SOCIOECONOMIC AND DEMOGRAPHIC INFLUENCES ON WHITE MATTER HYPERINTENSITY BURDEN IN THE UNITED KINGDOM: DATA FROM UK BIOBANK

Abstract Apolipoprotein (APOE) e4 genotype is an accepted risk factor for accelerated cognitive aging 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 = 8395 after exclusions). 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 e4’s potential link with cerebrovascular contributions to cognitive aging.

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Interactions Between Age, Sex, Menopause, and Brain Structure at Midlife: A UK Biobank Study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgaa847 ◽

2020 ◽

Author(s):

Stephanie Than ◽

Chris Moran ◽

Richard Beare ◽

Amanda J Vincent ◽

Taya A Collyer ◽

...

Keyword(s):

White Matter ◽

Significant Interaction ◽

Menopausal Status ◽

Brain Magnetic Resonance Imaging ◽

White Matter Hyperintensity ◽

Imaging Biomarkers ◽

Inverse Association ◽

Uk Biobank ◽

Matter Volume ◽

Perimenopausal Women

Abstract Objectives Age and female sex are risk factors for dementia, and menopause is associated with cognitive dysfunction. Previous work largely considered the effects of sex and menopause as being independent of age. We studied whether age interacts with sex or menopause in explaining imaging biomarkers of dementia during midlife. Methods In this cross-sectional study of UK Biobank participants with brain magnetic resonance imaging (MRI), we explored the interaction of age with sex or menopausal status in explaining total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMHV), regional cortical volume , and subcortical volume. Results Data were available for 1827 postmenopausal women, 230 pre/perimenopausal women and 2165 men (median age 63.3 years). There was a significant interaction between age and sex (P = .024) for TBV, where the inverse association age with TBV was steeper in women (β = –5.35 mL/year) than in men (β = –4.77 mL/year). Similar age–sex interactions were also observed for GMV and WMV. In women, there was a significant interaction between age and menopausal status (P = .007) where the inverse association of age with TBV was steeper in postmenopausal (β = –5.89 mL/year) than in pre/perimenopausal women (β = –1.61 mL/year). Similar age–menopause interactions were found in predicting lower GMV and higher WMHV. Differences in the direction of these age–sex and age–menopause interactions were found for regional cortical and subcortical brain volumes. Conclusion Sex and menopause both interact with age during midlife in explaining MRI biomarkers of dementia. Further work is required to understand the mechanisms driving these interactions to develop strategies for delaying dementia.

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Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?

International Journal of Obesity ◽

10.1038/s41366-021-00891-6 ◽

2021 ◽

Author(s):

Stephen Clark ◽

Michelle Morris ◽

Nik Lomax ◽

Mark Birkin

Keyword(s):

Cohort Study ◽

United Kingdom ◽

Classification System ◽

Holistic Approach ◽

Data Driven ◽

Uk Biobank ◽

The United Kingdom ◽

The Individual ◽

The Uk

AbstractCOVID-19 is a disease that has been shown to have outcomes that vary by certain socio-demographic and socio-economic groups. It is increasingly important that an understanding of these outcomes should be derived not from the consideration of one aspect, but by a more multi-faceted understanding of the individual. In this study use is made of a recent obesity driven classification of participants in the United Kingdom Biobank (UKB) to identify trends in COVID-19 outcomes. This classification is informed by a recently created obesity systems map, and the COVID-19 outcomes are: undertaking a test, a positive test, hospitalisation and mortality. It is demonstrated that the classification is able to identify meaningful differentials in these outcomes. This more holistic approach is recommended for identification and prioritisation of COVID-19 risk and possible long-COVID determination.

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

NeuroImage ◽

10.1016/j.neuroimage.2021.118189 ◽

2021 ◽

pp. 118189

Author(s):

Valentina Bordin ◽

Ilaria Bertani ◽

Irene Mattioli ◽

Vaanathi Sundaresan ◽

Paul McCarthy ◽

...

Keyword(s):

White Matter ◽

Large Scale ◽

White Matter Hyperintensity ◽

Uk Biobank

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

10.1101/2020.07.28.208579 ◽

2020 ◽

Author(s):

Valentina Bordin ◽

Ilaria Bertani ◽

Irene Mattioli ◽

Vaanathi Sundaresan ◽

Paul McCarthy ◽

...

Keyword(s):

White Matter ◽

Large Scale ◽

White Matter Hyperintensity ◽

List Type ◽

Uk Biobank ◽

Physiological Variables ◽

Healthy Elderly ◽

Processing Strategies ◽

Wide Range ◽

The Uk

ABSTRACTLarge 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.HIGHLIGHTSWe harmonised measures of WMHs across two studies on healthy ageingSpecific pre-processing strategies can increase comparability across studiesModelling of biological differences is crucial to provide calibrated measures

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The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

10.2337/figshare.14096678.v1 ◽

2021 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

Cognitive Function ◽

White Matter ◽

Visual Memory ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

The Relationship ◽

Genetic Instruments

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

10.2337/figshare.14096678.v2 ◽

2021 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

Cognitive Function ◽

White Matter ◽

Visual Memory ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

The Relationship ◽

Genetic Instruments

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

10.2337/figshare.14096678 ◽

2021 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

Cognitive Function ◽

White Matter ◽

Visual Memory ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

The Relationship ◽

Genetic Instruments

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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Evidence of directional and stabilizing selection in contemporary humans

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1707227114 ◽

2017 ◽

Vol 115 (1) ◽

pp. 151-156 ◽

Cited By ~ 33

Author(s):

Jaleal S. Sanjak ◽

Julia Sidorenko ◽

Matthew R. Robinson ◽

Kevin R. Thornton ◽

Peter M. Visscher

Keyword(s):

United Kingdom ◽

Natural Selection ◽

Human Evolution ◽

Molecular Genetic ◽

Stabilizing Selection ◽

Uk Biobank ◽

The United Kingdom ◽

Health And Disease ◽

Linear And Nonlinear ◽

The Uk

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

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The relationship between glycaemia, cognitive function, structural brain outcomes and dementia: A Mendelian randomization study in the UK Biobank

10.1101/2020.05.07.20094110 ◽

2020 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

White Matter ◽

Visual Memory ◽

Hippocampal Volume ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

Inverse Variance ◽

Volume Coefficient

AbstractAimsTo investigate the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR).MethodsUK Biobank (n~500,000) individuals, aged 40-69 years at baseline. Our exposures were genetic instruments for type-2 diabetes (163 variants) and HbA1c (52 variants) and our outcomes were reaction time (RT - milliseconds), visual memory (number of incorrect responses), hippocampal and white matter hyperintensity volumes (both mm3), Alzheimer’s disease (AD). To study potential bidirectional effects, we then investigated the associations between genetic variants for RT (43 variants) and clinical type-2 diabetes and measured HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside standard MR sensitivity analyses.ResultsUsing IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (expß=0.98, 95%CI=0.93; 1.03), hippocampal volume (coefficient mm3=0.00, 95%CI=-0.01; 0.01) or risk of AD (OR 0.97, 95%CI=0.89; 1.06). HbA1c was not associated with reaction time (expß=1.01, 95%CI=1.00; 1.01), white matter hyperintensity volume (expß=0.88, 95%CI=0.73; 1.07), hippocampal volume (coefficient=-0.02, 95%CI=-0.10; 0.06), risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median approach. IVW showed no evidence that reaction time was associated with diabetes (OR 0.96, 95%CI=0.63; 1.46) or HbA1c (coefficient=-0.08, 95%CI=-0.57; 0.42). MR-Egger intercept p-values indicated no major issues with unbalanced horizontal pleiotropy (all p>0.05).ConclusionsOverall, we observed little evidence of causal associations between glycaemia and cognition, structural brain and dementia phenotypes.AbbreviationsAlzheimer’s dementia (AD)Benjamini-Hochberg false discovery rate (BH-FDR)Genome-wide association study (GWAS)Hippocampal volume (HV)Hospital episode statistics (HES)International Classification of Diseases (ICD)Inverse variance weighted (IVW)Magnetic resonance imaging (MRI)Mendelian randomization (MR)Quality control (QC)Reaction time (RT)Simulation extrapolation (SIMEX)UK Biobank (UKB)Visual memory (VM)Weighted median Estimator (WME)White matter hyperintensity volume (WMHV)

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