Biology subjects

Suri, S.

Publications and source records attributed to Suri, S..

10 recordsLinked to original sources

bioRxiv2023

The association of longitudinal diet and waist-to-hip ratio from midlife to old age with hippocampus connectivity and memory in old age: a cohort study

Epidemiological studies suggest lifestyle factors may reduce the risk of dementia. However, few studies have examined the association of diet and waist-to-hip ratio with hippocampus connectivity. In the Whitehall II Imaging Sub-study, we examined longitudinal changes in diet quality in 512 participants and waist-to-hip ratio in 665 participants. Diet quality was measured using the Alternative Health Eating Index-2010 assessed three times across 11 years between ages 48 and 60 years, and waist-to-hip ratio five times over 21 years between ages 48 and 68 years. Brain imaging and cognitive tests were performed at age 70{+/-}5 years. We measured white matter using diffusion tensor imaging and hippocampal functional connectivity using resting-state functional magnetic resonance imaging. In addition to associations of diet and waist-to-hip ratio with brain imaging measures, we tested whether associations between diet, waist-to-hip ratio and cognitive performance were mediated by brain connectivity. We found better diet quality in midlife and improvements in diet over mid-to-late life were associated with higher hippocampal functional connectivity to the occipital lobe and cerebellum, and better white matter integrity as measured by higher fractional anisotropy and lower diffusivity. Higher waist-to-hip ratio in midlife was associated with higher mean and radial diffusivity and lower fractional anisotropy in several tracts including the inferior longitudinal fasciculus and cingulum. Associations between midlife waist-to-hip ratio, working memory and executive function were partially mediated by radial diffusivity. All associations were independent of age, sex, education, and physical activity. Our findings highlight the importance of maintaining a good diet and a healthy waist-to-hip ratio in midlife to maintain brain health in later life. Future interventional studies for the improvement of dietary and metabolic health should target midlife for the prevention of cognitive decline in old age.

neuroscience↗

bioRxiv2021

Individual variation in brain microstructural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52{+/-} 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 {+/-}4.9 years) and late-life (mean age = 67.7 {+/-}4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 {+/-}4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions that are both positively and negatively associated with cortical structure.

neuroscience↗

bioRxiv2021

Brain age relates to early life factors but not to accelerated brain aging

Brain age is a widely used index for quantifying individuals brain health as deviation from a normative brain aging trajectory. Higher than expected brain age is thought partially to reflect above-average rate of brain aging. We explicitly tested this assumption in two large datasets and found no association between cross-sectional brain age and steeper brain decline measured longitudinally. Rather, brain age in adulthood was associated with early-life influences indexed by birth weight and polygenic scores. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.

neuroscience↗

bioRxiv2020

Education and income show heterogeneous relationships to lifespan brain and cognitive differences across European and US cohorts

Socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. Here we show that relationships between SES, brain volumes and general cognitive ability differ significantly across European and US cohorts (4-97 years, N {approx} 500,000; 54,000 with brain imaging). Education was positively related to intracranial (ICV) and total brain gray matter (GM) volume. Income was related to ICV, but not GM. Relationships varied significantly across samples, and SES was more strongly related to brain and cognition in US than European cohorts. Differences in neuroanatomical volumes explained part of the SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. Rather, a relationship may be established early in life. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

neuroscience↗

bioRxiv2020

Integrating large-scale neuroimaging research datasets: harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

Large scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise sample differences contributing to study-level differences in WMH variations. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data. HIGHLIGHTSO_LIWe harmonised measures of WMHs across two studies on healthy ageing C_LIO_LISpecific pre-processing strategies can increase comparability across studies C_LIO_LIModelling of biological differences is crucial to provide calibrated measures C_LI

neuroscience↗

bioRxiv2020

History of childbirths relates to region-specific brain aging patterns in middle and older-aged women

Pregnancy involves maternal brain adaptations, but little is known about how parity influences womens brain aging trajectories later in life. In this study, we replicated previous findings showing less apparent brain aging in women with a history of childbirths, and identified regional brain aging patterns linked to parity in 19,787 middle and older-aged women. Using novel applications of brain-age prediction methods, we found that a higher number of previous childbirths was linked to less apparent brain aging in striatal and limbic regions. The strongest effect was found in the accumbens - a key region in the mesolimbic reward system, which plays an important role in maternal behavior. While only prospective longitudinal studies would be conclusive, our findings indicate that subcortical brain modulations during pregnancy and postpartum may be traceable decades after childbirth.

neuroscience↗

bioRxiv2020

Self-reported sleep problems are related to cortical thinning in aging but not memory decline and amyloid-β accumulation - results from the Lifebrain consortium

BackgroundOlder persons with poor sleep are more likely to develop neurodegenerative disease, but the causality underlying this association is unclear. To move towards explanation, we examine whether sleep quality and quantity are similarly associated with brain changes across the adult lifespan. MethodsAssociations between self-reported sleep parameters (Pittsburgh Sleep Quality Index;PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n=2205, 4363 MRIs, 18-92 years). Analyses were augmented by considering episodic memory change, gene expression from the Allen Human Brain Atlas, and amyloid-beta (A{beta}) accumulation (n=1980). ResultsPSQI components sleep problems and low sleep quality were related to thinning of the right lateral temporal cortex. The association with sleep problems emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. BMI and symptoms of depression had negligible effects. Sleep problems were neither related to longitudinal change in episodic memory function nor to A{beta} accumulation, suggesting that sleep-related cortical changes were independent of AD neuropathology and cognitive decline. ConclusionWorse self-reported sleep in later adulthood was associated with more cortical thinning in regions of high expression of genes related to oligodendrocytes and S1 pyramidal neurons, but not to A{beta} accumulation or memory decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes, except for a few restricted regions, indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

neuroscience↗

bioRxiv2020

Mid-life and late life activities and their relationship with MRI measures of brain structure and functional connectivity in the UK Biobank cohort

INTRODUCTIONThis study aimed to evaluate whether mid-life and late life participation in leisure activities is linked to measures of brain structure, functional connectivity and cognition in early old age. METHODSWe examined data collected from 7,152 participants of the UK Biobank study. Weekly participation in six leisure activities was assessed twice. A cognitive battery and 3T MRI brain scan were administered at the second visit. RESULTSWeekly computer use at mid-life associated with larger volumes of the left putamen and higher scores for fluid intelligence, alphanumeric and numeric trail making tasks and prospective memory. Frequent attendance at a sports club or gym at mid-life was associated with stronger connectivity of the sensorimotor network with the lateral visual and cerebellar networks. No other associations were significant. DISCUSSIONThis study demonstrates that not all leisure activities contribute to cognitive health equally, nor is there one unifying neural signature across leisure activities.

neuroscience↗

bioRxiv2020

Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study

Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II MRI cohort using machine learning and imaging-derived measures of gray matter morphology, diffusion-based white matter microstructure, and resting state functional connectivity. Ten-fold cross validation yielded multimodal and modality-specific brain age estimates for each participant, and additional predictions based on a separate training sample was included for comparison. The results showed equivalent age prediction accuracy between the multimodal model and the gray and white matter models (R2 of 0.34, 0.31, and 0.31, respectively), while the functional connectivity model showed a lower prediction accuracy (R2 of 0.01). Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with more apparent brain aging, with consistent associations across modalities.

neuroscience↗

bioRxiv2019

Self-reported sleep relates to hippocampal atrophy across the adult lifespan - results from the Lifebrain consortium

BackgroundPoor sleep is associated with multiple age-related neurodegenerative and neuropsychiatric conditions. The hippocampus plays a special role in sleep and sleep-dependent cognition, and accelerated hippocampal atrophy is typically seen with higher age. Hence, it is critical to establish how the relationship between sleep and hippocampal volume loss unfolds across the adult lifespan.\n\nMethodsSelf-reported sleep measures and MRI-derived hippocampal volumes were obtained from 3105 cognitively normal participants (18-90 years) from major European brain studies in the Lifebrain consortium. Hippocampal volume change was estimated from 5116 MRIs from 1299 participants, covering up to 11 years. Cross-sectional analyses were repeated in a sample of 21390 participants from the UK Biobank.\n\nResultsThe relationship between self-reported sleep and age differed across sleep items. Sleep duration, efficiency, problems, and use of medication worsened monotonously with age, whereas subjective sleep quality, sleep latency, and daytime tiredness improved. Women reported worse sleep in general than men, but the relationship to age was similar. No cross-sectional sleep - hippocampal volume relationships was found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing on average 0.22% greater annual loss than low scorers. Simulations showed that longitudinal effects were too small to be detected as age-interactions in cross-sectional analyses.\n\nConclusionsWorse self-reported sleep is associated with higher rates of hippocampal decline across the adult lifespan. This suggests that sleep is relevant to understand individual differences in hippocampal atrophy, but limited effect sizes call for cautious interpretation.

neuroscience↗