Publications by authors named "Sana Suri"

33 Publications

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

Neuroimage 2021 May 20;237:118189. Epub 2021 May 20.

Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK. Electronic address:

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 study sample differences contributing to differences in WMH variations across studies. 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.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118189DOI Listing
May 2021

Associations of dietary markers with brain volume and connectivity: A systematic review of MRI studies.

Ageing Res Rev 2021 May 13;70:101360. Epub 2021 May 13.

Department of Psychiatry, University of Oxford, OX3 7JX, UK; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX37JX, UK.

The high prevalence of unhealthy dietary patterns and related brain disorders, such as dementia, emphasizes the importance of research that examines the effect of dietary factors on brain health. Identifying markers of brain health, such as volume and connectivity, that relate to diet is an important first step towards understanding the lifestyle determinants of healthy brain ageing. We conducted a systematic review of 52 studies (total n = 21,221 healthy participants aged 26-80 years, 55 % female) that assessed with a range of MRI measurements, which brain areas, connections, and cerebrovascular factors were associated with dietary markers. We report associations between regional brain measures and dietary health. Collectively, lower diet quality was related to reduced brain volume and connectivity, especially in white and grey matter of the frontal, temporal and parietal lobe, cingulate, entorhinal cortex and the hippocampus. Associations were also observed in connecting fibre pathways and in particular the default-mode, sensorimotor and attention networks. However, there were also some inconsistencies in research methods and findings. We recommend that future research use more comprehensive and consistent dietary measures, more representative samples, and examine the role of key subcortical regions previously highlighted in relevant animal work.
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http://dx.doi.org/10.1016/j.arr.2021.101360DOI Listing
May 2021

Associations of cognitive performance with cardiovascular magnetic resonance phenotypes in the UK Biobank.

Eur Heart J Cardiovasc Imaging 2021 May 14. Epub 2021 May 14.

Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.

Aims: Existing evidence suggests links between brain and cardiovascular health. We investigated associations between cognitive performance and cardiovascular magnetic resonance (CMR) phenotypes in the UK Biobank, considering a range of potential confounders.

Methods And Results: We studied 29 763 participants with CMR and cognitive testing, specifically, fluid intelligence (FI, 13 verbal-numeric reasoning questions), and reaction time (RT, a timed pairs matching exercise); both were considered continuous variables for modelling. We included the following CMR metrics: left and right ventricular (LV and RV) volumes in end-diastole and end-systole, LV/RV ejection fractions, LV/RV stroke volumes, LV mass, and aortic distensibility. Multivariable linear regression models were used to estimate the association of each CMR measure with FI and RT, adjusting for age, sex, smoking, education, deprivation, diabetes, hypertension, high cholesterol, prior myocardial infarction, alcohol intake, and exercise level. We report standardized beta-coefficients, 95% confidence intervals, and P-values adjusted for multiple testing. In this predominantly healthy cohort (average age 63.0 ± 7.5 years), better cognitive performance (higher FI, lower RT) was associated with larger LV/RV volumes, higher LV/RV stroke volumes, greater LV mass, and greater aortic distensibility in fully adjusted models. There was some evidence of non-linearity in the relationship between FI and LV end-systolic volume, with reversal of the direction of association at very high volumes. Associations were consistent for men and women and in different ages.

Conclusion: Better cognitive performance is associated with CMR measures likely representing a healthier cardiovascular phenotype. These relationships remained significant after adjustment for a range of cardiometabolic, lifestyle, and demographic factors, suggesting possible involvement of alternative disease mechanisms.
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http://dx.doi.org/10.1093/ehjci/jeab075DOI Listing
May 2021

Study Protocol: The Heart and Brain Study.

Front Physiol 2021 31;12:643725. Epub 2021 Mar 31.

Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Background: It is well-established that what is good for the heart is good for the brain. Vascular factors such as hypertension, diabetes, and high cholesterol, and genetic factors such as the apolipoprotein E4 allele increase the risk of developing both cardiovascular disease and dementia. However, the mechanisms underlying the heart-brain association remain unclear. Recent evidence suggests that impairments in vascular phenotypes and cerebrovascular reactivity (CVR) may play an important role in cognitive decline. The combines state-of-the-art vascular ultrasound, cerebrovascular magnetic resonance imaging (MRI) and cognitive testing in participants of the long-running Whitehall II Imaging cohort to examine these processes together. This paper describes the study protocol, data pre-processing and overarching objectives.

Methods And Design: The 775 participants of the Whitehall II Imaging cohort, aged 65 years or older in 2019, have received clinical and vascular risk assessments at 5-year-intervals since 1985, as well as a 3T brain MRI scan and neuropsychological tests between 2012 and 2016 (Whitehall II Wave MRI-1). Approximately 25% of this cohort are selected for the , which involves a single testing session at the University of Oxford (Wave MRI-2). Between 2019 and 2023, participants will undergo ultrasound scans of the ascending aorta and common carotid arteries, measures of central and peripheral blood pressure, and 3T MRI scans to measure CVR in response to 5% carbon dioxide in air, vessel-selective cerebral blood flow (CBF), and cerebrovascular lesions. The structural and diffusion MRI scans and neuropsychological battery conducted at Wave MRI-1 will also be repeated. Using this extensive life-course data, the will examine how 30-year trajectories of vascular risk throughout midlife (40-70 years) affect vascular phenotypes, cerebrovascular health, longitudinal brain atrophy and cognitive decline at older ages.

Discussion: The study will generate one of the most comprehensive datasets to examine the longitudinal determinants of the heart-brain association. It will evaluate novel physiological processes in order to describe the optimal window for managing vascular risk in order to delay cognitive decline. Ultimately, the will inform strategies to identify at-risk individuals for targeted interventions to prevent or delay dementia.
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http://dx.doi.org/10.3389/fphys.2021.643725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046163PMC
March 2021

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

Neuroimage Clin 2021 7;30:102616. Epub 2021 Mar 7.

Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.

White matter hyperintensities (WMHs) on T-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T-weighted images (Tw) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and Tw-hypointense/nonTw-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular Tw-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in Tw reveals specific associations with cognitive performance.
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http://dx.doi.org/10.1016/j.nicl.2021.102616DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995650PMC
March 2021

Associations between arterial stiffening and brain structure, perfusion, and cognition in the Whitehall II Imaging Sub-study: A retrospective cohort study.

PLoS Med 2020 12 29;17(12):e1003467. Epub 2020 Dec 29.

Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Background: Aortic stiffness is closely linked with cardiovascular diseases (CVDs), but recent studies suggest that it is also a risk factor for cognitive decline and dementia. However, the brain changes underlying this risk are unclear. We examined whether aortic stiffening during a 4-year follow-up in mid-to-late life was associated with brain structure and cognition in the Whitehall II Imaging Sub-study.

Methods And Findings: The Whitehall II Imaging cohort is a randomly selected subset of the ongoing Whitehall II Study, for which participants have received clinical follow-ups for 30 years, across 12 phases. Aortic pulse wave velocity (PWV) was measured in 2007-2009 (Phase 9) and at a 4-year follow-up in 2012-2013 (Phase 11). Between 2012 and 2016 (Imaging Phase), participants received a multimodal 3T brain magnetic resonance imaging (MRI) scan and cognitive tests. Participants were selected if they had no clinical diagnosis of dementia and no gross brain structural abnormalities. Voxel-based analyses were used to assess grey matter (GM) volume, white matter (WM) microstructure (fractional anisotropy (FA) and diffusivity), white matter lesions (WMLs), and cerebral blood flow (CBF). Cognitive outcomes were performance on verbal memory, semantic fluency, working memory, and executive function tests. Of 542 participants, 444 (81.9%) were men. The mean (SD) age was 63.9 (5.2) years at the baseline Phase 9 examination, 68.0 (5.2) at Phase 11, and 69.8 (5.2) at the Imaging Phase. Voxel-based analysis revealed that faster rates of aortic stiffening in mid-to-late life were associated with poor WM microstructure, viz. lower FA, higher mean, and radial diffusivity (RD) in 23.9%, 11.8%, and 22.2% of WM tracts, respectively, including the corpus callosum, corona radiata, superior longitudinal fasciculus, and corticospinal tracts. Similar voxel-wise associations were also observed with follow-up aortic stiffness. Moreover, lower mean global FA was associated with faster rates of aortic stiffening (B = -5.65, 95% CI -9.75, -1.54, Bonferroni-corrected p < 0.0125) and higher follow-up aortic stiffness (B = -1.12, 95% CI -1.95, -0.29, Bonferroni-corrected p < 0.0125). In a subset of 112 participants who received arterial spin labelling scans, faster aortic stiffening was also related to lower cerebral perfusion in 18.4% of GM, with associations surviving Bonferroni corrections in the frontal (B = -10.85, 95% CI -17.91, -3.79, p < 0.0125) and parietal lobes (B = -12.75, 95% CI -21.58, -3.91, p < 0.0125). No associations with GM volume or WMLs were observed. Further, higher baseline aortic stiffness was associated with poor semantic fluency (B = -0.47, 95% CI -0.76 to -0.18, Bonferroni-corrected p < 0.007) and verbal learning outcomes (B = -0.36, 95% CI -0.60 to -0.12, Bonferroni-corrected p < 0.007). As with all observational studies, it was not possible to infer causal associations. The generalisability of the findings may be limited by the gender imbalance, high educational attainment, survival bias, and lack of ethnic and socioeconomic diversity in this cohort.

Conclusions: Our findings indicate that faster rates of aortic stiffening in mid-to-late life were associated with poor brain WM microstructural integrity and reduced cerebral perfusion, likely due to increased transmission of pulsatile energy to the delicate cerebral microvasculature. Strategies to prevent arterial stiffening prior to this point may be required to offer cognitive benefit in older age.

Trial Registration: ClinicalTrials.gov NCT03335696.
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http://dx.doi.org/10.1371/journal.pmed.1003467DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771705PMC
December 2020

Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging.

Hum Brain Mapp 2021 Apr 14;42(6):1626-1640. Epub 2020 Dec 14.

Department of Psychiatry, University of Oxford, Oxford, UK.

The concept of brain maintenance refers to the preservation of brain integrity in older age, while cognitive reserve refers to the capacity to maintain cognition in the presence of neurodegeneration or aging-related brain changes. While both mechanisms are thought to contribute to individual differences in cognitive function among older adults, there is currently no "gold standard" for measuring these constructs. Using machine-learning methods, we estimated brain and cognitive age based on deviations from normative aging patterns in the Whitehall II MRI substudy cohort (N = 537, age range = 60.34-82.76), and tested the degree of correspondence between these constructs, as well as their associations with premorbid IQ, education, and lifestyle trajectories. In line with established literature highlighting IQ as a proxy for cognitive reserve, higher premorbid IQ was linked to lower cognitive age independent of brain age. No strong evidence was found for associations between brain or cognitive age and lifestyle trajectories from midlife to late life based on latent class growth analyses. However, post hoc analyses revealed a relationship between cumulative lifestyle measures and brain age independent of cognitive age. In conclusion, we present a novel approach to characterizing brain and cognitive maintenance in aging, which may be useful for future studies seeking to identify factors that contribute to brain preservation and cognitive reserve mechanisms in older age.
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http://dx.doi.org/10.1002/hbm.25316DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978127PMC
April 2021

Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium.

Cereb Cortex 2021 Mar;31(4):1953-1969

Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway.

We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations 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). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.
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http://dx.doi.org/10.1093/cercor/bhaa332DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7945023PMC
March 2021

Effect of apolipoprotein E polymorphism on cognition and brain in the Cambridge Centre for Ageing and Neuroscience cohort.

Brain Neurosci Adv 2020 Jan-Dec;4:2398212820961704. Epub 2020 Oct 7.

Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.

Polymorphisms in the apolipoprotein E (APOE) gene have been associated with individual differences in cognition, brain structure and brain function. For example, the ε4 allele has been associated with cognitive and brain impairment in old age and increased risk of dementia, while the ε2 allele has been claimed to be neuroprotective. According to the 'antagonistic pleiotropy' hypothesis, these polymorphisms have different effects across the lifespan, with ε4, for example, postulated to confer benefits on cognitive and brain functions earlier in life. In this stage 2 of the Registered Report - https://osf.io/bufc4, we report the results from the cognitive and brain measures in the Cambridge Centre for Ageing and Neuroscience cohort (www.cam-can.org). We investigated the antagonistic pleiotropy hypothesis by testing for allele-by-age interactions in approximately 600 people across the adult lifespan (18-88 years), on six outcome variables related to cognition, brain structure and brain function (namely, fluid intelligence, verbal memory, hippocampal grey-matter volume, mean diffusion within white matter and resting-state connectivity measured by both functional magnetic resonance imaging and magnetoencephalography). We found no evidence to support the antagonistic pleiotropy hypothesis. Indeed, Bayes factors supported the null hypothesis in all cases, except for the (linear) interaction between age and possession of the ε4 allele on fluid intelligence, for which the evidence for faster decline in older ages was ambiguous. Overall, these pre-registered analyses question the antagonistic pleiotropy of APOE polymorphisms, at least in healthy adults.
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http://dx.doi.org/10.1177/2398212820961704DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7545750PMC
October 2020

Association of midlife stroke risk with structural brain integrity and memory performance at older ages: a longitudinal cohort study.

Brain Commun 2020 7;2(1):fcaa026. Epub 2020 Mar 7.

Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.

Cardiovascular health in midlife is an established risk factor for cognitive function later in life. Knowing mechanisms of this association may allow preventative steps to be taken to preserve brain health and cognitive performance in older age. In this study, we investigated the association of the Framingham stroke-risk score, a validated multifactorial predictor of 10-year risk of stroke, with brain measures and cognitive performance in stroke-free individuals. We used a large ( = 800) longitudinal cohort of community-dwelling adults of the Whitehall II imaging sub-study with no obvious structural brain abnormalities, who had Framingham stroke risk measured five times between 1991 and 2013 and MRI measures of structural integrity, and cognitive function performed between 2012 and 2016 [baseline mean age 47.9 (5.2) years, range 39.7-62.7 years; MRI mean age 69.81 (5.2) years, range 60.3-84.6 years; 80.6% men]. Unadjusted linear associations were assessed between the Framingham stroke-risk score in each wave and voxelwise grey matter density, fractional anisotropy and mean diffusivity at follow-up. These analyses were repeated including socio-demographic confounders as well as stroke risk in previous waves to examine the effect of residual risk acquired between waves. Finally, we used structural equation modelling to assess whether stroke risk negatively affects cognitive performance via specific brain measures. Higher unadjusted stroke risk measured at each of the five waves over 20 years prior to the MRI scan was associated with lower voxelwise grey and white matter measures. After adjusting for socio-demographic variables, higher stroke risk from 1991 to 2009 was associated with lower grey matter volume in the medial temporal lobe. Higher stroke risk from 1997 to 2013 was associated with lower fractional anisotropy along the corpus callosum. In addition, higher stroke risk from 2012 to 2013, sequentially adjusted for risk measured in 1991-94, 1997-98 and 2002-04 (i.e. 'residual risks' acquired from the time of these examinations onwards), was associated with widespread lower fractional anisotropy, and lower grey matter volume in sub-neocortical structures. Structural equation modelling suggested that such reductions in brain integrity were associated with cognitive impairment. These findings highlight the importance of considering cerebrovascular health in midlife as important for brain integrity and cognitive function later in life (ClinicalTrials.gov Identifier: NCT03335696).
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http://dx.doi.org/10.1093/braincomms/fcaa026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491431PMC
March 2020

Association of trajectories of depressive symptoms with vascular risk, cognitive function and adverse brain outcomes: The Whitehall II MRI sub-study.

J Psychiatr Res 2020 12 9;131:85-93. Epub 2020 Sep 9.

Department of Psychiatry, University of Oxford, Oxford, UK. Electronic address:

Background: Trajectories of depressive symptoms over the lifespan vary between people, but it is unclear whether these differences exhibit distinct characteristics in brain structure and function.

Methods: In order to compare indices of white matter microstructure and cognitive characteristics of groups with different trajectories of depressive symptoms, we examined 774 participants of the Whitehall II Imaging Sub-study, who had completed the depressive subscale of the General Health Questionnaire up to nine times over 25 years. Twenty-seven years after the first examination, participants underwent magnetic resonance imaging to characterize white matter hyperintensities (WMH) and microstructure and completed neuropsychological tests to assess cognition. Twenty-nine years after the first examination, participants completed a further cognitive screening test.

Outcomes: Using K-means cluster modelling, we identified five trajectory groups of depressive symptoms: consistently low scorers ("low"; n = 505, 62·5%), a subgroup with an early peak in depression scores ("early"; n = 123, 15·9%), intermediate scorers ("middle"; n = 89, 11·5%), a late symptom subgroup with an increase in symptoms towards the end of the follow-up period ("late"; n = 29, 3·7%), and consistently high scorers ("high"; n = 28, 3·6%). The late, but not the consistently high scorers, showed higher mean diffusivity, larger volumes of WMH and impaired executive function. In addition, the late subgroup had higher Framingham Stroke Risk scores throughout the follow-up period, indicating a higher load of vascular risk factors.

Interpretation: Our findings suggest that tracking depressive symptoms in the community over time may be a useful tool to identify phenotypes that show different etiologies and cognitive and brain outcomes.
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http://dx.doi.org/10.1016/j.jpsychires.2020.09.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063684PMC
December 2020

The Global Brain Health Survey: Development of a Multi-Language Survey of Public Views on Brain Health.

Front Public Health 2020 14;8:387. Epub 2020 Aug 14.

The Ukrainian Psychotrauma Center, Lesya Ukrainka Eastern European National University, Lutsk, Ukraine.

Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15-20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.
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http://dx.doi.org/10.3389/fpubh.2020.00387DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456866PMC
May 2021

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

Neuroimage 2020 11 21;222:117292. Epub 2020 Aug 21.

Department of Psychiatry, University of Oxford, Oxford, UK.

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 (WHII) MRI cohort using machine learning and imaging-derived measures of gray matter (GM) morphology, white matter microstructure (WM), and resting state functional connectivity (FC). The results showed that the prediction accuracy improved when multiple imaging modalities were included in the model (R = 0.30, 95% CI [0.24, 0.36]). The modality-specific GM and WM models showed similar performance (R = 0.22 [0.16, 0.27] and R = 0.24 [0.18, 0.30], respectively), while the FC model showed the lowest prediction accuracy (R = 0.002 [-0.005, 0.008]), indicating that the FC features were less related to chronological age compared to structural measures. Follow-up analyses showed that FC predictions were similarly low in a matched sub-sample from UK Biobank, and although FC predictions were consistently lower than GM predictions, the accuracy improved with increasing sample size and age range. Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with brain aging in the WHII cohort. Blood pressure showed a stronger association with white matter compared to gray matter, while no differences in the associations of alcohol intake and stroke risk with these modalities were observed. In conclusion, machine-learning based brain age prediction can reduce the dimensionality of neuroimaging data to provide meaningful biomarkers of individual brain aging. However, model performance depends on study-specific characteristics including sample size and age range, which may cause discrepancies in findings across studies.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121758PMC
November 2020

Associations Between Longitudinal Trajectories of Cognitive and Social Activities and Brain Health in Old Age.

JAMA Netw Open 2020 08 3;3(8):e2013793. Epub 2020 Aug 3.

Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.

Importance: Prior neuroimaging studies have found that late-life participation in cognitive (eg, reading) and social (eg, visiting friends and family) leisure activities are associated with magnetic resonance imaging (MRI) markers of the aging brain, but little is known about the neural and cognitive correlates of changes in leisure activities during the life span.

Objectives: To examine trajectories of cognitive and social activities from midlife to late life and evaluate whether these trajectories are associated with brain structure, functional connectivity, and cognition.

Design, Setting, And Participants: This prospective cohort included participants enrolled in the Whitehall II study and its MRI substudy based in the UK. Participants provided information on their leisure activities at 5 times during calendar years 1997 to 1999, 2002 to 2004, 2006, 2007 to 2009, and 2011 to 2013 and underwent MRI and cognitive battery testing from January 1, 2012, to December 31, 2016. Data analysis was performed from October 7, 2017, to July 15, 2019.

Main Outcome And Measures: Growth curve models and latent class growth analysis were used to identify longitudinal trajectories of cognitive and social activities. Multiple linear regression was used to evaluate associations between activity trajectories and gray matter, white matter microstructure, functional connectivity, and cognition.

Results: A total of 574 individuals (468 [81.5%] men; mean [SD] age, 69.9 [4.9] years; median Montreal Cognitive Assessment score, 28 [interquartile range, 26-28]) were included in the present analysis. During a mean (SD) of 15 (4.2) years, cognitive and social activity levels increased during midlife before reaching a plateau in late life. Both baseline (global cognition: unstandardized β [SE], 0.955 [0.285], uncorrected P = .001; executive function: β [SE], 1.831 [0.499], uncorrected P < .001; memory: β [SE], 1.394 [0.550], uncorrected P = .01; processing speed: β [SE], 1.514 [0.528], uncorrected P = .004) and change (global cognition: β [SE], -1.382 [0.492], uncorrected P = .005, executive function: β [SE], -2.219 [0.865], uncorrected P = .01; memory: β [SE], -2.355 [0.948], uncorrected P = .01) in cognitive activities were associated with multiple domains of cognition as well as global gray matter volume (β [SE], -0.910 [0.388], uncorrected P = .02). Baseline (β [SE], 1.695 [0.525], uncorrected P = .001) and change (β [SE], 2.542 [1.026], uncorrected P = .01) in social activities were associated only with executive function, in addition to voxelwise measures of functional connectivity that involved sensorimotor (quadratic change in social activities: number of voxels, 306; P = 0.01) and temporoparietal (linear change in social activities: number of voxels, 16; P = .02) networks. Otherwise, no voxelwise associations were found with gray matter, white matter, or resting-state functional connectivity. False discovery rate corrections for multiple comparisons suggested that the association between cognitive activity levels and executive function was robust (β [SE], 1.831 [0.499], false discovery rate P < .001).

Conclusions And Relevance: The findings suggest that a life course approach may delineate the association between leisure activities and cognitive and brain health and that interventions aimed at improving and maintaining cognitive engagement may be valuable for the cognitive health of community-dwelling older adults.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.13793DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7441365PMC
August 2020

The maternal brain: Region-specific patterns of brain aging are traceable decades after childbirth.

Hum Brain Mapp 2020 11 7;41(16):4718-4729. Epub 2020 Aug 7.

Department of Psychology, University of Oslo, Oslo, Norway.

Pregnancy involves maternal brain adaptations, but little is known about how parity influences women's 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 were 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.
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http://dx.doi.org/10.1002/hbm.25152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555081PMC
November 2020

Subjective Cognitive Complaints Given in Questionnaire: Relationship With Brain Structure, Cognitive Performance and Self-Reported Depressive Symptoms in a 25-Year Retrospective Cohort Study.

Am J Geriatr Psychiatry 2021 03 7;29(3):217-226. Epub 2020 Jul 7.

Department of Psychiatry (AT, SS, CA,EZ, NF, CES, AM, CEM, KPE), University of Oxford, Oxford, UK.

Background: Subjective cognitive complaints are common but it is unclear whether they indicate an underlying pathological process or reflect affective symptoms.

Method: 800 community-dwelling older adults were drawn from the Whitehall II cohort. Subjective cognitive complaint inquiry for memory and concentration, a range of neuropsychological tests and multimodal MRI were performed in 2012-2016. Subjective complaints were again elicited after 1 year. Group differences in grey and white matter, between those with and without subjective complaints, were assessed using voxel-based morphometry and tract-based spatial statistics, respectively. Mixed effects models assessed whether cognitive decline or depressive symptoms (over a 25-year period) were associated with later subjective complaints. Analyses were controlled for potential confounders and multiple comparisons.

Results: Mean age of the sample at scanning was 69.8 years (±5.1, range: 60.3-84.6). Subjective memory complaints were common (41%) and predicted further similar complaints later (mean 1.4 ± 1.4 years). There were no group differences in grey matter density or white matter integrity. Subjective complaints were not cross-sectionally or longitudinally associated with objectively assessed cognition. However, those with subjective complaints reported higher depressive symptoms ("poor concentration": odds ratio = 1.12, 95% CI 1.07-1.18; "poor memory": odds ratio = 1.18, 1.12-1.24).

Conclusions: In our sample subjective complaints were consistent over time and reflected depressive symptoms but not markers of neurodegenerative brain damage or concurrent or future objective cognitive impairment. Clinicians assessing patients presenting with memory complaints should be vigilant for affective disorders. These results question the rationale for including subjective complaints in a spectrum with Mild Cognitive Impairment diagnostic criteria.
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http://dx.doi.org/10.1016/j.jagp.2020.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097240PMC
March 2021

Sleep duration over 28 years, cognition, gray matter volume, and white matter microstructure: a prospective cohort study.

Sleep 2020 05;43(5)

Department of Neurology, Global Brain Health Institute, Memory and Aging Center, University of California, San Francisco, CA.

Study Objectives: To examine the association between sleep duration trajectories over 28 years and measures of cognition, gray matter volume, and white matter microstructure. We hypothesize that consistently meeting sleep guidelines that recommend at least 7 hours of sleep per night will be associated with better cognition, greater gray matter volumes, higher fractional anisotropy, and lower radial diffusivity values.

Methods: We studied 613 participants (age 42.3 ± 5.03 years at baseline) who self-reported sleep duration at five time points between 1985 and 2013, and who had cognitive testing and magnetic resonance imaging administered at a single timepoint between 2012 and 2016. We applied latent class growth analysis to estimate membership into trajectory groups based on self-reported sleep duration over time. Analysis of gray matter volumes was carried out using FSL Voxel-Based-Morphometry and white matter microstructure using Tract Based Spatial Statistics. We assessed group differences in cognitive and MRI outcomes using nonparametric permutation testing.

Results: Latent class growth analysis identified four trajectory groups, with an average sleep duration of 5.4 ± 0.2 hours (5%, N = 29), 6.2 ± 0.3 hours (37%, N = 228), 7.0 ± 0.2 hours (45%, N = 278), and 7.9 ± 0.3 hours (13%, N = 78). No differences in cognition, gray matter, and white matter measures were detected between groups.

Conclusions: Our null findings suggest that current sleep guidelines that recommend at least 7 hours of sleep per night may not be supported in relation to an association between sleep patterns and cognitive function or brain structure.
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http://dx.doi.org/10.1093/sleep/zsz290DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215267PMC
May 2020

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

Sleep 2020 05;43(5)

Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway.

Objectives: Poor 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.

Methods: Self-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 for whom longitudinal MRIs were available, followed up to 11 years with a mean interval of 3.3 years. Cross-sectional analyses were repeated in a sample of 21,390 participants from the UK Biobank.

Results: No cross-sectional sleep-hippocampal volume relationships were found. However, worse sleep quality, efficiency, problems, and daytime tiredness were related to greater hippocampal volume loss over time, with high scorers showing 0.22% greater annual loss than low scorers. The relationship between sleep and hippocampal atrophy did not vary across age. Simulations showed that the observed longitudinal effects were too small to be detected as age-interactions in the cross-sectional analyses.

Conclusions: Worse self-reported sleep is associated with higher rates of hippocampal volume 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.
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http://dx.doi.org/10.1093/sleep/zsz280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215271PMC
May 2020

Are People Ready for Personalized Brain Health? Perspectives of Research Participants in the Lifebrain Consortium.

Gerontologist 2020 08;60(6):1050-1059

Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.

Background And Objectives: A healthy brain is central to physical and mental well-being. In this multi-site, qualitative study, we investigated views and attitudes of adult participants in brain research studies on the brain and personalized brain health as well as interest in maintaining a healthy brain.

Design And Methods: We conducted individual interviews with 44 adult participants in brain research cohorts of the Lifebrain consortium in Spain, Norway, Germany, and the United Kingdom. The interviews were audio recorded, transcribed, and coded using a cross-country codebook. The interview data were analyzed using qualitative content analysis.

Results: Most participants did not focus on their own brain health and expressed uncertainty regarding how to maintain it. Those actively focusing on brain health often picked one specific strategy like diet or memory training. The participants were interested in taking brain health tests to learn about their individual risk of developing brain diseases, and were willing to take measures to maintain their brain health if personalized follow-up was provided and the measures had proven impact. The participants were interested in more information on brain health. No differences in responses were identified between age groups, sex, or countries.

Discussion And Implications: Concise, practical, personalized, and evidence-based information about the brain may promote brain health. Based on our findings, we have launched an ongoing global brain health survey to acquire more extensive, quantitative, and representative data on public perception of personalized brain health.
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http://dx.doi.org/10.1093/geront/gnz155DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427479PMC
August 2020

Association of Midlife Cardiovascular Risk Profiles With Cerebral Perfusion at Older Ages.

JAMA Netw Open 2019 06 5;2(6):e195776. Epub 2019 Jun 5.

Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Importance: Poor cardiovascular health is an established risk factor for dementia, but little is known about its association with brain physiology in older adults.

Objective: To examine the association of cardiovascular risk factors, measured repeatedly during a 20-year period, with cerebral perfusion at older ages.

Design, Setting, And Participants: In this longitudinal cohort study, individuals were selected from the Whitehall II Imaging Substudy. Participants were included if they had no clinical diagnosis of dementia, had no gross brain structural abnormalities on magnetic resonance imaging scans, and had received pseudocontinuous arterial spin labeling magnetic resonance imaging. Cardiovascular risk was measured at 5-year intervals across 5 phases from September 1991 to October 2013. Arterial spin labeling scans were acquired between April 2014 and December 2014. Data analysis was performed from June 2016 to September 2018.

Exposures: Framingham Risk Score (FRS) for cardiovascular disease, comprising age, sex, high-density lipoprotein cholesterol level, total cholesterol level, systolic blood pressure, use of antihypertensive medications, cigarette smoking, and diabetes, was assessed at 5 visits.

Main Outcomes And Measures: Cerebral blood flow (CBF; in milliliters per 100 g of tissue per minute) was quantified with pseudocontinuous arterial spin labeling magnetic resonance imaging.

Results: Of 116 adult participants, 99 (85.3%) were men. At the first examination, mean (SD) age was 47.1 (5.0) years; at the last examination, mean (SD) age was 67.4 (4.9) years. Mean (SD) age at MRI scan was 69.3 (5.0) years. Log-FRS increased with time (B = 0.058; 95% CI, 0.044 to 0.072; P < .001). Higher cumulative FRS over the 20-year period (measured as the integral of the rate of change of log-FRS) was associated with lower gray matter CBF (B = -0.513; 95% CI -0.802 to -0.224; P < .001) after adjustment for age, sex, education, socioeconomic status, cognitive status, arterial transit time, use of statins, and weekly alcohol consumption. Voxelwise analyses revealed that this association was significant in 39.6% of gray matter regions, including the posterior cingulate, precuneus, lateral parietal cortex, occipital cortex, hippocampi, and parahippocampal gyrus. The strength of the association of higher log-FRS with lower CBF decreased progressively from the first examination (R2 = 0.253; B = -10.816; 99% CI -18.375 to -3.257; P < .001) to the last (R2 = 0.188; B = -7.139; 99% CI -14.861 to 0.582; P = .02), such that the most recent FRS measurement at mean (SD) age 67.4 (4.9) years was not significantly associated with CBF with a Bonferroni-corrected P < .01 .

Conclusions And Relevance: Cardiovascular risk in midlife was significantly associated with lower gray matter perfusion at older ages, but this association was not significant for cardiovascular risk in later life. This finding could inform the timing of cardiovascular interventions so as to be optimally effective.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.5776DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593638PMC
June 2019

Predicting cognitive resilience from midlife lifestyle and multi-modal MRI: A 30-year prospective cohort study.

PLoS One 2019 19;14(2):e0211273. Epub 2019 Feb 19.

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Background: There is significant heterogeneity in the clinical expression of structural brain abnormalities, including Alzheimer's disease biomarkers. Some individuals preserve their memory despite the presence of risk factors or pathological brain changes, indicating resilience. We aimed to test whether resilient individuals could be distinguished from those who develop cognitive impairment, using sociodemographic variables and neuroimaging.

Methods: We included 550 older adults participating in the Whitehall II study with longitudinal data, cognitive test results, and multi-modal MRI. Hippocampal atrophy was defined as Scheltens Scores >0. Resilient individuals (n = 184) were defined by high cognitive performance despite hippocampal atrophy (HA). Non-resilient participants (n = 133) were defined by low cognitive performance (≥1.5 standard deviations (S.D.) below the group mean) in the presence of HA. Dynamic and static exposures were evaluated for their ability to predict later resilience status using multivariable logistic regression. In a brain-wide analysis we tested for group differences in the integrity of white matter (structural connectivity) and resting-state networks (functional connectivity).

Findings: Younger age (OR: 0.87, 95% CI: 0.83 to 0.92, p<0.001), higher premorbid FSIQ (OR: 1.06, 95% CI: 1.03 to 1.10, p<0.0001) and social class (OR 1 vs. 3: 4.99, 95% CI: 1.30 to 19.16, p = 0.02, OR 2 vs. 3: 8.43, 95% CI: 1.80 to 39.45, p = 0.007) were independently associated with resilience. Resilient individuals could be differentiated from non-resilient participants by higher fractional anisotropy (FA), and less association between anterior and posterior resting state networks. Higher FA had a significantly more positive effect on cognitive performance in participants with HA, compared to those without.

Conclusions: Resilient individuals could be distinguished from those who developed impairments on the basis of sociodemographic characteristics, brain structural and functional connectivity, but not midlife lifestyles. There was a synergistic deleterious effect of hippocampal atrophy and poor white matter integrity on cognitive performance. Exploiting and supporting neural correlates of resilience could offer a fresh approach to postpone or avoid the appearance of clinical symptoms.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0211273PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380585PMC
November 2019

Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction.

Neuroimage 2019 01 26;184:801-812. Epub 2018 Sep 26.

Wellcome Centre for Integrative Neuroimaging - Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, UK.

Diffusion MRI data can be affected by hardware and subject-related artefacts that can adversely affect downstream analyses. Therefore, automated quality control (QC) is of great importance, especially in large population studies where visual QC is not practical. In this work, we introduce an automated diffusion MRI QC framework for single subject and group studies. The QC is based on a comprehensive, non-parametric approach for movement and distortion correction: FSL EDDY, which allows us to extract a rich set of QC metrics that are both sensitive and specific to different types of artefacts. Two different tools are presented: QUAD (QUality Assessment for DMRI), for single subject QC and SQUAD (Study-wise QUality Assessment for DMRI), which is designed to enable group QC and facilitate cross-studies harmonisation efforts.
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http://dx.doi.org/10.1016/j.neuroimage.2018.09.073DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6264528PMC
January 2019

Uncoupling protein 2 haplotype does not affect human brain structure and function in a sample of community-dwelling older adults.

PLoS One 2017 3;12(8):e0181392. Epub 2017 Aug 3.

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Uncoupling protein 2 (UCP2) is a mitochondrial membrane protein that plays a role in uncoupling electron transport from adenosine triphosphate (ATP) formation. Polymorphisms of the UCP2 gene in humans affect protein expression and function and have been linked to survival into old age. Since UCP2 is expressed in several brain regions, we investigated in this study whether UCP2 polymorphisms might 1) affect occurrence of neurodegenerative or mental health disorders and 2) affect measures of brain structure and function. We used structural magnetic resonance imaging (MRI), diffusion-weighted MRI and resting-state functional MRI in the neuroimaging sub-study of the Whitehall II cohort. Data from 536 individuals aged 60 to 83 years were analyzed. No association of UCP2 polymorphisms with the occurrence of neurodegenerative disorders or grey and white matter structure or resting-state functional connectivity was observed. However, there was a significant effect on occurrence of mood disorders in men with the minor alleles of -866G>A (rs659366) and Ala55Val (rs660339)) being associated with increasing odds of lifetime occurrence of mood disorders in a dose dependent manner. This result was not accompanied by effects of UCP2 polymorphisms on brain structure and function, which might either indicate that the sample investigated here was too small and underpowered to find any significant effects, or that potential effects of UCP2 polymorphisms on the brain are too subtle to be picked up by any of the neuroimaging measures used.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181392PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5542610PMC
September 2017

Distinct resting-state functional connections associated with episodic and visuospatial memory in older adults.

Neuroimage 2017 10 26;159:122-130. Epub 2017 Jul 26.

Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, United Kingdom.

Episodic and spatial memory are commonly impaired in ageing and Alzheimer's disease. Volumetric and task-based functional magnetic resonance imaging (fMRI) studies suggest a preferential involvement of the medial temporal lobe (MTL), particularly the hippocampus, in episodic and spatial memory processing. The present study examined how these two memory types were related in terms of their associated resting-state functional architecture. 3T multiband resting state fMRI scans from 497 participants (60-82 years old) of the cross-sectional Whitehall II Imaging sub-study were analysed using an unbiased, data-driven network-modelling technique (FSLNets). Factor analysis was performed on the cognitive battery; the Hopkins Verbal Learning test and Rey-Osterreith Complex Figure test factors were used to assess verbal and visuospatial memory respectively. We present a map of the macroscopic functional connectome for the Whitehall II Imaging sub-study, comprising 58 functionally distinct nodes clustered into five major resting-state networks. Within this map we identified distinct functional connections associated with verbal and visuospatial memory. Functional anticorrelation between the hippocampal formation and the frontal pole was significantly associated with better verbal memory in an age-dependent manner. In contrast, hippocampus-motor and parietal-motor functional connections were associated with visuospatial memory independently of age. These relationships were not driven by grey matter volume and were unique to the respective memory domain. Our findings provide new insights into current models of brain-behaviour interactions, and suggest that while both episodic and visuospatial memory engage MTL nodes of the default mode network, the two memory domains differ in terms of the associated functional connections between the MTL and other resting-state brain networks.
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http://dx.doi.org/10.1016/j.neuroimage.2017.07.049DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678287PMC
October 2017

Effect of age and the APOE gene on metabolite concentrations in the posterior cingulate cortex.

Neuroimage 2017 05 18;152:509-516. Epub 2017 Mar 18.

Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom.

Proton magnetic resonance spectroscopy (H-MRS) has provided valuable information about the neurochemical profile of Alzheimer's disease (AD). However, its clinical utility has been limited in part by the lack of consistent information on how metabolite concentrations vary in the normal aging brain and in carriers of apolipoprotein E (APOE) ε4, an established risk gene for AD. We quantified metabolites within an 8cm voxel within the posterior cingulate cortex (PCC)/precuneus in 30 younger (20-40 years) and 151 cognitively healthy older individuals (60-85 years). All H-MRS scans were performed at 3T using the short-echo SPECIAL sequence and analyzed with LCModel. The effect of APOE was assessed in a sub-set of 130 volunteers. Older participants had significantly higher myo-inositol and creatine, and significantly lower glutathione and glutamate than younger participants. There was no significant effect of APOE or an interaction between APOE and age on the metabolite profile. Our data suggest that creatine, a commonly used reference metabolite in H-MRS studies, does not remain stable across adulthood within this region and therefore may not be a suitable reference in studies involving a broad age-range. Increases in creatine and myo-inositol may reflect age-related glial proliferation; decreases in glutamate and glutathione suggest a decline in synaptic and antioxidant efficiency. Our findings inform longitudinal clinical studies by characterizing age-related metabolite changes in a non-clinical sample.
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http://dx.doi.org/10.1016/j.neuroimage.2017.03.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5440729PMC
May 2017

Classification and characterization of periventricular and deep white matter hyperintensities on MRI: A study in older adults.

Neuroimage 2018 04 15;170:174-181. Epub 2017 Mar 15.

Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK; Dipartimento di Scienze Biomediche, Metaboliche e Neuroscienze, Università di Modena e Reggio Emilia, Italy.

White matter hyperintensities (WMH) are frequently divided into periventricular (PWMH) and deep (DWMH), and the two classes have been associated with different cognitive, microstructural, and clinical correlates. However, although this distinction is widely used in visual ratings scales, how to best anatomically define the two classes is still disputed. In fact, the methods used to define PWMH and DWMH vary significantly between studies, making results difficult to compare. The purpose of this study was twofold: first, to compare four current criteria used to define PWMH and DWMH in a cohort of healthy older adults (mean age: 69.58 ± 5.33 years) by quantifying possible differences in terms of estimated volumes; second, to explore associations between the two WMH sub-classes with cognition, tissue microstructure and cardiovascular risk factors, analysing the impact of different criteria on the specific associations. Our results suggest that the classification criterion used for the definition of PWMH and DWMH should not be considered a major obstacle for the comparison of different studies. We observed that higher PWMH load is associated with reduced cognitive function, higher mean arterial pressure and age. Higher DWMH load is associated with higher body mass index. PWMH have lower fractional anisotropy than DWMH, which also have more heterogeneous microstructure. These findings support the hypothesis that PWMH and DWMH are different entities and that their distinction can provide useful information about healthy and pathological aging processes.
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http://dx.doi.org/10.1016/j.neuroimage.2017.03.024DOI Listing
April 2018

Prototypic and arkypallidal neurons in the dopamine-intact external globus pallidus.

J Neurosci 2015 Apr;35(17):6667-88

Medical Research Council Brain Network Dynamics Unit, Department of Pharmacology, University of Oxford, Oxford OX1 3QT, United Kingdom, and Oxford Parkinson's Disease Centre, University of Oxford, Oxford OX1 3QX, United Kingdom

Studies in dopamine-depleted rats indicate that the external globus pallidus (GPe) contains two main types of GABAergic projection cell; so-called "prototypic" and "arkypallidal" neurons. Here, we used correlative anatomical and electrophysiological approaches in rats to determine whether and how this dichotomous organization applies to the dopamine-intact GPe. Prototypic neurons coexpressed the transcription factors Nkx2-1 and Lhx6, comprised approximately two-thirds of all GPe neurons, and were the major GPe cell type innervating the subthalamic nucleus (STN). In contrast, arkypallidal neurons expressed the transcription factor FoxP2, constituted just over one-fourth of GPe neurons, and innervated the striatum but not STN. In anesthetized dopamine-intact rats, molecularly identified prototypic neurons fired at relatively high rates and with high regularity, regardless of brain state (slow-wave activity or spontaneous activation). On average, arkypallidal neurons fired at lower rates and regularities than prototypic neurons, and the two cell types could be further distinguished by the temporal coupling of their firing to ongoing cortical oscillations. Complementing the activity differences observed in vivo, the autonomous firing of identified arkypallidal neurons in vitro was slower and more variable than that of prototypic neurons, which tallied with arkypallidal neurons displaying lower amplitudes of a "persistent" sodium current important for such pacemaking. Arkypallidal neurons also exhibited weaker driven and rebound firing compared with prototypic neurons. In conclusion, our data support the concept that a dichotomous functional organization, as actioned by arkypallidal and prototypic neurons with specialized molecular, structural, and physiological properties, is fundamental to the operations of the dopamine-intact GPe.
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http://dx.doi.org/10.1523/JNEUROSCI.4662-14.2015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4412890PMC
April 2015

Reduced cerebrovascular reactivity in young adults carrying the APOE ε4 allele.

Alzheimers Dement 2015 Jun 23;11(6):648-57.e1. Epub 2014 Aug 23.

Department of Psychiatry, University of Oxford, Oxford United Kingdom; Functional Magnetic Resonance Imaging of the Brain Centre, University of Oxford, Oxford United Kingdom. Electronic address:

Background: Functional magnetic resonance imaging (MRI) studies have shown that APOE ε2- and ε4-carriers have similar patterns of blood-oxygenation-level-dependent (BOLD) activation suggesting that we need to look beyond the BOLD signal to link APOE's effect on the brain to Alzheimer's disease (AD)-risk.

Methods: We evaluated APOE-related differences in BOLD activation in response to a memory task, cerebrovascular reactivity using a CO2-inhalation challenge (CO2-CVR), and the potential contribution of CO2-CVR to the BOLD signal.

Results: APOE ε4-carriers had the highest task-related hippocampal BOLD signal relative to non-carriers. The largest differences in CO2-CVR were between ε2- and ε4-carriers, with the latter having the lowest values. Genotype differences in CO2-CVR accounted for ∼70% of hippocampal BOLD differences between groups.

Conclusion: Because CO2-CVR gauges vascular health, the differential effect of APOE in young adults may reflect a vascular contribution to the vulnerability of ε4-carriers to late-life pathology. Studies confirming our findings are warranted.
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http://dx.doi.org/10.1016/j.jalz.2014.05.1755DOI Listing
June 2015

Using structural and diffusion magnetic resonance imaging to differentiate the dementias.

Curr Neurol Neurosci Rep 2014 Sep;14(9):475

Department of Psychiatry, Warneford Hospital, Warneford Lane, University of Oxford, Oxford, OX3 7JX, UK.

Dementia is one of the major causes of personal, societal and financial dependence in older people and in today's ageing society there is a pressing need for early and accurate markers of cognitive decline. There are several subtypes of dementia but the four most common are Alzheimer's disease, Lewy body dementia, vascular dementia and frontotemporal dementia. These disorders can only be diagnosed at autopsy, and ante-mortem assessments of "probable dementia (e.g. of Alzheimer type)" are traditionally driven by clinical symptoms of cognitive or behavioural deficits. However, owing to the overlapping nature of symptoms and age of onset, a significant proportion of dementia cases remain incorrectly diagnosed. Misdiagnosis can have an extensive impact, both at the level of the individual, who may not be offered the appropriate treatment, and on a wider scale, by influencing the entry of patients into relevant clinical trials. Magnetic resonance imaging (MRI) may help to improve diagnosis by providing non-invasive and detailed disease-specific markers of cognitive decline. MRI-derived measurements of grey and white matter structural integrity are potential surrogate markers of disease progression, and may also provide valuable diagnostic information. This review summarises the latest evidence on the use of structural and diffusion MRI in differentiating between the four major dementia subtypes.
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http://dx.doi.org/10.1007/s11910-014-0475-3DOI Listing
September 2014