidemiology of ageing.

neuroscience↗

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↗