scholarly journals Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference

2018 ◽  
Author(s):  
Vaanathi Sundaresan ◽  
Ludovica Griffanti ◽  
Petya Kindalova ◽  
Fidel Alfaro-Almagro ◽  
Giovanna Zamboni ◽  
...  
Keyword(s):  
White Matter ◽  
Vascular Disease ◽  
White Matter Hyperintensities ◽  
Age Groups ◽  
Clinical Importance ◽  
Population Level ◽  
Distribution Model ◽  
Ageing Population ◽  
Uk Biobank ◽  
The Uk

AbstractWhite matter hyperintensities (WMH), also known as white matter lesions, are localised white matter areas that appear hyperintense on MRI scans. WMH commonly occur in the ageing population, and are often associated with several factors such as cognitive disorders, cardiovascular risk factors, cerebrovascular and neurodegenerative diseases. Despite the fact that some links between lesion location and parametric factors such as age have already been established, the relationship between voxel-wise spatial distribution of lesions and these factors is not yet well understood. Hence, it would be of clinical importance to model the distribution of lesions at the population-level and quantitatively analyse the effect of various factors on the lesion distribution model.In this work we compare various methods, including our proposed method, to generate voxel-wise distributions of WMH within a population with respect to various factors. Our proposed Bayesian spline method models the spatio-temporal distribution of WMH with respect to a parametric factor of interest, in this case age, within a population. Our probabilistic model takes as input the lesion segmentation binary maps of subjects belonging to various age groups and provides a population-level parametric lesion probability map as output. We used a spline representation to ensure a degree of smoothness in space and the dimension associated with the parameter, and formulated our model using a Bayesian framework.We tested our algorithm output on simulated data and compared our results with those obtained using various existing methods with different levels of algorithmic and computational complexity. We then compared the better performing methods on a real dataset, consisting of 1000 subjects of the UK Biobank, divided in two groups based on hypertension diagnosis. Finally, we applied our method on a clinical dataset of patients with vascular disease.On simulated dataset, the results from our algorithm showed a mean square error (MSE) value of 7.27 × 10−5, which was lower than the MSE value reported in the literature, with the advantage of being robust and computationally efficient. In the UK Biobank data, we found that the lesion probabilities are higher for the hypertension group compared to the non-hypertension group and further verified this finding using a statistical t-test. Finally, when applying our method on patients with vascular disease, we observed that the overall probability of lesions is significantly higher in later age groups, which is in line with the current literature.

scholarly journals Midlife blood pressure is associated with the severity of white matter hyperintensities: analysis of the UK Biobank cohort study

2020 ◽  
Author(s):  
Karolina Agnieszka Wartolowska ◽  
Alastair John Stewart Webb
Keyword(s):  
Blood Pressure ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Linear Models ◽  
Population Attributable Fraction ◽  
Relative Role ◽  
Uk Biobank ◽  
Assessment Centre ◽  
The Uk

Abstract Aims White matter hyperintensities (WMH) progress with age and hypertension, but the key period of exposure to elevated blood pressure (BP), and the relative role of systolic BP (SBP) vs. diastolic BP (DBP), remains unclear. This study aims to determine the relationship between WMH and concurrent vs. past BP.  Methods and results  UK Biobank is a prospective community-based cohort of 40–69-year olds from 22 centres, with magnetic resonance imaging in a subgroup of over 40 000 people at 4–12 years after baseline assessment. Standardized associations between WMH load (WMH volume normalized by total white matter volume and logit-transformed) and concurrent vs. past BP were determined using linear models, adjusted for age, sex, cardiovascular risk factors, BP source, assessment centre, and time since baseline. Associations adjusted for regression dilution bias were determined between median WMH and usual SBP or DBP, stratified by age and baseline BP. In 37 041 eligible participants with WMH data and BP measures, WMH were more strongly associated with concurrent SBP [DBP: β = 0.064, 95% confidence interval (CI) 0.050–0.078; SBP: β = 0.076, 95% CI 0.062–0.090], but the strongest association was for past DBP (DBP: β = 0.087, 95% CI 0.064–0.109; SBP: β = 0.045, 95% CI 0.022–0.069), particularly under the age of 50 (DBP: β = 0.103, 95% CI 0.055–0.152; SBP: β = 0.012, 95% CI −0.044 to 0.069). Due to the higher prevalence of elevated SBP, median WMH increased 1.126 (95% CI 1.107–1.146) per 10 mmHg usual SBP and 1.106 (95% CI 1.090–1.122) per 5 mmHg usual DBP, whilst the population attributable fraction of WMH in the top decile was greater for elevated SBP (19.1% for concurrent SBP; 24.4% for past SBP). Any increase in BP, even below 140 for SBP and below 90 mmHg for DBP, and especially if requiring antihypertensive medication, was associated with increased WMH. Conclusions WMH were strongly associated with concurrent and past elevated BP with the population burden of severe WMH greatest for SBP. However, before the age of 50, DBP was more strongly associated with WMH. Long-term prevention of WMH may require control of even mildly elevated midlife DBP.

scholarly journals Obesity impairs cognitive function via metabolic syndrome and cerebrovascular disease: an SEM analysis in 15,000 adults from the UK Biobank

2020 ◽  
Author(s):  
Filip Morys ◽  
Mahsa Dadar ◽  
Alain Dagher
Keyword(s):  
Metabolic Syndrome ◽  
Cognitive Impairment ◽  
White Matter ◽  
Cerebrovascular Disease ◽  
Cortical Thickness ◽  
White Matter Hyperintensities ◽  
Uk Biobank ◽  
Central Nervous System Damage ◽  
The Uk ◽  
The Relationship

AbstractChronic obesity is associated with several complications, including cognitive impairment and dementia. However, we have piecemeal knowledge of the mechanisms linking obesity to central nervous system damage. Adiposity leads to the metabolic syndrome, consisting of inflammation, hypertension, dyslipidemia and insulin resistance. In turn, these metabolic abnormalities cause cerebrovascular dysfunction, which may cause white and grey matter tissue loss and consequent cognitive impairment. While there have been several neuroimaging studies linking adiposity to changes in brain morphometry, a comprehensive investigation of the relationship has so far not been done. Here we use structural equation modelling applied to over 15,000 individuals from the UK Biobank to identify the causal chain that links adiposity to cognitive dysfunction. We found that body mass index and waist-to-hip ratio were positively related to higher plasma C-reactive protein, dyslipidemia, occurrence of hypertension and diabetes, all of which were in turn related to cerebrovascular disease as measured by volume of white matter hyperintensities on magnetic resonance imaging. White mater hyperintensities were associated with lower cortical thickness and volume and higher subcortical volumes, which were associated with cognitive deficits on tests of visuospatial memory, fluid intelligence, and working memory among others. In follow-up analyses we found that inflammation, hypertension and diabetes mediated 20% of the relationship between obesity and cerebrovascular disease and that cerebrovascular disease mediated a significant proportion of the relationship between obesity and cortical thickness and volume. We also showed that volume of white matter hyperintensities was related to decreased fractional anisotropy and increased mean diffusivity in the majority of white matter tracts, pointing to white matter dysconnectivity as a major cause of impaired cognition. Our results have clinical implications, supporting a role for the management of adiposity in the prevention of late-life dementia and cognitive decline.

scholarly journals Whole-exome sequencing in 16,511 individuals reveals a role of the HTRA1 protease and its substrate EGFL8 in brain white matter hyperintensities

2021 ◽  
Author(s):  
Rainer Malik ◽  
Nathalie Beaufort ◽  
Simon Frerich ◽  
Benno Gesierich ◽  
Marios K Georgakis ◽  
...  
Keyword(s):  
White Matter ◽  
General Population ◽  
White Matter Hyperintensities ◽  
Rare Variants ◽  
Uk Biobank ◽  
Protease Domain ◽  
Whole Exome ◽  
The Uk ◽  
Burden Tests

White matter hyperintensities (WMH) are among the most common radiological abnormalities in the ageing population and an established risk factor for stroke and dementia. While common variant association studies have revealed multiple genetic loci with an influence on WMH volume, the contribution of rare variants to WMH burden in the general population remains largely unexplored. We conducted a comprehensive analysis of WMH burden in the UK Biobank using publicly available whole-exome sequencing data (N=16,511) and found a splice-site variant in GBE1, encoding 1,4-alpha-glucan branching enzyme 1, to be associated with lower white matter burden on an exome-wide level (c.691+2T>C, beta=-0.74, se=0.13, p=9.7E-9). Applying whole-exome gene-based burden tests, we found damaging missense and loss-of-function variants in HTRA1 to associate with increased WMH volume (p=5.5E-6, FDR=0.04). HTRA1 encodes a secreted serine protease implicated in familial forms of small vessel disease. Domain-specific burden tests revealed that the association with WMH volume was restricted to rare variants in the protease domain (amino acids 204-364; beta=0.79, se=0.14, p=9.4E-8). The frequency of such variants in the UK Biobank population was 1 in 450. WMH volume was brought forward by approximately 11 years in carriers of a rare protease domain variant. A comparison with the effect size of established risk factors for WMH burden revealed that the presence of a rare variant in the HTRA1 protease domain corresponded to a larger effect than meeting the criteria for hypertension (beta=0.26, se=0.02, p=2.9E-59) or being in the upper 99.8% percentile of the distribution of a polygenic risk score based on common genetic variants (beta=0.44, se=0.14, p=0.002). In biochemical experiments, most (6/9) of the identified protease domain variants resulted in a markedly reduced protease activity. We further found EGFL8, which showed suggestive evidence for association with WMH volume (p=1.5E-4, FDR=0.22) in gene burden tests, to be a direct substrate of HTRA1 and to be preferentially expressed in cerebral arterioles and arteries. In a phenome-wide association study (PheWAS) mapping ICD-10 diagnoses to 741 standardized Phecodes, rare variants in the HTRA1 protease domain were associated with multiple neurological and non-neurological conditions including migraine with aura (OR=12.24, 95%CI [2.54-35.25], p=8.3E-5). Collectively, these findings highlight an important role of rare genetic variation and of the HTRA1 protease in determining WMH burden in the general population. 

scholarly journals Is glycaemia associated with poorer brain health and risk of dementia? Cross sectional and follow-up analysis of the UK Biobank

2020 ◽  
Author(s):  
Victoria Garfield ◽  
Aliki-Eleni Farmaki ◽  
Sophie V. Eastwood ◽  
Rohini Mathur ◽  
Christopher T. Rentsch ◽  
...  
Keyword(s):  
Cognitive Function ◽  
White Matter ◽  
Cognitive Decline ◽  
Visual Memory ◽  
White Matter Hyperintensities ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Brain Health ◽  
Cross Sectional ◽  
The Uk

ABSTRACTObjectiveTo understand the relationship across the glycaemic spectrum with incident dementia, brain structure, and cognitive decline.Research Design and Methods: UK Biobank participants, aged 40-69 at recruitment. HbA1c and diabetes diagnosis define baseline glycaemic categories. Outcomes included incident vascular dementia (VD), Alzheimer’s dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. All results are in reference to normoglycaemic individuals (HbA1c 35-<42 mmol/mol).Results210433 (47%), 15246 (3%), 3280 (0.7%), 20793 (5%) individuals had low HbA1c, pre-diabetes, undiagnosed diabetes, and known diabetes, respectively. Pre- and known diabetes markedly increased incident VD, (hazard ratios (HR) 1.51, 95%CI=1.01;2.25 and 1.96, 95%CI=1.49;2.58, respectively), less so AD (1.18, 0.92;1.52 and 1.13 0.95,1.33), adjusting for demographic and socioeconomic variables. For VD, multivariate adjustment, driven by antihypertensives, attenuated associations, HR 1.27, 0.84;1.91 and 1.45,1.07;1.97. Pre- and known diabetes conferred elevated risks of cognitive decline (odds ratio OR 1.53, 1.02;2.29 and 1.49, 1.02;2.18, respectively). People with pre-diabetes, undiagnosed and known diabetes had higher WMH volumes (4%, 30%, 3%, respectively), and lower HV (34.51 mm3, 11.73 mm3 and 61.13 mm3 respectively). People with low-normal HbA1c (<35 mmol/mol) had 5% lower WMH volume and 13.6 mm3 greater HV than normoglycaemic individuals.ConclusionsPre and known diabetes increase VD risks, less so AD. Excess VD risks were largely accounted for by treated hypertension. Hyperglycaemic states were associated with adverse, whereas low normal HbA1c was associated with favourable brain structure compared to normoglycaemic individuals. Our findings have implications for cardiovascular medication in hyperglycaemia for brain health.Type-2 diabetes and, more generally, hyperglycaemic states, have been associated with poorer cognitive function (such as learning and memory)(1), increased risk of dementia(2) and alterations in key brain structures, particularly the hippocampus(3). In contrast, recent evidence from a randomised crossover trial also suggests that, in people with diabetes, even modest hypoglycaemia has a detrimental effect on cognitive function(4). Thus, it is also important to explore how low levels of glycated haemoglobin (HbA1c) relate to these outcomes. A previous paper explored the cross sectional association between baseline diabetes and two cognition measures in the UK Biobank (reaction time and visual memory)(5). The authors found that diabetes was associated with poorer scores on the reaction time test, but paradoxically, better scores on the visual memory test. They did not explore other outcomes or lesser glycaemic states.Memory loss is the most conclusively reported adverse effect of hyperglycaemia on cognitive function(6). Hippocampal atrophy is a crucial feature of age-related memory loss and the hippocampus is particularly vulnerable to the neurotoxic consequences of diabetes(7). Evidence relating diabetes to the presence and progression of white matter hyperintensities is equivocal(8), but some research suggests that those with diabetes have greater volumes of white matter hyperintensities(9,10). Although there have been numerous studies in this area, the role of glycaemia in brain health across the entire glycaemic spectrum remains unclear, in particular no studies have investigated how lesser hyperglycaemic states relate to these outcomes, as most studies have focused on diagnosed diabetes only.Thus, the aim of this study was to investigate the associations between five glycaemic states across the entire spectrum (low HbA1c, normoglycaemia, pre-diabetes, undiagnosed diabetes and known diabetes) and Alzheimer’s dementia (AD) risk, vascular dementia (VD) risk, baseline cognitive function and cognitive decline, hippocampal volume, and white matter hyperintensities volume in the UK Biobank. We hypothesised that there would be a U-shaped association between glycaemia and our outcomes of interest, such that those with lower and higher HbA1c would have worse outcomes than those with normal glycaemic levels.

Variation of cardiac magnetic resonance radiomics features by age and sex in healthy participants from the UK Biobank

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
Z Raisi-Estabragh ◽  
A Jaggi ◽  
N Aung ◽  
S Neubauer ◽  
S Piechnik ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiac Magnetic Resonance ◽  
Age Groups ◽  
Texture Features ◽  
Funding Source ◽  
Uk Biobank ◽  
Men And Women ◽  
The Uk ◽  
Age And Sex ◽  
Apparently Healthy

Abstract Introduction Cardiac magnetic resonance (CMR) radiomics use voxel-level data to derive quantitative indices of myocardial tissue texture, which may provide complementary risk information to traditional CMR measures. Purpose In this first stage of our work, establishing the performance characteristics of CMR radiomics in relation to disease outcomes, we aimed to elucidate differences in radiomic features by sex and age in apparently healthy adults. Methods We defined a healthy cohort from the first 5,065 individuals completing the UK Biobank Imaging Enhancement, limiting to white Caucasian ethnicity, and excluding those with major co-morbidities, or cardiovascular risk factors/symptoms. We created evenly distributed age groups: 45–54 years, 55–64 years, 65–74 years. Radiomics features were extracted from left ventricle segmentations, with normalisation to body surface area. We compared mean values of individual features between the sexes, stratified by age and separately between the oldest and youngest age groups for each sex. Results We studied 657 (309 men, 358 women) healthy individuals. There were significant differences between radiomics features of men and women. Different features appeared more important at different age groups. For instance, in the youngest age group “end-systolic coarseness” showed greatest difference between men and women, whilst “end-diastolic run percentage” and “end-diastolic high grey level emphasis” showed most variation in the oldest and middle age groups. In the oldest age groups, differences between men and women were most predominant in the texture features, whilst in the younger groups a mixture of shape and texture differences were observed. We demonstrate significant variation between radiomics features by age, these differences are exclusively in texture features with different features implicated in men and women (“end-diastolic mean intensity” in women, “end-systolic sum entropy in men”). Conclusions There are significant age and sex differences in CMR radiomics features of apparently healthy adults, demonstrating alterations in myocardial architecture not appreciated by conventional indices. In younger ages, shape and texture differences are observed, whilst in older ages texture differences dominate. Furthermore, texture features are the most different features between the youngest and oldest hearts. We provide proof-of-concept data indicating CMR radiomics has discriminatory value with regard to two characteristics strongly linked to cardiovascular outcomes. We will next elucidate relationships between CMR radiomics, cardiac risk factors, and clinical outcomes, establishing predictive value incremental to existing measures. Funding Acknowledgement Type of funding source: Other. Main funding source(s): European Union's Horizon 2020 research and innovation programme (825903),British Heart Foundation Clinical Research Training Fellowship (FS/17/81/33318)

scholarly journals Associations of cigarette smoking with gray and white matter in the UK Biobank

2019 ◽  
Author(s):  
Joshua Gray ◽  
Matthew Thompson ◽  
Chelsie Benca-Bachman ◽  
Max Michael Owens ◽  
Mikela Murphy ◽  
...  
Keyword(s):  
White Matter ◽  
Cigarette Smoking ◽  
Gray Matter ◽  
Brain Structure ◽  
Mean Diffusivity ◽  
Medial Lemniscus ◽  
Uk Biobank ◽  
Matter Volume ◽  
Increased Risk ◽  
The Uk

Chronic cigarette smoking is associated with increased risk for myriad health consequences including cognitive decline and dementia, but research on the link between smoking and brain structure is nascent. We assessed the relationship of cigarette smoking (ever smoked, cigarettes per day, and duration) with gray and white matter using the UK Biobank cohort (gray matter N = 19,615; white matter N = 17,760), adjusting for numerous demographic and health confounders. Ever smoked and duration were associated with smaller total gray matter volume. Ever smoked was associated with reduced volume of the right VIIIa cerebellum, as well as elevated white matter hyperintensity volumes. Smoking duration was associated with reduced total white matter volume. With regard to specific tracts, ever smoked was associated with reduced fractional anisotropy in the left cingulate gyrus part of the cingulum, left posterior thalamic radiation, and bilateral superior thalamic radiation and increased mean diffusivity in the middle cerebellar peduncle, right medial lemniscus, bilateral posterior thalamic radiation, and bilateral superior thalamic radiation. Overall, we found significant associations of cigarette exposure with global measures of gray and white matter. Furthermore, we found select associations of ever smoked, but not cigarettes per day or duration, with specific gray and white matter regions. These findings inform our understanding of the connections between smoking and variation in brain structure and clarify potential mechanisms of risk for common neurological sequelae.

scholarly journals Vaccinating Adolescents and Children Significantly Reduces COVID-19 Morbidity and Mortality across All Ages: A Popula-Tion-Based Modeling Study Using the UK as an Example

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1180
Author(s):  
Tinevimbo Shiri ◽  
Marc Evans ◽  
Carla A. Talarico ◽  
Angharad R. Morgan ◽  
Maaz Mussad ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Age Groups ◽  
Population Level ◽  
Vital Role ◽  
Morbidity And Mortality ◽  
Transmission Model ◽  
Base Case ◽  
Global Public Health ◽  
The Uk ◽  
The Impact

Debate persists around the risk–benefit balance of vaccinating adolescents and children against COVID-19. Central to this debate is quantifying the contribution of adolescents and children to the transmission of SARS-CoV-2, and the potential impact of vaccinating these age groups. In this study, we present a novel SEIR mathematical disease transmission model that quantifies the impact of different vaccination strategies on population-level SARS-CoV-2 infections and clinical outcomes. The model employs both age- and time-dependent social mixing patterns to capture the impact of changes in restrictions. The model was used to assess the impact of vaccinating adolescents and children on the natural history of the COVID-19 pandemic across all age groups, using the UK as an example. The base case model demonstrates significant increases in COVID-19 disease burden in the UK following a relaxation of restrictions, if vaccines are limited to those ≥18 years and vulnerable adolescents (≥12 years). Including adolescents and children in the vaccination program could reduce overall COVID-related mortality by 57%, and reduce cases of long COVID by 75%. This study demonstrates that vaccinating adolescents and children has the potential to play a vital role in reducing SARS-CoV-2 infections, and subsequent COVID-19 morbidity and mortality, across all ages. Our results have major global public health implications and provide valuable information to inform a potential pandemic exit strategy.

scholarly journals Associations of cigarette smoking with gray and white matter in the UK Biobank

2020 ◽  
Vol 45 (7) ◽  
pp. 1215-1222
Author(s):  
Joshua C. Gray ◽  
Matthew Thompson ◽  
Chelsie Bachman ◽  
Max M. Owens ◽  
Mikela Murphy ◽  
...  
Keyword(s):  
White Matter ◽  
Cigarette Smoking ◽  
Uk Biobank ◽  
The Uk

scholarly journals Adapting the UK Biobank brain imaging protocol and analysis pipeline for the C-MORE multi-organ study of COVID-19 survivors

2021 ◽  
Author(s):  
Ludovica Griffanti ◽  
Betty Raman ◽  
Fidel Alfaro-Almagro ◽  
Nicola Filippini ◽  
Mark Philip Cassar ◽  
...  
Keyword(s):  
White Matter ◽  
Brain Mri ◽  
Mean Diffusivity ◽  
Brain Anatomy ◽  
Uk Biobank ◽  
Analysis Pipeline ◽  
Imaging Protocol ◽  
Diffusion Weighted Images ◽  
Radiology Reports ◽  
The Uk

SARS-CoV-2 infection has been shown to damage multiple organs, including the brain. Multiorgan MRI can provide further insight on the repercussions of COVID-19 on organ health but requires a balance between richness and quality of data acquisition and total scan duration. We adapted the UK Biobank brain MRI protocol to produce high-quality images while being suitable as part of a post-COVID-19 multiorgan MRI exam. The analysis pipeline, also adapted from UK Biobank, includes new imaging-derived phenotypes (IDPs) designed to assess the effects of COVID-19. A first application of the protocol and pipeline was performed in 51 COVID-19 patients post-hospital discharge and 25 controls participating in the Oxford C-MORE study. The protocol acquires high resolution T1, T2-FLAIR, diffusion weighted images, susceptibility weighted images, and arterial spin labelling data in 17 minutes. The automated imaging pipeline derives 1575 IDPs, assessing brain anatomy (including olfactory bulb volume and intensity) and tissue perfusion, hyperintensities, diffusivity, and susceptibility. In the C-MORE data, these quantitative measures were consistent with clinical radiology reports. Our exploratory analysis tentatively revealed that recovered COVID-19 patients had a decrease in frontal grey matter volumes, an increased burden of white matter hyperintensities, and reduced mean diffusivity in the total and normal appearing white matter in the posterior thalamic radiation and sagittal stratum, relative to controls. These differences were generally more prominent in patients who received organ support. Increased T2* in the thalamus was also observed in recovered COVID-19 patients, with a more prominent increase for non-critical patients. This initial evidence of brain changes in COVID-19 survivors prompts the need for further investigations. Follow-up imaging in the C-MORE study is currently ongoing, and this protocol is now being used in large-scale studies. The pipeline is widely applicable and will contribute to new analyses to hopefully clarify the medium to long-term effects of COVID-19.

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