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Jensen DEA, Ebmeier KP, Suri S, Rushworth MFS, Klein-Flügge MC. Nuclei-specific hypothalamus networks predict a dimensional marker of stress in humans. Nat Commun 2024; 15:2426. [PMID: 38499548 PMCID: PMC10948785 DOI: 10.1038/s41467-024-46275-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 02/21/2024] [Indexed: 03/20/2024] Open
Abstract
The hypothalamus is part of the hypothalamic-pituitary-adrenal axis which activates stress responses through release of cortisol. It is a small but heterogeneous structure comprising multiple nuclei. In vivo human neuroimaging has rarely succeeded in recording signals from individual hypothalamus nuclei. Here we use human resting-state fMRI (n = 498) with high spatial resolution to examine relationships between the functional connectivity of specific hypothalamic nuclei and a dimensional marker of prolonged stress. First, we demonstrate that we can parcellate the human hypothalamus into seven nuclei in vivo. Using the functional connectivity between these nuclei and other subcortical structures including the amygdala, we significantly predict stress scores out-of-sample. Predictions use 0.0015% of all possible brain edges, are specific to stress, and improve when using nucleus-specific compared to whole-hypothalamus connectivity. Thus, stress relates to connectivity changes in precise and functionally meaningful subcortical networks, which may be exploited in future studies using interventions in stress disorders.
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Affiliation(s)
- Daria E A Jensen
- Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford, OX1 3TA, UK.
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB, University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK.
- Clinic of Cognitive Neurology, University Medical Center Leipzig and Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103, Leipzig, Germany.
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK
| | - Matthew F S Rushworth
- Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford, OX1 3TA, UK
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB, University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Miriam C Klein-Flügge
- Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford, OX1 3TA, UK.
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB, University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Lane, Oxford, OX3 7JX, UK.
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Schindler LS, Subramaniapillai S, Ambikairajah A, Barth C, Crestol A, Voldsbekk I, Beck D, Gurholt TP, Topiwala A, Suri S, Ebmeier KP, Andreassen OA, Draganski B, Westlye LT, de Lange AMG. Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later. Front Glob Womens Health 2023; 4:1320640. [PMID: 38213741 PMCID: PMC10783171 DOI: 10.3389/fgwh.2023.1320640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p < 0.001, LDL β = 0.20, p < 0.001, triglycerides β = 0.12, p < 0.001) and HbA1c (β = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (β = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (β = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (β range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (β = -0.27, p < 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
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Affiliation(s)
- Louise S. Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ananthan Ambikairajah
- Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, Australia
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P. Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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3
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Jensen DE, Ebmeier KP, Akbaraly T, Jansen MG, Singh-Manoux A, Kivimäki M, Zsoldos E, Klein-Flügge MC, Suri S. The association of longitudinal diet and waist-to-hip ratio from midlife to old age with hippocampus connectivity and memory in old age: a cohort study. bioRxiv 2023:2023.12.12.570778. [PMID: 38168259 PMCID: PMC10760001 DOI: 10.1101/2023.12.12.570778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Epidemiological studies suggest lifestyle factors may reduce the risk of dementia. However, few studies have examined the association of diet and waist-to-hip ratio with hippocampus connectivity. In the Whitehall II Imaging Sub-study, we examined longitudinal changes in diet quality in 512 participants and waist-to-hip ratio in 665 participants. Diet quality was measured using the Alternative Health Eating Index-2010 assessed three times across 11 years between ages 48 and 60 years, and waist-to-hip ratio five times over 21 years between ages 48 and 68 years. Brain imaging and cognitive tests were performed at age 70±5 years. We measured white matter using diffusion tensor imaging and hippocampal functional connectivity using resting-state functional magnetic resonance imaging. In addition to associations of diet and waist-to-hip ratio with brain imaging measures, we tested whether associations between diet, waist-to-hip ratio and cognitive performance were mediated by brain connectivity. We found better diet quality in midlife and improvements in diet over mid-to-late life were associated with higher hippocampal functional connectivity to the occipital lobe and cerebellum, and better white matter integrity as measured by higher fractional anisotropy and lower diffusivity. Higher waist-to-hip ratio in midlife was associated with higher mean and radial diffusivity and lower fractional anisotropy in several tracts including the inferior longitudinal fasciculus and cingulum. Associations between midlife waist-to-hip ratio, working memory and executive function were partially mediated by radial diffusivity. All associations were independent of age, sex, education, and physical activity. Our findings highlight the importance of maintaining a good diet and a healthy waist-to-hip ratio in midlife to maintain brain health in later life. Future interventional studies for the improvement of dietary and metabolic health should target midlife for the prevention of cognitive decline in old age.
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Fjell AM, Sørensen Ø, Wang Y, Amlien IK, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demuth I, Drevon CA, Ebmeier KP, Ghisletta P, Kievit R, Kühn S, Madsen KS, Mowinckel AM, Nyberg L, Sexton CE, Solé-Padullés C, Vidal-Piñeiro D, Wagner G, Watne LO, Walhovd KB. No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy. Nat Hum Behav 2023; 7:2008-2022. [PMID: 37798367 PMCID: PMC10663160 DOI: 10.1038/s41562-023-01707-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 08/31/2023] [Indexed: 10/07/2023]
Abstract
Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.
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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - Ilja Demuth
- Department of Endocrinology and Metabolic Diseases (including Division of Lipid Metabolism), Biology of Aging Working Group, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health Center for Regenerative Therapies, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Christian A Drevon
- Vitas AS, Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Rogier Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Claire E Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK
- Global Brain Health Institute, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Alzheimer's Association, Chicago, IL, USA
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
- Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pii Sunyer, Barcelona, Spain
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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Demnitz N, Hulme OJ, Siebner HR, Kjaer M, Ebmeier KP, Boraxbekk CJ, Gillan CM. Characterising the covariance pattern between lifestyle factors and structural brain measures: a multivariable replication study of two independent ageing cohorts. Neurobiol Aging 2023; 131:115-123. [PMID: 37619515 DOI: 10.1016/j.neurobiolaging.2023.07.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 08/26/2023]
Abstract
Modifiable lifestyle factors have been shown to promote healthy brain ageing. However, studies have typically focused on a single factor at a time. Given that lifestyle factors do not occur in isolation, multivariable analyses provide a more realistic model of the lifestyle-brain relationship. Here, canonical correlation analyses (CCA) examined the relationship between nine lifestyle factors and seven MRI-derived indices of brain structure. The resulting covariance pattern was further explored with Bayesian regressions. CCA analyses were first conducted on a Danish cohort of older adults (n = 251) and then replicated in a British cohort (n = 668). In both cohorts, the latent factors of lifestyle and brain structure were positively correlated (UK: r = .37, p < 0.001; Denmark: r = .27, p < 0.001). In the cross-validation study, the correlation between lifestyle-brain latent factors was r = .10, p = 0.008. However, the pattern of associations differed between datasets. These findings suggest that baseline characterisation and tailoring towards the study sample may be beneficial for achieving targeted lifestyle interventions.
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Affiliation(s)
- Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark.
| | - Oliver J Hulme
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; London Mathematical Laboratory, London, UK; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael Kjaer
- Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Center for Healthy Aging, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark; Department of Radiation Sciences, Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Claire M Gillan
- School of Psychology, Trinity College Dublin, Dublin, Ireland; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
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6
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Binnewies J, Nawijn L, Brandmaier AM, Baaré WFC, Boraxbekk CJ, Demnitz N, Drevon CA, Fjell AM, Lindenberger U, Madsen KS, Nyberg L, Topiwala A, Walhovd KB, Ebmeier KP, Penninx BWJH. Lifestyle-related risk factors and their cumulative associations with hippocampal and total grey matter volume across the adult lifespan: A pooled analysis in the European Lifebrain consortium. Brain Res Bull 2023; 200:110692. [PMID: 37336327 DOI: 10.1016/j.brainresbull.2023.110692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 06/16/2023] [Indexed: 06/21/2023]
Abstract
BACKGROUND Lifestyle-related risk factors, such as obesity, physical inactivity, short sleep, smoking and alcohol use, have been associated with low hippocampal and total grey matter volumes (GMV). However, these risk factors have mostly been assessed as separate factors, leaving it unknown if variance explained by these factors is overlapping or additive. We investigated associations of five lifestyle-related factors separately and cumulatively with hippocampal and total GMV, pooled across eight European cohorts. METHODS We included 3838 participants aged 18-90 years from eight cohorts of the European Lifebrain consortium. Using individual person data, we performed cross-sectional meta-analyses on associations of presence of lifestyle-related risk factors separately (overweight/obesity, physical inactivity, short sleep, smoking, high alcohol use) as well as a cumulative unhealthy lifestyle score (counting the number of present lifestyle-related risk factors) with FreeSurfer-derived hippocampal volume and total GMV. Lifestyle-related risk factors were defined according to public health guidelines. RESULTS High alcohol use was associated with lower hippocampal volume (r = -0.10, p = 0.021), and overweight/obesity with lower total GMV (r = -0.09, p = 0.001). Other lifestyle-related risk factors were not significantly associated with hippocampal volume or GMV. The cumulative unhealthy lifestyle score was negatively associated with total GMV (r = -0.08, p = 0.001), but not hippocampal volume (r = -0.01, p = 0.625). CONCLUSIONS This large pooled study confirmed the negative association of some lifestyle-related risk factors with hippocampal volume and GMV, although with small effect sizes. Lifestyle factors should not be seen in isolation as there is evidence that having multiple unhealthy lifestyle factors is associated with a linear reduction in overall brain volume.
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Affiliation(s)
- Julia Binnewies
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, the Netherlands.
| | - Laura Nawijn
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, the Netherlands
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark; Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Christian A Drevon
- Vitas Ltd. Oslo Science Park & Department of Nutrition, IMB, University of Oslo, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Anya Topiwala
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, United Kingdom
| | - Brenda W J H Penninx
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, the Netherlands
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7
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Fjell AM, Sørensen Ø, Wang Y, Amlien IK, Baaré WFC, Bartrés-Faz D, Boraxbekk CJ, Brandmaier AM, Demuth I, Drevon CA, Ebmeier KP, Ghisletta P, Kievit R, Kühn S, Madsen KS, Nyberg L, Solé-Padullés C, Vidal-Piñeiro D, Wagner G, Watne LO, Walhovd KB. Is Short Sleep Bad for the Brain? Brain Structure and Cognitive Function in Short Sleepers. J Neurosci 2023; 43:5241-5250. [PMID: 37365003 PMCID: PMC10342221 DOI: 10.1523/jneurosci.2330-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 05/01/2023] [Accepted: 05/08/2023] [Indexed: 06/28/2023] Open
Abstract
Many sleep less than recommended without experiencing daytime sleepiness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this using a cross-sectional and longitudinal sample of 47,029 participants of both sexes (20-89 years) from the Lifebrain consortium, Human Connectome project (HCP) and UK Biobank (UKB), with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. A total of 740 participants who reported to sleep <6 h did not experience daytime sleepiness or sleep problems/disturbances interfering with falling or staying asleep. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime sleepiness and sleep problems (n = 1742) and participants sleeping the recommended 7-8 h (n = 3886). However, both groups of short sleepers showed slightly lower general cognitive function (GCA), 0.16 and 0.19 SDs, respectively. Analyses using accelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income, and education. The results suggest that some people can cope with less sleep without obvious negative associations with brain morphometry and that sleepiness and sleep problems may be more related to brain structural differences than duration. However, the slightly lower performance on tests of general cognitive abilities warrants closer examination in natural settings.SIGNIFICANCE STATEMENT Short habitual sleep is prevalent, with unknown consequences for brain health and cognitive performance. Here, we show that daytime sleepiness and sleep problems are more strongly related to regional brain volumes than sleep duration. However, participants sleeping ≤6 h had slightly lower scores on tests of general cognitive function (GCA). This indicates that sleep need is individual and that sleep duration per se is very weakly if at all related brain health, while daytime sleepiness and sleep problems may show somewhat stronger associations. The association between habitual short sleep and lower scores on tests of general cognitive abilities must be further scrutinized in natural settings.
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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, 2650 Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Carl-Johan Boraxbekk
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, 2650 Hvidovre, Copenhagen, Denmark
- Umeå Center for Functional Brain Imaging, Umeå University, 907 36 Umeå, Sweden
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, 907 36 Umeå, Sweden
- Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital Bispebjerg, 2400 Copenhagen, Denmark
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, 2020 Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - Ilja Demuth
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Endocrinology and Metabolic Diseases (including Division of Lipid Metabolism), Biology of Aging working group, Augustenburger Platz 1, 13353 Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178 Berlin, Germany
- BCRT - Berlin Institute of Health Center for Regenerative Therapies, 13353 Berlin, Germany
| | - Christian A Drevon
- Vitas AS, The Science Park, 0349 Oslo, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of 0372 Oslo, Norway
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, 1205 Geneva, Switzerland
- UniDistance Suisse, 3900 Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, 1205 Geneva, Switzerland
| | - Rogier Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager and Hvidovre, 2650 Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, 1799 Copenhagen, Denmark
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, 907 36 Umeå, Sweden
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, 07743 Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Oslo University Hospital, 0424 Oslo, Norway
- Department of Geriatric Medicine, Akershus University Hospital, 1478 Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, 1478, Lørenskog, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0424 Oslo, Norway
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8
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Anatürk M, Patel R, Ebmeier KP, Georgiopoulos G, Newby D, Topiwala A, de Lange AMG, Cole JH, Jansen MG, Singh-Manoux A, Kivimäki M, Suri S. Development and validation of a dementia risk score in the UK Biobank and Whitehall II cohorts. BMJ Ment Health 2023; 26:e300719. [PMID: 37603383 PMCID: PMC10577770 DOI: 10.1136/bmjment-2023-300719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/31/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Current dementia risk scores have had limited success in consistently identifying at-risk individuals across different ages and geographical locations. OBJECTIVE We aimed to develop and validate a novel dementia risk score for a midlife UK population, using two cohorts: the UK Biobank, and UK Whitehall II study. METHODS We divided the UK Biobank cohort into a training (n=176 611, 80%) and test sample (n=44 151, 20%) and used the Whitehall II cohort (n=2934) for external validation. We used the Cox LASSO regression to select the strongest predictors of incident dementia from 28 candidate predictors and then developed the risk score using competing risk regression. FINDINGS Our risk score, termed the UK Biobank Dementia Risk Score (UKBDRS), consisted of age, education, parental history of dementia, material deprivation, a history of diabetes, stroke, depression, hypertension, high cholesterol, household occupancy, and sex. The score had a strong discrimination accuracy in the UK Biobank test sample (area under the curve (AUC) 0.8, 95% CI 0.78 to 0.82) and in the Whitehall cohort (AUC 0.77, 95% CI 0.72 to 0.81). The UKBDRS also significantly outperformed three other widely used dementia risk scores originally developed in cohorts in Australia (the Australian National University Alzheimer's Disease Risk Index), Finland (the Cardiovascular Risk Factors, Ageing, and Dementia score), and the UK (Dementia Risk Score). CLINICAL IMPLICATIONS Our risk score represents an easy-to-use tool to identify individuals at risk for dementia in the UK. Further research is required to determine the validity of this score in other populations.
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Affiliation(s)
- Melis Anatürk
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Raihaan Patel
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | - Georgios Georgiopoulos
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Anya Topiwala
- Department of Psychiatry, University of Oxford, Oxford, UK
- Big Data Institute, University of Oxford, Oxford, UK
| | - Ann-Marie G de Lange
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Clinical Neurosciences, University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - James H Cole
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Michelle G Jansen
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud Universiteit, Nijmegen, The Netherlands
| | - Archana Singh-Manoux
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université Paris Cité, Paris, France
- Faculty of Brain Sciences, University College London, London, UK
| | - Mika Kivimäki
- Faculty of Brain Sciences, University College London, London, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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9
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Lövdén M, Pagin A, Bartrés-Faz D, Boraxbekk CJ, Brandmaier AM, Demnitz N, Drevon CA, Ebmeier KP, Fjell AM, Ghisletta P, Gorbach T, Lindenberger U, Plachti A, Walhovd KB, Nyberg L. No moderating influence of education on the association between changes in hippocampus volume and memory performance in aging. Aging Brain 2023; 4:100082. [PMID: 37457634 PMCID: PMC10338350 DOI: 10.1016/j.nbas.2023.100082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/13/2023] [Accepted: 06/14/2023] [Indexed: 07/18/2023] Open
Abstract
Contemporary accounts of factors that may modify the risk for age-related neurocognitive disorders highlight education and its contribution to a cognitive reserve. By this view, individuals with higher educational attainment should show weaker associations between changes in brain and cognition than individuals with lower educational attainment. We tested this prediction in longitudinal data on hippocampus volume and episodic memory from 708 middle-aged and older individuals using local structural equation modeling. This technique does not require categorization of years of education and does not constrain the shape of relationships, thereby maximizing the chances of revealing an effect of education on the hippocampus-memory association. The results showed that the data were plausible under the assumption that there was no influence of education on the association between change in episodic memory and change in hippocampus volume. Restricting the sample to individuals with elevated genetic risk for dementia (APOE ε4 carriers) did not change these results. We conclude that the influence of education on changes in episodic memory and hippocampus volume is inconsistent with predictions by the cognitive reserve theory.
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Affiliation(s)
- Martin Lövdén
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - Amos Pagin
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences and Institute of Neurosciences, University of Barcelona, Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Carl-Johan Boraxbekk
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Andreas M. Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark
| | - Christian A. Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo & Vitas AS, Oslo Science Park, Norway
| | - Klaus P. Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, UK
| | - Anders M. Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317 Oslo, Norway
- ComputationalRadiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Norway
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland
- Faculty of Psychology, UniDistance Suisse, Brig, Switzerland
| | - Tetiana Gorbach
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark
| | - Kristine B. Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317 Oslo, Norway
- ComputationalRadiology and Artificial Intelligence, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Norway
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
- Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland
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10
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Budin‐Ljøsne I, Friedman BB, Baaré WFC, Bartrés‐Faz D, Carver RB, Drevon CA, Ebmeier KP, Fjell AM, Ghisletta P, Henson RN, Kievit R, Madsen KS, Nawijn L, Suri S, Solé‐Padullés C, Walhovd KB, Zsoldos E. Stakeholder engagement in European brain research: Experiences of the Lifebrain consortium. Health Expect 2023; 26:1318-1326. [PMID: 36989126 PMCID: PMC10154816 DOI: 10.1111/hex.13747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 02/17/2023] [Accepted: 02/28/2023] [Indexed: 03/30/2023] Open
Abstract
INTRODUCTION Stakeholder engagement remains scarce in basic brain research. However, it can greatly improve the relevance of investigations and accelerate the translation of study findings to policy. The Lifebrain consortium investigated risk and protective factors influencing brain health using cognition, lifestyle and imaging data from European cohorts. Stakeholder activities of Lifebrain-organized in a separate work package-included organizing stakeholder events, investigating public perceptions of brain health and dissemination. Here, we describe the experiences of researchers and stakeholders regarding stakeholder engagement in the Lifebrain project. METHODS Stakeholder engagement in Lifebrain was evaluated through surveys among researchers and stakeholders and stakeholders' feedback at stakeholder events through evaluation forms. Survey data were analysed using a simple content analysis approach, and results from evaluation forms were summarized after reviewing the frequency of responses. RESULTS Consortium researchers and stakeholders experienced the engagement activities as meaningful and relevant. Researchers highlighted that it made the research and research processes more visible and contributed to new networks, optimized data collection on brain health perceptions and the production of papers and provided insights into stakeholder views. Stakeholders found research activities conducted in the stakeholder engagement work package to be within their field of interest and research results relevant to their work. Researchers identified barriers to stakeholder engagement, including lack of time, difficulties in identifying relevant stakeholders, and challenges in communicating complex scientific issues in lay language and maintaining relationships with stakeholders over time. Stakeholders identified barriers such as lack of budget, limited resources in their organization, time constraints and insufficient communication between researchers and stakeholders. CONCLUSION Stakeholder engagement in basic brain research can greatly benefit researchers and stakeholders alike. Its success is conditional on dedicated human and financial resources, clear communication, transparent mutual expectations and clear roles and responsibilities. PUBLIC CONTRIBUTION Patient organizations, research networks, policymakers and members of the general public were involved in engagement and research activities throughout the project duration.
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Affiliation(s)
| | - Barbara B. Friedman
- Department of Psychology, Center for Lifespan Changes in Brain and CognitionUniversity of OsloOsloNorway
| | - William F. C. Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital—Amager and HvidovreCopenhagenDenmark
| | - David Bartrés‐Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of NeurosciencesUniversity of BarcelonaBarcelonaSpain
| | - Rebecca B. Carver
- Department of CommunicationsNorwegian Institute of Public HealthOsloNorway
| | - Christian A. Drevon
- Vitas ASOsloNorway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of MedicineUniversity of OsloOsloNorway
| | - Klaus P. Ebmeier
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Warneford HospitalUniversity of OxfordOxfordUK
| | - Anders M. Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and CognitionUniversity of OsloOsloNorway
| | - Paolo Ghisletta
- Methodology and Data Analysis Group, Faculty of Psychology and Educational SciencesUniversity of GenevaGenevaSwitzerland
- Faculty Council of the Faculty of PsychologyUniDistance SuisseBrigSwitzerland
- Swiss National Centre of Competence in Research LIVESUniversity of GenevaGenevaSwitzerland
| | - Richard N. Henson
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Rogier Kievit
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Cognitive Neuroscience DepartmentDonders Institute for Brain, Cognition and Behavior, Radboud University Medical CenterNijmegenThe Netherlands
| | - Kathrine S. Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital—Amager and HvidovreCopenhagenDenmark
- Radiography, Department of TechnologyUniversity College CopenhagenCopenhagenDenmark
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Sana Suri
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Warneford HospitalUniversity of OxfordOxfordUK
| | - Cristina Solé‐Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of NeurosciencesUniversity of BarcelonaBarcelonaSpain
| | - Kristine B. Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and CognitionUniversity of OsloOsloNorway
| | - Enikő Zsoldos
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Warneford HospitalUniversity of OxfordOxfordUK
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11
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Topiwala A, Mankia K, Bell S, Webb A, Ebmeier KP, Howard I, Wang C, Alfaro-Almagro F, Miller K, Burgess S, Smith S, Nichols TE. Association of gout with brain reserve and vulnerability to neurodegenerative disease. Nat Commun 2023; 14:2844. [PMID: 37202397 PMCID: PMC10195870 DOI: 10.1038/s41467-023-38602-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 05/09/2023] [Indexed: 05/20/2023] Open
Abstract
Studies of neurodegenerative disease risk in gout are contradictory. Relationships with neuroimaging markers of brain structure, which may offer insights, are uncertain. Here we investigated associations between gout, brain structure, and neurodegenerative disease incidence. Gout patients had smaller global and regional brain volumes and markers of higher brain iron, using both observational and genetic approaches. Participants with gout also had higher incidence of all-cause dementia, Parkinson's disease, and probable essential tremor. Risks were strongly time dependent, whereby associations with incident dementia were highest in the first 3 years after gout diagnosis. These findings suggest gout is causally related to several measures of brain structure. Lower brain reserve amongst gout patients may explain their higher vulnerability to multiple neurodegenerative diseases. Motor and cognitive impairments may affect gout patients, particularly in early years after diagnosis.
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Affiliation(s)
- Anya Topiwala
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK.
| | - Kulveer Mankia
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds and NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Chapel Allerton Hospital, Leeds, UK
| | - Steven Bell
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Alastair Webb
- Wolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Isobel Howard
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai, China
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla Miller
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Stephen Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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12
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Nyberg L, Andersson M, Lundquist A, Baaré WFC, Bartrés-Faz D, Bertram L, Boraxbekk CJ, Brandmaier AM, Demnitz N, Drevon CA, Duezel S, Ebmeier KP, Ghisletta P, Henson R, Jensen DEA, Kievit RA, Knights E, Kühn S, Lindenberger U, Plachti A, Pudas S, Roe JM, Madsen KS, Solé-Padullés C, Sommerer Y, Suri S, Zsoldos E, Fjell AM, Walhovd KB. Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates. Cereb Cortex 2023; 33:5075-5081. [PMID: 36197324 PMCID: PMC10151879 DOI: 10.1093/cercor/bhac400] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 11/13/2022] Open
Abstract
It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.
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Affiliation(s)
- Lars Nyberg
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Micael Andersson
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Department of Statistics, USBE, Umeå University, Umeå S-90187, Sweden
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Lars Bertram
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Carl-Johan Boraxbekk
- Department of Radiation Sciences (Radiology), Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Faculty of Medical and Health Sciences, Institute for Clinical Medicine, University of Copenhagen, 2400 Copenhagen, Denmark
- Department of Neurology, Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital - Bispebjerg and Frederiksberg, 2400 Copenhagen, Denmark
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- MSB Medical School Berlin, 14197 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Christian A Drevon
- Vitas AS, Science Park, 0349 Oslo, Norway
- Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo Norway
| | - Sandra Duezel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, 1204 Geneva, Switzerland
- UniDistance Suisse, 3900 Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, 1204 Geneva, Switzerland
| | - Richard Henson
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Daria E A Jensen
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, OX3 9DU Oxford, UK
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Ethan Knights
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 7EF, England
| | - Simone Kühn
- Lise Meitner Group for Environmental Neuroscience, Max Planck Institute for Human Development & Clinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Max Plank UCL Centre for Computational Psychiatry and Ageing Research, 14195 Berlin, Germany, and London, UK
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, 901 87 Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - James M Roe
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, 2200 Copenhagen N, Denmark
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institut de Neurociències, Universitat de Barcelona, and Institut d’Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), 08036 Barcelona, Spain
| | - Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, 23562 Lübeck, Germany
| | - Sana Suri
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, OX3 7JX Oxford, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Center for Computational Radiology and Artificial Intelligence, Oslo University Hospital, 0373 Oslo, Norway
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13
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Carver RB, Fredheim NAG, Mowinckel AM, Ebmeier KP, Friedman BB, Rosness TA, Drevon CA, Suri S, Baaré WFC, Zsoldos E, Solé-Padullés C, Bartrés-Faz D, Ghisletta P, Nawijn L, Düzel S, Madsen KS, Fjell AM, Lindenberger U, Walhovd KB, Budin-Ljøsne I. People's interest in brain health testing: Findings from an international, online cross-sectional survey. Front Public Health 2022; 10:998302. [PMID: 36339192 PMCID: PMC9631023 DOI: 10.3389/fpubh.2022.998302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/26/2022] [Indexed: 01/26/2023] Open
Abstract
Brain health entails mental wellbeing and cognitive health in the absence of brain disorders. The past decade has seen an explosion of tests, cognitive and biological, to predict various brain conditions, such as Alzheimer's Disease. In line with these current developments, we investigated people's willingness and reasons to-or not to-take a hypothetical brain health test to learn about risk of developing a brain disease, in a cross-sectional multilanguage online survey. The survey was part of the Global Brain Health Survey, open to the public from 4th June 2019 to 31st August 2020. Respondents were largely recruited via European brain councils and research organizations. 27,590 people responded aged 18 years or older and were predominantly women (71%), middle-aged or older (>40 years; 83%), and highly educated (69%). Responses were analyzed to explore the relationship between demographic variables and responses. Results We found high public interest in brain health testing: over 91% would definitely or probably take a brain health test and 86% would do so even if it gave information about a disease that cannot be treated or prevented. The main reason for taking a test was the ability to respond if one was found to be at risk of brain disease, such as changing lifestyle, seeking counseling or starting treatment. Higher interest in brain health testing was found in men, respondents with lower education levels and those with poor self-reported cognitive health. Conclusion High public interest in brain health and brain health testing in certain segments of society, coupled with an increase of commercial tests entering the market, is likely to put pressure on public health systems to inform the public about brain health testing in years to come.
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Affiliation(s)
- Rebecca B. Carver
- Department of Communication, Norwegian Institute of Public Health, Oslo, Norway,*Correspondence: Rebecca B. Carver
| | | | - Athanasia Monika Mowinckel
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Barbara Bodorkos Friedman
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Tor Atle Rosness
- Reviews and Health Technology Assessments Cluster, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian A. Drevon
- Department Nutrition, Faculty of Medicine, Institute Basic Medical Sciences, University of Oslo, Oslo, Norway,Vitas AS, Oslo Science Park, Oslo, Norway
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - William F. C. Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
| | - Eniko Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences & Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences & Institute of Neurosciences, University of Barcelona, Barcelona, Spain,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland,UniDistance Suisse, Brig, Switzerland,Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark,Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Anders M. Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Kristine B. Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
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14
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Topiwala A, Taschler B, Ebmeier KP, Smith S, Zhou H, Levey DF, Codd V, Samani NJ, Gelernter J, Nichols TE, Burgess S. Alcohol consumption and telomere length: Mendelian randomization clarifies alcohol's effects. Mol Psychiatry 2022; 27:4001-4008. [PMID: 35879401 PMCID: PMC9718662 DOI: 10.1038/s41380-022-01690-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 06/23/2022] [Accepted: 06/29/2022] [Indexed: 02/07/2023]
Abstract
Alcohol's impact on telomere length, a proposed marker of biological aging, is unclear. We performed the largest observational study to date (in n = 245,354 UK Biobank participants) and compared findings with Mendelian randomization (MR) estimates. Two-sample MR used data from 472,174 participants in a recent genome-wide association study (GWAS) of telomere length. Genetic variants were selected on the basis of associations with alcohol consumption (n = 941,280) and alcohol use disorder (AUD) (n = 57,564 cases). Non-linear MR employed UK Biobank individual data. MR analyses suggested a causal relationship between alcohol traits, more strongly for AUD, and telomere length. Higher genetically-predicted AUD (inverse variance-weighted (IVW) β = -0.06, 95% confidence interval (CI): -0.10 to -0.02, p = 0.001) was associated with shorter telomere length. There was a weaker association with genetically-predicted alcoholic drinks weekly (IVW β = -0.07, CI: -0.14 to -0.01, p = 0.03). Results were consistent across methods and independent from smoking. Non-linear analyses indicated a potential threshold relationship between alcohol and telomere length. Our findings indicate that alcohol consumption may shorten telomere length. There are implications for age-related diseases.
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Affiliation(s)
- A Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK.
| | - B Taschler
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - K P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK
| | - S Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - H Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - D F Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - V Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - N J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - J Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - T E Nichols
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - S Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0SR, UK
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, CB1 8RN, UK
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15
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Binnewies J, Nawijn L, Brandmaier AM, Baaré WFC, Bartrés-Faz D, Drevon CA, Düzel S, Fjell AM, Han LKM, Knights E, Lindenberger U, Milaneschi Y, Mowinckel AM, Nyberg L, Plachti A, Madsen KS, Solé-Padullés C, Suri S, Walhovd KB, Zsoldos E, Ebmeier KP, Penninx BWJH. Associations of depression and regional brain structure across the adult lifespan: Pooled analyses of six population-based and two clinical cohort studies in the European Lifebrain consortium. Neuroimage Clin 2022; 36:103180. [PMID: 36088843 PMCID: PMC9467888 DOI: 10.1016/j.nicl.2022.103180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/08/2022] [Accepted: 08/30/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Major depressive disorder has been associated with lower prefrontal thickness and hippocampal volume, but it is unknown whether this association also holds for depressive symptoms in the general population. We investigated associations of depressive symptoms and depression status with brain structures across population-based and patient-control cohorts, and explored whether these associations are similar over the lifespan and across sexes. METHODS We included 3,447 participants aged 18-89 years from six population-based and two clinical patient-control cohorts of the European Lifebrain consortium. Cross-sectional meta-analyses using individual person data were performed for associations of depressive symptoms and depression status with FreeSurfer-derived thickness of bilateral rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC), and hippocampal and total grey matter volume (GMV), separately for population-based and clinical cohorts. RESULTS Across patient-control cohorts, depressive symptoms and presence of mild-to-severe depression were associated with lower mOFC thickness (rsymptoms = -0.15/ rstatus = -0.22), rACC thickness (rsymptoms = -0.20/ rstatus = -0.25), hippocampal volume (rsymptoms = -0.13/ rstatus = 0.13) and total GMV (rsymptoms = -0.21/ rstatus = -0.25). Effect sizes were slightly larger for presence of moderate-to-severe depression. Associations were similar across age groups and sex. Across population-based cohorts, no associations between depression and brain structures were observed. CONCLUSIONS Fitting with previous meta-analyses, depressive symptoms and depression status were associated with lower mOFC, rACC thickness, and hippocampal and total grey matter volume in clinical patient-control cohorts, although effect sizes were small. The absence of consistent associations in population-based cohorts with mostly mild depressive symptoms, suggests that significantly lower thickness and volume of the studied brain structures are only detectable in clinical populations with more severe depressive symptoms.
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Affiliation(s)
- Julia Binnewies
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands.
| | - Laura Nawijn
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Department of Psychology, MSB Medical School Berlin, Berlin, Germany
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo & Vitas Ltd, Oslo Science Park, Oslo, Norway
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Ethan Knights
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Yuri Milaneschi
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | | | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Anna Plachti
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Sana Suri
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Enikő Zsoldos
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, United Kingdom
| | - Brenda W J H Penninx
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
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16
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Walhovd KB, Nyberg L, Lindenberger U, Amlien IK, Sørensen Ø, Wang Y, Mowinckel AM, Kievit RA, Ebmeier KP, Bartrés-Faz D, Kühn S, Boraxbekk CJ, Ghisletta P, Madsen KS, Baaré WFC, Zsoldos E, Magnussen F, Vidal-Piñeiro D, Penninx B, Fjell AM. Brain aging differs with cognitive ability regardless of education. Sci Rep 2022; 12:13886. [PMID: 35974034 PMCID: PMC9381768 DOI: 10.1038/s41598-022-17727-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/29/2022] [Indexed: 11/23/2022] Open
Abstract
Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal cognitively healthy brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up for up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway.
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, The Netherlands, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences & Institute of Neurosciences, Universitat de Barcelona, and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Clinic and Policlinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carl-Johan Boraxbekk
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva, Switzerland
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - Willliam F C Baaré
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
- Welcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Fredrik Magnussen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
| | - Brenda Penninx
- Amsterdam Neuroscience, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Blindern, POB1094, 0317, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
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17
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Subramaniapillai S, Suri S, Barth C, Maximov II, Voldsbekk I, van der Meer D, Gurholt TP, Beck D, Draganski B, Andreassen OA, Ebmeier KP, Westlye LT, de Lange AG. Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort. Hum Brain Mapp 2022; 43:3759-3774. [PMID: 35460147 PMCID: PMC9294301 DOI: 10.1002/hbm.25882] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/24/2022] [Accepted: 04/05/2022] [Indexed: 12/13/2022] Open
Abstract
Cardiometabolic risk (CMR) factors are associated with accelerated brain aging and increased risk for sex-dimorphic illnesses such as Alzheimer's disease (AD). Yet, it is unknown how CMRs interact with sex and apolipoprotein E-ϵ4 (APOE4), a known genetic risk factor for AD, to influence brain age across different life stages. Using age prediction based on multi-shell diffusion-weighted imaging data in 21,308 UK Biobank participants, we investigated whether associations between white matter Brain Age Gap (BAG) and body mass index (BMI), waist-to-hip ratio (WHR), body fat percentage (BF%), and APOE4 status varied (i) between males and females, (ii) according to age at menopause in females, and (iii) across different age groups in males and females. We report sex differences in associations between BAG and all three CMRs, with stronger positive associations among males compared to females. Independent of APOE4 status, higher BAG (older brain age relative to chronological age) was associated with greater BMI, WHR, and BF% in males, whereas in females, higher BAG was associated with greater WHR, but not BMI and BF%. These divergent associations were most prominent within the oldest group of females (66-81 years), where greater BF% was linked to lower BAG. Earlier menopause transition was associated with higher BAG, but no interactions were found with CMRs. In conclusion, the findings point to sex- and age-specific associations between CMRs and brain age. Incorporating sex as a factor of interest in studies addressing CMR may promote sex-specific precision medicine, consequently improving health care for both males and females.
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Affiliation(s)
- Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
- Department of Psychology, Faculty of ScienceMcGill UniversityMontrealQuebecCanada
- Department of PsychologyUniversity of OsloOsloNorway
| | - Sana Suri
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Claudia Barth
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Ivan I. Maximov
- Department of PsychologyUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- Department of Health and FunctioningWestern Norway University of Applied SciencesBergenNorway
| | - Irene Voldsbekk
- Department of PsychologyUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
| | - Dennis van der Meer
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- School of Mental Health and Neuroscience, Faculty of Health Medicine and Life SciencesMaastricht UniversityMaastrichtThe Netherlands
| | - Tiril P. Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
| | - Dani Beck
- Department of PsychologyUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | | | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and AddictionOslo University Hospital and University of OsloOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | - Ann‐Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
- Department of PsychologyUniversity of OsloOsloNorway
- Department of PsychiatryUniversity of OxfordOxfordUK
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18
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Topiwala A, Wang C, Ebmeier KP, Burgess S, Bell S, Levey DF, Zhou H, McCracken C, Roca-Fernández A, Petersen SE, Raman B, Husain M, Gelernter J, Miller KL, Smith SM, Nichols TE. Associations between moderate alcohol consumption, brain iron, and cognition in UK Biobank participants: Observational and mendelian randomization analyses. PLoS Med 2022; 19:e1004039. [PMID: 35834561 PMCID: PMC9282660 DOI: 10.1371/journal.pmed.1004039] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/01/2022] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Brain iron deposition has been linked to several neurodegenerative conditions and reported in alcohol dependence. Whether iron accumulation occurs in moderate drinkers is unknown. Our objectives were to investigate evidence in support of causal relationships between alcohol consumption and brain iron levels and to examine whether higher brain iron represents a potential pathway to alcohol-related cognitive deficits. METHODS AND FINDINGS Observational associations between brain iron markers and alcohol consumption (n = 20,729 UK Biobank participants) were compared with associations with genetically predicted alcohol intake and alcohol use disorder from 2-sample mendelian randomization (MR). Alcohol intake was self-reported via a touchscreen questionnaire at baseline (2006 to 2010). Participants with complete data were included. Multiorgan susceptibility-weighted magnetic resonance imaging (9.60 ± 1.10 years after baseline) was used to ascertain iron content of each brain region (quantitative susceptibility mapping (QSM) and T2*) and liver tissues (T2*), a marker of systemic iron. Main outcomes were susceptibility (χ) and T2*, measures used as indices of iron deposition. Brain regions of interest included putamen, caudate, hippocampi, thalami, and substantia nigra. Potential pathways to alcohol-related iron brain accumulation through elevated systemic iron stores (liver) were explored in causal mediation analysis. Cognition was assessed at the scan and in online follow-up (5.82 ± 0.86 years after baseline). Executive function was assessed with the trail-making test, fluid intelligence with puzzle tasks, and reaction time by a task based on the "Snap" card game. Mean age was 54.8 ± 7.4 years and 48.6% were female. Weekly alcohol consumption was 17.7 ± 15.9 units and never drinkers comprised 2.7% of the sample. Alcohol consumption was associated with markers of higher iron (χ) in putamen (β = 0.08 standard deviation (SD) [95% confidence interval (CI) 0.06 to 0.09], p < 0.001), caudate (β = 0.05 [0.04 to 0.07], p < 0.001), and substantia nigra (β = 0.03 [0.02 to 0.05], p < 0.001) and lower iron in the thalami (β = -0.06 [-0.07 to -0.04], p < 0.001). Quintile-based analyses found these associations in those consuming >7 units (56 g) alcohol weekly. MR analyses provided weak evidence these relationships are causal. Genetically predicted alcoholic drinks weekly positively associated with putamen and hippocampus susceptibility; however, these associations did not survive multiple testing corrections. Weak evidence for a causal relationship between genetically predicted alcohol use disorder and higher putamen susceptibility was observed; however, this was not robust to multiple comparisons correction. Genetically predicted alcohol use disorder was associated with serum iron and transferrin saturation. Elevated liver iron was observed at just >11 units (88 g) alcohol weekly c.f. <7 units (56 g). Systemic iron levels partially mediated associations of alcohol intake with brain iron. Markers of higher basal ganglia iron associated with slower executive function, lower fluid intelligence, and slower reaction times. The main limitations of the study include that χ and T2* can reflect changes in myelin as well as iron, alcohol use was self-reported, and MR estimates can be influenced by genetic pleiotropy. CONCLUSIONS To the best of our knowledge, this study represents the largest investigation of moderate alcohol consumption and iron homeostasis to date. Alcohol consumption above 7 units weekly associated with higher brain iron. Iron accumulation represents a potential mechanism for alcohol-related cognitive decline.
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Affiliation(s)
- Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Steven Bell
- Department of Clinical Neurosciences, University of Cambridge, United Kingdom
| | - Daniel F. Levey
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Hang Zhou
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Celeste McCracken
- 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, United Kingdom
| | | | - Steffen E. Petersen
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, United Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health NHS Trust, West Smithfield, London, United Kingdom
- Health Data Research UK, London, United Kingdom
- Alan Turing Institute, London, United Kingdom
| | - Betty Raman
- 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, United Kingdom
| | - Masud Husain
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- Division of Clinical Neurology, John Radcliffe Hospital, Oxford University Hospitals Trust, Oxford, United Kingdom
| | - Joel Gelernter
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, United States of America
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, United States of America
| | - Karla L. Miller
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
| | - Thomas E. Nichols
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), Oxford University, Oxford, United Kingdom
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19
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Budin-Ljøsne I, Mowinckel AM, Friedman BB, Ebmeier KP, Drevon CA, Carver RB, Zsoldos E, Fredheim NAG, Sørensen Ø, Baaré WFC, Madsen KS, Fjell AM, Kievit RA, Ghisletta P, Bartrés-Faz D, Nawijn L, Solé-Padullés C, Walhovd KB, Düzel S, Zasyekina L, Iulita MF, Ferretti MT. Public perceptions of brain health: an international, online cross-sectional survey. BMJ Open 2022; 12:e057999. [PMID: 35437254 PMCID: PMC9016409 DOI: 10.1136/bmjopen-2021-057999] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/24/2022] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVES To investigate public perspectives on brain health. DESIGN Cross-sectional multilanguage online survey. SETTING Lifebrain posted the survey on its website and social media and shared it with stakeholders. The survey was open from 4 June 2019 to 31 August 2020. PARTICIPANTS n=27 590 aged ≥18 years from 81 countries in five continents completed the survey. The respondents were predominantly women (71%), middle aged (41-60 years; 37%) or above (>60 years; 46%), highly educated (69%) and resided in Europe (98%). MAIN OUTCOME MEASURES Respondents' views were assessed regarding factors that may influence brain health, life periods considered important to look after the brain and diseases and disorders associated with the brain. We run exploratory linear models at a 99% level of significance to assess correlates of the outcome variables, adjusting for likely confounders in a targeted fashion. RESULTS Of all significant effects, the respondents recognised the impact of lifestyle factors on brain health but had relatively less awareness of the role socioeconomic factors might play. Most respondents rated all life periods as important for the brain (95%-96%), although the prenatal period was ranked significantly lower (84%). Equally, women and highly educated respondents more often rated factors and life periods to be important for brain health. Ninety-nine per cent of respondents associated Alzheimer's disease and dementia with the brain. The respondents made a connection between mental health and the brain, and mental disorders such as schizophrenia and depression were significantly more often considered to be associated with the brain than neurological disorders such as stroke and Parkinson's disease. Few respondents (<32%) associated cancer, hypertension, diabetes and arthritis with the brain. CONCLUSIONS Differences in perceptions of brain health were noted among specific segments of the population. Policies providing information about brain-friendly health behaviours and targeting people less likely to have relevant experience may be needed.
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Affiliation(s)
| | - Athanasia Monika Mowinckel
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Barbara Bodorkos Friedman
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | | | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
- Vitas AS, Oslo, Norway
| | - Rebecca Bruu Carver
- Department of Communication, Norwegian Institute of Public Health, Oslo, Norway
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford, UK
| | | | - Øystein Sørensen
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - William Frans Christiaan Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, København, Denmark
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, København, Denmark
| | - Anders M Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- Swiss National Centre of Competence in Research LIVES, Geneva, Switzerland
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences and Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences and Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Kristine B Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Larisa Zasyekina
- Department of General and Clinical Psychology, Lesya Ukrainka Volyn National University, Luc'k, Ukraine
| | - Maria Florencia Iulita
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
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20
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Jansen MG, Griffanti L, Mackay CE, Anatürk M, Melazzini L, Lange AMGD, Filippini N, Zsoldos E, Wiegertjes K, Leeuw FED, Singh-Manoux A, Kivimäki M, Ebmeier KP, Suri S. Association of cerebral small vessel disease burden with brain structure and cognitive and vascular risk trajectories in mid-to-late life. J Cereb Blood Flow Metab 2022; 42:600-612. [PMID: 34610763 PMCID: PMC8943617 DOI: 10.1177/0271678x211048411] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
We characterize the associations of total cerebral small vessel disease (SVD) burden with brain structure, trajectories of vascular risk factors, and cognitive functions in mid-to-late life. Participants were 623 community-dwelling adults from the Whitehall II Imaging Sub-study with multi-modal MRI (mean age 69.96, SD = 5.18, 79% men). We used linear mixed-effects models to investigate associations of SVD burden with up to 25-year retrospective trajectories of vascular risk and cognitive performance. General linear modelling was used to investigate concurrent associations with grey matter (GM) density and white matter (WM) microstructure, and whether these associations were modified by cognitive status (Montreal Cognitive Asessment [MoCA] scores of < 26 vs. ≥ 26). Severe SVD burden in older age was associated with higher mean arterial pressure throughout midlife (β = 3.36, 95% CI [0.42-6.30]), and faster cognitive decline in letter fluency (β = -0.07, 95% CI [-0.13--0.01]), and verbal reasoning (β = -0.05, 95% CI [-0.11--0.001]). Moreover, SVD burden was related to lower GM volumes in 9.7% of total GM, and widespread WM microstructural decline (FWE-corrected p < 0.05). The latter association was most pronounced in individuals who demonstrated cognitive impairments on MoCA (MoCA < 26; F3,608 = 2.14, p = 0.007). These findings highlight the importance of managing midlife vascular health to preserve brain structure and cognitive function in old age.
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Affiliation(s)
- Michelle G Jansen
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands.,Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ludovica Griffanti
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging (Oxford Centres for Functional MRI of the Brain & Human Brain Activity) University of Oxford, Oxford, UK
| | - Clare E Mackay
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging (Oxford Centres for Functional MRI of the Brain & Human Brain Activity) University of Oxford, Oxford, UK
| | - Melis Anatürk
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Centre for Medical Image Computing, Department of Computer Science, 4919University College London, University College London, London, UK
| | - Luca Melazzini
- Wellcome Centre for Integrative Neuroimaging (Oxford Centres for Functional MRI of the Brain & Human Brain Activity) University of Oxford, Oxford, UK.,Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
| | - Ann-Marie G de Lange
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Department of Psychology, 6305University of Oslo, University of Oslo, Oslo, Norway
| | | | - Enikő Zsoldos
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging (Oxford Centres for Functional MRI of the Brain & Human Brain Activity) University of Oxford, Oxford, UK
| | - Kim Wiegertjes
- Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, 4919University College London, University College London, London, UK.,INSERM, Epidemiology of Ageing and Neurogenerative Diseases, Université de Paris, Paris, France
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, 4919University College London, University College London, London, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK
| | - Sana Suri
- Department of Psychiatry, 6396University of Oxford, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging (Oxford Centres for Functional MRI of the Brain & Human Brain Activity) University of Oxford, Oxford, UK
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21
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de Lange AG, Anatürk M, Rokicki J, Han LKM, Franke K, Alnæs D, Ebmeier KP, Draganski B, Kaufmann T, Westlye LT, Hahn T, Cole JH. Mind the gap: Performance metric evaluation in brain-age prediction. Hum Brain Mapp 2022; 43:3113-3129. [PMID: 35312210 PMCID: PMC9188975 DOI: 10.1002/hbm.25837] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/04/2022] [Accepted: 03/06/2022] [Indexed: 12/21/2022] Open
Abstract
Estimating age based on neuroimaging-derived data has become a popular approach to developing markers for brain integrity and health. While a variety of machine-learning algorithms can provide accurate predictions of age based on brain characteristics, there is significant variation in model accuracy reported across studies. We predicted age in two population-based datasets, and assessed the effects of age range, sample size and age-bias correction on the model performance metrics Pearson's correlation coefficient (r), the coefficient of determination (R2 ), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results showed that these metrics vary considerably depending on cohort age range; r and R2 values are lower when measured in samples with a narrower age range. RMSE and MAE are also lower in samples with a narrower age range due to smaller errors/brain age delta values when predictions are closer to the mean age of the group. Across subsets with different age ranges, performance metrics improve with increasing sample size. Performance metrics further vary depending on prediction variance as well as mean age difference between training and test sets, and age-bias corrected metrics indicate high accuracy-also for models showing poor initial performance. In conclusion, performance metrics used for evaluating age prediction models depend on cohort and study-specific data characteristics, and cannot be directly compared across different studies. Since age-bias corrected metrics generally indicate high accuracy, even for poorly performing models, inspection of uncorrected model results provides important information about underlying model attributes such as prediction variance.
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Affiliation(s)
- Ann‐Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanne,Department of PsychologyUniversity of OsloOslo,Department of PsychiatryUniversity of OxfordOxford
| | - Melis Anatürk
- Department of PsychiatryUniversity of OxfordOxford,Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
| | - Jaroslav Rokicki
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway,Centre of Research and Education in Forensic PsychiatryOslo University HospitalOsloNorway
| | - Laura K. M. Han
- Department of PsychiatryAmsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Katja Franke
- Structural Brain Mapping Group, Department of NeurologyJena University HospitalJenaGermany
| | - Dag Alnæs
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway
| | | | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanne,Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Tobias Kaufmann
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway,Tübingen Center for Mental Health, Department of Psychiatry and PsychotherapyUniversity of TübingenTübingenGermany
| | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOslo,NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway,KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
| | - Tim Hahn
- Institute of Translational PsychiatryUniversity of MünsterMünsterGermany
| | - James H. Cole
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK,Dementia Research Centre, Queen Square Institute of NeurologyUniversity College LondonLondonUK
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22
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Solé-Padullés C, Macià D, Andersson M, Stiernstedt M, Pudas S, Düzel S, Zsoldos E, Ebmeier KP, Binnewies J, Drevon CA, Brandmaier AM, Mowinckel AM, Fjell AM, Madsen KS, Baaré WFC, Lindenberger U, Nyberg L, Walhovd KB, Bartrés-Faz D. No Association Between Loneliness, Episodic Memory and Hippocampal Volume Change in Young and Healthy Older Adults: A Longitudinal European Multicenter Study. Front Aging Neurosci 2022; 14:795764. [PMID: 35283753 PMCID: PMC8905540 DOI: 10.3389/fnagi.2022.795764] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 01/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background Loneliness is most prevalent during adolescence and late life and has been associated with mental health disorders as well as with cognitive decline during aging. Associations between longitudinal measures of loneliness and verbal episodic memory and brain structure should thus be investigated. Methods We sought to determine associations between loneliness and verbal episodic memory as well as loneliness and hippocampal volume trajectories across three longitudinal cohorts within the Lifebrain Consortium, including children, adolescents (N = 69, age range 10-15 at baseline examination) and older adults (N = 1468 over 60). We also explored putative loneliness correlates of cortical thinning across the entire cortical mantle. Results Loneliness was associated with worsening of verbal episodic memory in one cohort of older adults. Specifically, reporting medium to high levels of loneliness over time was related to significantly increased memory loss at follow-up examinations. The significance of the loneliness-memory change association was lost when eight participants were excluded after having developed dementia in any of the subsequent follow-up assessments. No significant structural brain correlates of loneliness were found, neither hippocampal volume change nor cortical thinning. Conclusion In the present longitudinal European multicenter study, the association between loneliness and episodic memory was mainly driven by individuals exhibiting progressive cognitive decline, which reinforces previous findings associating loneliness with cognitive impairment and dementia.
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Affiliation(s)
- Cristina Solé-Padullés
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain,*Correspondence: Cristina Solé-Padullés,
| | - Dídac Macià
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain,ISGlobal, Hospital Clínic – University of Barcelona, Barcelona, Spain
| | - Micael Andersson
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Mikael Stiernstedt
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Enikő Zsoldos
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Julia Binnewies
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Christian A. Drevon
- Vitas Ltd., Oslo, Norway,Department of Nutrition, Institute of Basic Medical Sciences, Faculty Medicine, University of Oslo, Oslo, Norway
| | - Andreas M. Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Athanasia M. Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders M. Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark,Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark
| | - William F. C. Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Lars Nyberg
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden,Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Kristine B. Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - David Bartrés-Faz
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain,August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
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23
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Walhovd KB, Fjell AM, Wang Y, Amlien IK, Mowinckel AM, Lindenberger U, Düzel S, Bartrés-Faz D, Ebmeier KP, Drevon CA, Baaré WFC, Ghisletta P, Johansen LB, Kievit RA, Henson RN, Madsen KS, Nyberg L, R Harris J, Solé-Padullés C, Pudas S, Sørensen Ø, Westerhausen R, Zsoldos E, Nawijn L, Lyngstad TH, Suri S, Penninx B, Rogeberg OJ, Brandmaier AM. Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts. Cereb Cortex 2022; 32:839-854. [PMID: 34467389 PMCID: PMC8841563 DOI: 10.1093/cercor/bhab248] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 12/19/2022] Open
Abstract
Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo 0424, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo 0424, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin D-14195, Germany
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Barcelona 08036, Spain
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Christian A Drevon
- Vitas AS, Oslo 0349, Norway
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo 0317, Norway
| | - William F C Baaré
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
- UniDistance Suisse, Brig, Brig 3900, Switzerland
- Swiss National Centre of Competence in Research LIVES, University of Geneva, Geneva 1212, Switzerland
| | - Louise Baruël Johansen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, Glostrup 2600, Denmark
| | - Rogier A Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen 6500 GL, The Netherlands
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Kathrine Skak Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Radiography, Department of Technology, University College Copenhagen, Copenhagen 1799, Denmark
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå 901 87, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå 901 87, Sweden
- Department of Radiation Sciences, Radiology, Umeå University, 901 87 Umeå, Sweden
| | - Jennifer R Harris
- Division for Health Data and Digitalisation, The Norwegian Institute of Public Health, Oslo 0213, Norway
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Barcelona 08036, Spain
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå 901 87, Sweden
- Department of Radiation Sciences, Radiology, Umeå University, 901 87 Umeå, Sweden
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - René Westerhausen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo 0317, Norway
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam 1081 HJ, The Netherlands
| | - Torkild Hovde Lyngstad
- Department of Sociology and Human Geography, Faculty of Social Sciences, University of Oslo, Oslo 0317, Norway
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, UK
| | - Brenda Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam 1081 HJ, The Netherlands
| | | | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin D-14195, Germany
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24
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Schindler LS, Subramaniapillai S, Barth C, van der Meer D, Pedersen ML, Kaufmann T, Maximov II, Linge J, Leinhard OD, Beck D, Gurholt TP, Voldsbekk I, Suri S, Ebmeier KP, Draganski B, Andreassen OA, Westlye LT, de Lange AMG. Associations between abdominal adipose tissue, reproductive span, and brain characteristics in post-menopausal women. Neuroimage Clin 2022; 36:103239. [PMID: 36451350 PMCID: PMC9668664 DOI: 10.1016/j.nicl.2022.103239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/06/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022]
Abstract
The menopause transition involves changes in oestrogens and adipose tissue distribution, which may influence female brain health post-menopause. Although increased central fat accumulation is linked to risk of cardiometabolic diseases, adipose tissue also serves as the primary biosynthesis site of oestrogens post-menopause. It is unclear whether different types of adipose tissue play diverging roles in female brain health post-menopause, and whether this depends on lifetime oestrogen exposure, which can have lasting effects on the brain and body even after menopause. Using the UK Biobank sample, we investigated associations between brain characteristics and visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) in 10,251 post-menopausal females, and assessed whether the relationships varied depending on length of reproductive span (age at menarche to age at menopause). To parse the effects of common genetic variation, we computed polygenic scores for reproductive span. The results showed that higher VAT and ASAT were both associated with higher grey and white matter brain age, and greater white matter hyperintensity load. The associations varied positively with reproductive span, indicating more prominent associations between adipose tissue and brain measures in females with a longer reproductive span. The effects were in general small, but could not be fully explained by genetic variation or relevant confounders. Our findings indicate that associations between abdominal adipose tissue and brain health post-menopause may partly depend on individual differences in cumulative oestrogen exposure during reproductive years, emphasising the complexity of neural and endocrine ageing processes in females.
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Affiliation(s)
- Louise S Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland; Department of Psychology, University of Oslo, Oslo, Norway.
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland; Department of Psychology, University of Oslo, Oslo, Norway
| | - Claudia Barth
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, The Netherlands
| | - Mads L Pedersen
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | - Ivan I Maximov
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Jennifer Linge
- AMRA Medical AB, Linköping, Sweden; Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- AMRA Medical AB, Linköping, Sweden; Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland; Dept. of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland; Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychiatry, University of Oxford, Oxford, UK
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Topiwala A, Ebmeier KP, Maullin-Sapey T, Nichols TE. Alcohol consumption and MRI markers of brain structure and function: Cohort study of 25,378 UK Biobank participants. Neuroimage Clin 2022; 35:103066. [PMID: 35653911 PMCID: PMC9163992 DOI: 10.1016/j.nicl.2022.103066] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 12/15/2022]
Abstract
Moderate alcohol consumption is widespread but its impact on brain structure and function is contentious. The relationship between alcohol intake and structural and functional neuroimaging indices, the threshold intake for associations, and whether population subgroups are at higher risk of alcohol-related brain harm remain unclear. 25,378 UK Biobank participants (mean age 54.9 ± 7.4 years, 12,254 female) underwent multi-modal MRI 9.6 ± 1.1 years after study baseline. Alcohol use was self-reported at baseline (2006-10). T1-weighted, diffusion weighted and resting state images were examined. Lower total grey matter volumes were observed in those drinking as little as 7-14 units (56-112 g) weekly. Higher alcohol consumption was associated with multiple markers of white matter microstructure, including lower fractional anisotropy, higher mean and radial diffusivity in a spatially distributed pattern across the brain. Associations between functional connectivity and alcohol intake were observed in the default mode, central executive, attention, salience and visual resting state networks. Relationships between total grey matter and alcohol were stronger than other modifiable factors, including blood pressure and smoking, and robust to unobserved confounding. Frequent binging, higher blood pressure and BMI steepened the negative association between alcohol and total grey matter volume. In this large observational cohort study, alcohol consumption was associated with multiple structural and functional MRI markers in mid- to late-life.
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Affiliation(s)
- Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford OX3 7LF, UK.
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Thomas Maullin-Sapey
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford OX3 7LF, UK
| | - Thomas E Nichols
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford OX3 7LF, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
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26
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Anatürk M, Patel R, Georgiopoulos G, Newby D, Topiwala AG, de Lange AG, Cole JH, Jansen MG, Ebmeier KP, Singh‐Manoux A, Kivimaki M, Suri S. Development and external validation of a novel dementia risk prediction score in the UK Biobank cohort. Alzheimers Dement 2021. [DOI: 10.1002/alz.056250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Melis Anatürk
- University of Oxford Oxford United Kingdom
- University College London London United Kingdom
| | - Raihaan Patel
- McGill University Montreal QC Canada
- Douglas Mental Health University Institute Montreal QC Canada
| | | | | | | | - Ann‐Marie G de Lange
- University of Oxford Oxford United Kingdom
- University of Lausanne Lausanne Switzerland
- Oslo University Hospital Oslo Norway
| | | | | | | | - Archana Singh‐Manoux
- University College London London United Kingdom
- Universite de Paris, INSERM Paris France
| | | | - Sana Suri
- University of Oxford Oxford United Kingdom
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Anatürk M, Suri S, Smith SM, Ebmeier KP, Sexton CE. Leisure Activities and Their Relationship With MRI Measures of Brain Structure, Functional Connectivity, and Cognition in the UK Biobank Cohort. Front Aging Neurosci 2021; 13:734866. [PMID: 34867271 PMCID: PMC8635062 DOI: 10.3389/fnagi.2021.734866] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 10/05/2021] [Indexed: 01/15/2023] Open
Abstract
Introduction: This study aimed to evaluate whether engagement in leisure activities is linked to measures of brain structure, functional connectivity, and cognition in early old age. Methods: We examined data collected from 7,152 participants of the United Kingdom Biobank (UK Biobank) study. Weekly participation in six leisure activities was assessed twice and a cognitive battery and 3T MRI brain scan were administered at the second visit. Based on responses collected at two time points, individuals were split into one of four trajectory groups: (1) stable low engagement, (2) stable weekly engagement, (3) low to weekly engagement, and (4) weekly to low engagement. Results: Consistent weekly attendance at a sports club or gym was associated with connectivity of the sensorimotor functional network with the lateral visual (β = 0.12, 95%CI = [0.07, 0.18], FDR q = 2.48 × 10-3) and cerebellar (β = 0.12, 95%CI = [0.07, 0.18], FDR q = 1.23 × 10-4) networks. Visiting friends and family across the two timepoints was also associated with larger volumes of the occipital lobe (β = 0.15, 95%CI = [0.08, 0.21], FDR q = 0.03). Additionally, stable and weekly computer use was associated with global cognition (β = 0.62, 95%CI = [0.35, 0.89], FDR q = 1.16 × 10-4). No other associations were significant (FDR q > 0.05). Discussion: This study demonstrates that not all leisure activities contribute to cognitive health equally, nor is there one unifying neural signature across diverse leisure activities.
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Affiliation(s)
- Melis Anatürk
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Stephen M. Smith
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
| | - Claire E. Sexton
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
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28
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Grydeland H, Sederevičius D, Wang Y, Bartrés-Faz D, Bertram L, Dobricic V, Düzel S, Ebmeier KP, Lindenberger U, Nyberg L, Pudas S, Sexton CE, Solé-Padullés C, Sørensen Ø, Walhovd KB, Fjell AM. Self-reported sleep relates to microstructural hippocampal decline in ß-amyloid positive Adults beyond genetic risk. Sleep 2021; 44:zsab110. [PMID: 33912975 PMCID: PMC8598196 DOI: 10.1093/sleep/zsab110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 04/16/2021] [Indexed: 12/01/2022] Open
Abstract
STUDY OBJECTIVES A critical role linking sleep with memory decay and β-amyloid (Aβ) accumulation, two markers of Alzheimer's disease (AD) pathology, may be played by hippocampal integrity. We tested the hypotheses that worse self-reported sleep relates to decline in memory and intra-hippocampal microstructure, including in the presence of Aβ. METHODS Two-hundred and forty-three cognitively healthy participants, aged 19-81 years, completed the Pittsburgh Sleep Quality Index once, and two diffusion tensor imaging sessions, on average 3 years apart, allowing measures of decline in intra-hippocampal microstructure as indexed by increased mean diffusivity. We measured memory decay at each imaging session using verbal delayed recall. One session of positron emission tomography, in 108 participants above 44 years of age, yielded 23 Aβ positive. Genotyping enabled control for APOE ε4 status, and polygenic scores for sleep and AD, respectively. RESULTS Worse global sleep quality and sleep efficiency related to more rapid reduction of hippocampal microstructure over time. Focusing on efficiency (the percentage of time in bed at night spent asleep), the relation was stronger in presence of Aβ accumulation, and hippocampal integrity decline mediated the relation with memory decay. The results were not explained by genetic risk for sleep efficiency or AD. CONCLUSIONS Worse sleep efficiency related to decline in hippocampal microstructure, especially in the presence of Aβ accumulation, and Aβ might link poor sleep and memory decay. As genetic risk did not account for the associations, poor sleep efficiency might constitute a risk marker for AD, although the driving causal mechanisms remain unknown.
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Affiliation(s)
- Håkon Grydeland
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Donatas Sederevičius
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Yunpeng Wang
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
| | - Lars Bertram
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | | | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK
| | - Lars Nyberg
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | | | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain
| | - Øystein Sørensen
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Kristine B Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, University of Oslo, Oslo, Norway
| | - Anders M Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
- Department of Radiology and Nuclear Medicine, University of Oslo, Oslo, Norway
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29
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Jensen DEA, Leoni V, Klein-Flügge MC, Ebmeier KP, Suri S. Associations of dietary markers with brain volume and connectivity: A systematic review of MRI studies. Ageing Res Rev 2021; 70:101360. [PMID: 33991658 DOI: 10.1016/j.arr.2021.101360] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 04/22/2021] [Accepted: 05/08/2021] [Indexed: 11/20/2022]
Abstract
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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Affiliation(s)
- Daria E A Jensen
- 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.
| | - Virginia Leoni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Italy
| | - Miriam C Klein-Flügge
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Tinsley building, OX1 3SR, UK
| | | | - Sana Suri
- 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
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30
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de Lange AMG, Kaufmann T, Quintana DS, Winterton A, Andreassen OA, Westlye LT, Ebmeier KP. Prominent health problems, socioeconomic deprivation, and higher brain age in lonely and isolated individuals: A population-based study. Behav Brain Res 2021; 414:113510. [PMID: 34358570 DOI: 10.1016/j.bbr.2021.113510] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 07/09/2021] [Accepted: 07/31/2021] [Indexed: 01/12/2023]
Abstract
Loneliness is linked to increased risk for Alzheimer's disease, but little is known about factors potentially contributing to adverse brain health in lonely individuals. In this study, we used data from 24,867 UK Biobank participants to investigate risk factors related to loneliness and estimated brain age based on neuroimaging data. The results showed that on average, individuals who self-reported loneliness on a single yes/no item scored higher on neuroticism, depression, social isolation, and socioeconomic deprivation, performed less physical activity, and had higher BMI compared to individuals who did not report loneliness. In line with studies pointing to a genetic overlap of loneliness with neuroticism and depression, permutation feature importance ranked these factors as the most important for classifying lonely vs. not lonely individuals (ROC AUC = 0.83). While strongly linked to loneliness, neuroticism and depression were not associated with brain age estimates. Conversely, objective social isolation showed a main effect on brain age, and individuals reporting both loneliness and social isolation showed higher brain age relative to controls - as part of a prominent risk profile with elevated scores on socioeconomic deprivation and unhealthy lifestyle behaviours, in addition to neuroticism and depression. While longitudinal studies are required to determine causality, this finding may indicate that the combination of social isolation and a genetic predisposition for loneliness involves a risk for adverse brain health. Importantly, the results underline the complexity in associations between loneliness and adverse health outcomes, where observed risks likely depend on a combination of interlinked variables including genetic as well as social, behavioural, physical, and socioeconomic factors.
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Affiliation(s)
- Ann-Marie G de Lange
- Department of Psychiatry, University of Oxford, Oxford, UK; NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland.
| | - Tobias Kaufmann
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Tübingen Center for Mental Health, Dept. of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Daniel S Quintana
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Adriano Winterton
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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31
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Demnitz N, Stathi A, Withall J, Stainer C, Seager P, De Koning J, Esser P, Wassenaar T, Dawes H, Brooks J, Ebmeier KP, Johansen-Berg H, Sexton CE. Hippocampal maintenance after a 12-month physical activity intervention in older adults: The REACT MRI study. Neuroimage Clin 2021; 35:102762. [PMID: 35361556 PMCID: PMC9421470 DOI: 10.1016/j.nicl.2021.102762] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 07/05/2021] [Accepted: 07/08/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Physical activity interventions have had varying results on modifying hippocampal volume. METHODS The Retirement in Action (REACT) study conducted a randomised-controlled trial of a 12-month physical activity and behaviour maintenance intervention in older adults at risk of mobility impairments. The physical activity sessions were delivered twice weekly for the first twelve weeks, and then reduced to once weekly, to groups of 15 participants. Activities included cardiovascular, strength, balance and flexibility exercises. A sub-sample of participants in the physical activity (N = 54) and control arms (N = 48) underwent a 3 T MRI brain scan and cognitive assessments at baseline, 6- and 12-months (mean age = 76.6 years, 6.8 SD). It was hypothesised that the intervention would lead to a reduced rate of decline in hippocampal volume. Group differences in changes in cognition were also examined. RESULTS As hypothesised, we found a maintenance in left hippocampal volume in the intervention arm, in comparison with the control arm after 12 months (p = 0.027). In a secondary analysis, this effect was attenuated after including age, sex and education level as covariates (p = 0.057). There was no significant between-group difference in the right hippocampus (p = 0.405). Contrary to our hypothesis, we did not find a beneficial effect of the intervention on cognitive outcomes. CONCLUSIONS Our findings suggest that a community-based physical activity intervention can significantly ward-off hippocampal atrophy in older adults. While the lack of effects on cognition may limit the interpretability of our results, our findings of hippocampal maintenance are promising given the potential clinical relevance of protecting the hippocampus from age-related decline.
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Affiliation(s)
- Naiara Demnitz
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, 2650 Hvidovre, Denmark.
| | - Afroditi Stathi
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Janet Withall
- Department for Health, University of Bath, Bath BA2 7AY, UK
| | - Candida Stainer
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Poppy Seager
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | | | - Patrick Esser
- Centre for Movement, Occupation and Rehabilitation Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford OX3 0FL, UK
| | - Thomas Wassenaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Helen Dawes
- Centre for Movement, Occupation and Rehabilitation Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford OX3 0FL, UK
| | - Jonathan Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol BS2 8DX, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Claire E Sexton
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
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Bordin V, Bertani I, Mattioli I, Sundaresan V, McCarthy P, Suri S, Zsoldos E, Filippini N, Mahmood A, Melazzini L, Laganà MM, Zamboni G, Singh-Manoux A, Kivimäki M, Ebmeier KP, Baselli G, Jenkinson M, Mackay CE, Duff EP, Griffanti L. Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets. Neuroimage 2021; 237:118189. [PMID: 34022383 PMCID: PMC8285593 DOI: 10.1016/j.neuroimage.2021.118189] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 04/16/2021] [Accepted: 05/17/2021] [Indexed: 12/31/2022] Open
Abstract
We harmonised measures of WMHs across two studies on healthy ageing. Specific pre-processing strategies can increase comparability across studies. Modelling of biological differences is crucial to provide calibrated measures.
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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Affiliation(s)
- Valentina Bordin
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Ilaria Bertani
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Irene Mattioli
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Italy
| | - Vaanathi Sundaresan
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Paul McCarthy
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sana Suri
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- 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; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Nicola Filippini
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Luca Melazzini
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
| | | | - Giovanna Zamboni
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Italy
| | - Archana Singh-Manoux
- INSERM U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, France; Department of Epidemiology and Public Health, University College London, London, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Clare E Mackay
- 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; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Paediatrics, University of Oxford, Oxford, UK
| | - Ludovica Griffanti
- 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.
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Anatürk M, Kaufmann T, Cole JH, Suri S, Griffanti L, Zsoldos E, Filippini N, Singh‐Manoux A, Kivimäki M, Westlye LT, Ebmeier KP, de Lange AG. Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging. Hum Brain Mapp 2021; 42:1626-1640. [PMID: 33314530 PMCID: PMC7978127 DOI: 10.1002/hbm.25316] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/27/2020] [Accepted: 12/01/2020] [Indexed: 12/17/2022] Open
Abstract
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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Affiliation(s)
- Melis Anatürk
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Tobias Kaufmann
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway
| | - James H. Cole
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Dementia Research Centre, Institute of NeurologyUniversity College LondonLondonUK
| | - Sana Suri
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Ludovica Griffanti
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Enikő Zsoldos
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Nicola Filippini
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Archana Singh‐Manoux
- Epidemiology of Ageing and Neurodegenerative diseasesUniversité de Paris, INSERM U1153ParisFrance
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
| | - Mika Kivimäki
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
| | - Lars T. Westlye
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | | | - Ann‐Marie G. de Lange
- Department of PsychiatryUniversity of OxfordOxfordUK
- NORMENT, Institute of Clinical MedicineUniversity of Oslo, & Division of Mental Health and Addiction, Oslo University HospitalOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
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34
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Fjell AM, Sørensen Ø, Amlien IK, Bartrés-Faz D, Bros DM, Buchmann N, Demuth I, Drevon CA, Düzel S, Ebmeier KP, Idland AV, Kietzmann TC, Kievit R, Kühn S, Lindenberger U, Mowinckel AM, Nyberg L, Price D, Sexton CE, Solé-Padullés C, Pudas S, Sederevicius D, Suri S, Wagner G, Watne LO, Westerhausen R, Zsoldos E, Walhovd KB. Self-reported sleep relates to hippocampal atrophy across the adult lifespan: results from the Lifebrain consortium. Sleep 2021; 43:5628807. [PMID: 31738420 PMCID: PMC7215271 DOI: 10.1093/sleep/zsz280] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 10/25/2019] [Indexed: 12/17/2022] Open
Abstract
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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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Didac Maciá Bros
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Nikolaus Buchmann
- Department of Cardiology, Charité - University Medicine Berlin Campus Benjamin Franklin, Berlin, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Germany
| | - Christian A Drevon
- Vitas AS, Research Park, Gaustadalleen 21, 0349, Oslo and 6 University of Oslo, Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, Medicine/University of Oslo, Norway
| | - Sandra Düzel
- Max Planck Institute for Human Development, Germany
| | | | - Ane-Victoria Idland
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway.,Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, Norway.,Institute of Basic Medical Sciences, University of Oslo, Norway
| | - Tim C Kietzmann
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Rogier Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Simone Kühn
- Max Planck Institute for Human Development, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Germany
| | | | | | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Darren Price
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
| | - Claire E Sexton
- Department of Psychiatry, University of Oxford, UK.,Global Brain Health Institute, Department of Neurology, University of California San Francisco, CA.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, and Institut de Neurociències, Universitat de Barcelona, Spain
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | | | - Sana Suri
- Department of Psychiatry, University of Oxford, UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Gerd Wagner
- Psychiatric Brain and Body Research Group, Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, Norway
| | - René Westerhausen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway
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35
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Suri S, Bulte D, Chiesa ST, Ebmeier KP, Jezzard P, Rieger SW, Pitt JE, Griffanti L, Okell TW, Craig M, Chappell MA, Blockley NP, Kivimäki M, Singh-Manoux A, Khir AW, Hughes AD, Deanfield JE, Jensen DEA, Green SF, Sigutova V, Jansen MG, Zsoldos E, Mackay CE. Study Protocol: The Heart and Brain Study. Front Physiol 2021; 12:643725. [PMID: 33868011 PMCID: PMC8046163 DOI: 10.3389/fphys.2021.643725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 03/03/2021] [Indexed: 11/20/2022] Open
Abstract
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 Heart and Brain Study 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 Heart and Brain Study, 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 Heart and Brain Study 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 Heart and Brain Study will inform strategies to identify at-risk individuals for targeted interventions to prevent or delay dementia.
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Affiliation(s)
- Sana Suri
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Daniel Bulte
- Oxford Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Scott T. Chiesa
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
| | - Peter Jezzard
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Sebastian W. Rieger
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jemma E. Pitt
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Ludovica Griffanti
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Thomas W. Okell
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Martin Craig
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | - Michael A. Chappell
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom
| | | | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Archana Singh-Manoux
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Paris, France
| | - Ashraf W. Khir
- Mechanical Engineering, Brunel University London, Uxbridge, United Kingdom
| | - Alun D. Hughes
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - John E. Deanfield
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Daria E. A. Jensen
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Sebastian F. Green
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
| | - Veronika Sigutova
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
| | - Michelle G. Jansen
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Enikő Zsoldos
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Clare E. Mackay
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
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36
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Melazzini L, Mackay CE, Bordin V, Suri S, Zsoldos E, Filippini N, Mahmood A, Sundaresan V, Codari M, Duff E, Singh-Manoux A, Kivimäki M, Ebmeier KP, Jenkinson M, Sardanelli F, Griffanti L. White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance. Neuroimage Clin 2021; 30:102616. [PMID: 33743476 PMCID: PMC7995650 DOI: 10.1016/j.nicl.2021.102616] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 02/26/2021] [Accepted: 02/27/2021] [Indexed: 12/19/2022]
Abstract
White matter hyperintensities (WMHs) on T2-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 T1-weighted images (T1w) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and T1w-hypointense/nonT1w-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 T1w-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 T1w reveals specific associations with cognitive performance.
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Affiliation(s)
- Luca Melazzini
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Clare E Mackay
- 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; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Valentina Bordin
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Sana Suri
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- 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; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Nicola Filippini
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Vaanathi Sundaresan
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Marina Codari
- Department of Radiology, Stanford University School of Medicine, Stanford, USA
| | - Eugene Duff
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Paediatrics, University of Oxford, Oxford, UK
| | - Archana Singh-Manoux
- INSERM U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Paris, France; Department of Epidemiology and Public Health, University College London, London, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Department of Radiology, IRCCS Policlinico San Donato, Milan, Italy
| | - Ludovica Griffanti
- 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
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37
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Topiwala A, Suri S, Allan C, Zsoldos E, Filippini N, Sexton CE, Mahmood A, Singh-Manoux A, Mackay CE, Kivimäki M, Ebmeier KP. 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; 29:217-226. [PMID: 32736919 PMCID: PMC8097240 DOI: 10.1016/j.jagp.2020.07.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 07/02/2020] [Accepted: 07/02/2020] [Indexed: 12/21/2022]
Abstract
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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Affiliation(s)
- Anya Topiwala
- Department of Psychiatry (AT, SS, CA,EZ, NF, CES, AM, CEM, KPE), University of Oxford, Oxford, UK; Big Data Institute (AT), University of Oxford, Oxford, UK.
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging, Oxford, UK
| | - Charlotte Allan
- Department of Psychiatry, University of Oxford, Oxford, UK,Institute of Translational and Clinical Research, Newcastle University / Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging, Oxford, UK
| | - Nicola Filippini
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging, Oxford, UK
| | - Claire E. Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging, Oxford, UK,Global Brain Health Institute, Memory and Aging Center, Department of Neurology, University of California, San Francisco, USA
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Archana Singh-Manoux
- Université de Paris, INSERM U1153, Paris, France,Department of Epidemiology and Public Health, University College London, London UK
| | - Clare E. Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging, Oxford, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London UK
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Melazzini L, Bordin V, Suri S, Zsoldos E, Ebmeier KP, Jenkinson M, Mackay C, Sardanelli F, Griffanti L. Classifying white matter hyperintensities according to intensity and spatial localisation reveals specific association with cognition. Alzheimers Dement 2020. [DOI: 10.1002/alz.042751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
| | | | - Sana Suri
- University of Oxford Oxford United Kingdom
| | | | | | | | | | - Francesco Sardanelli
- Università degli Studi di Milano Milano Italy
- IRCCS Policlinico San Donato Milan Italy
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39
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Suri S, Chiesa ST, Zsoldos E, Mackay CE, Filippini N, Griffanti L, Mahmood A, Singh-Manoux A, Shipley MJ, Brunner EJ, Kivimäki M, Deanfield JE, Ebmeier KP. Associations between arterial stiffening and brain structure, perfusion, and cognition in the Whitehall II Imaging Sub-study: A retrospective cohort study. PLoS Med 2020; 17:e1003467. [PMID: 33373359 PMCID: PMC7771705 DOI: 10.1371/journal.pmed.1003467] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 11/13/2020] [Indexed: 12/19/2022] Open
Abstract
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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Affiliation(s)
- Sana Suri
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Scott T. Chiesa
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Enikő Zsoldos
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Clare E. Mackay
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Nicola Filippini
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Ludovica Griffanti
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Abda Mahmood
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, France
| | - Martin J. Shipley
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Eric J. Brunner
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - John E. Deanfield
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom
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40
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Suri S, Chiesa ST, Zsoldos E, Filippini N, Mackay C, Griffanti L, Mahmood A, Singh‐Manoux A, Shipley MJ, Brunner E, Kivimaki M, Deanfield J, Ebmeier KP. Longitudinal aortic stiffness is associated with brain microstructure and cognition: A voxel‐wise magnetic resonance imaging study. Alzheimers Dement 2020. [DOI: 10.1002/alz.041822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Sana Suri
- University of Oxford Oxford United Kingdom
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41
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Demnitz N, Anatürk M, Allan CL, Filippini N, Griffanti L, Mackay C, Mahmood A, Sexton CE, Suri S, Topiwala AG, Zsoldos E, Kivimaki M, Singh‐Manoux A, Ebmeier KP. Association of trajectories of depressive symptoms with vascular risk factors, cognitive function and adverse brain outcomes: A 28‐year follow‐up. Alzheimers Dement 2020. [DOI: 10.1002/alz.041823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Naiara Demnitz
- Global Brain Health Institute Dublin Ireland
- University of Oxford Oxford United Kingdom
| | | | - Charlotte L Allan
- Newcastle University Newcastle United Kingdom
- Tyne and Wear NHS Foundation Trust Cumbria United Kingdom
| | | | | | | | | | | | - Sana Suri
- University of Oxford Oxford United Kingdom
| | | | | | | | - Archana Singh‐Manoux
- University College London London United Kingdom
- Universite de Paris, INSERM Paris France
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42
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Demnitz N, Anatürk M, Allan CL, Filippini N, Griffanti L, Mackay CE, Mahmood A, Sexton CE, Suri S, Topiwala AG, Zsoldos E, Kivimäki M, Singh-Manoux A, Ebmeier KP. 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; 131:85-93. [PMID: 32949819 PMCID: PMC8063684 DOI: 10.1016/j.jpsychires.2020.09.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/28/2020] [Accepted: 09/03/2020] [Indexed: 12/11/2022]
Abstract
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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Affiliation(s)
- Naiara Demnitz
- Department of Psychiatry, University of Oxford, Oxford, UK,Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Melis Anatürk
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Charlotte L. Allan
- Institute of Translational and Clinical Research, Newcastle University, and Tyne and Wear NHS Foundation Trust Cumbria, Northumberland UK
| | - Nicola Filippini
- Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | - Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | - Clare E. Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | - Abda Mahmood
- Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Claire E. Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | | | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK,Wellcome Centre for Integrative Neuroimaging (including Oxford Centre for Human Brain Activity and Functional Magnetic Resonance Imaging of the Brain), University of Oxford, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK,Université de Paris, INSERM U1153, Paris, France
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Fjell AM, Sørensen Ø, Amlien IK, Bartrés-Faz D, Brandmaier AM, Buchmann N, Demuth I, Drevon CA, Düzel S, Ebmeier KP, Ghisletta P, Idland AV, Kietzmann TC, Kievit RA, Kühn S, Lindenberger U, Magnussen F, Macià D, Mowinckel AM, Nyberg L, Sexton CE, Solé-Padullés C, Pudas S, Roe JM, Sederevicius D, Suri S, Vidal-Piñeiro D, Wagner G, Watne LO, Westerhausen R, Zsoldos E, Walhovd KB. Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium. Cereb Cortex 2020; 31:1953-1969. [PMID: 33236064 PMCID: PMC7945023 DOI: 10.1093/cercor/bhaa332] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 09/17/2020] [Accepted: 10/12/2020] [Indexed: 12/16/2022] Open
Abstract
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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Affiliation(s)
- Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0188 Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Inge K Amlien
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - David Bartrés-Faz
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona, 08007 Barcelona, Spain
| | - Andreas M Brandmaier
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK
| | - Nikolaus Buchmann
- Department of Cardiology, Charité - University Medicine Berlin Campus Benjamin Franklin, 12203 Berlin, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Lipid Clinic at the Interdisciplinary Metabolism Center, Charité - Universitätsmedizin Berlin, BCRT - Berlin Institute of Health Center for Regenerative Therapies, 10117 Berlin, Germany
| | - Christian A Drevon
- Vitas AS, Research Park, Gaustadalleen 21, 0349 Oslo, Norway.,Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, 0315 Oslo, Norway
| | - Sandra Düzel
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Oxford OX1 2JD UK
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, Swiss Distance University Institute, Swiss National Centre of Competence in Research LIVES, University of Geneva, 1205 Geneva, Switzerland
| | - Ane-Victoria Idland
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway.,Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, 0315 Oslo, Norway.,Institute of Basic Medical Sciences, University of Oslo, 0315 Oslo, Norway
| | - Tim C Kietzmann
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 1TN, UK.,Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Rogier A Kievit
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 1TN, UK
| | - Simone Kühn
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany, and London, UK
| | - Fredrik Magnussen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Didac Macià
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona, 08007 Barcelona, Spain
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - Claire E Sexton
- Department of Psychiatry, University of Oxford, Oxford OX1 2JD UK.,Global Brain Health Institute, Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 2JD, UK
| | - Cristina Solé-Padullés
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona, 08007 Barcelona, Spain
| | - Sara Pudas
- Umeå Center for Functional Brain Imaging, Umeå University, 901 87 Umeå, Sweden
| | - James M Roe
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Donatas Sederevicius
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford OX1 2JD UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 2JD, UK
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Gerd Wagner
- Psychiatric Brain and Body Research Group, Department of Psychiatry and Psychotherapy, Jena University Hospital, 07743 Jena, Germany
| | - Leiv Otto Watne
- Oslo Delirium Research Group, Department of Geriatric Medicine, University of Oslo, 0315 Oslo, Norway
| | - René Westerhausen
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford OX1 2JD UK.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 2JD, UK
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, University of Oslo, 0315 Oslo, Norway.,Department of Radiology and Nuclear Medicine, Oslo University Hospital, 0188 Oslo, Norway
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44
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de Lange AMG, Anatürk M, Suri S, Kaufmann T, Cole JH, Griffanti L, Zsoldos E, Jensen DEA, Filippini N, Singh-Manoux A, Kivimäki M, Westlye LT, Ebmeier KP. Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study. Neuroimage 2020; 222:117292. [PMID: 32835819 PMCID: PMC8121758 DOI: 10.1016/j.neuroimage.2020.117292] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/14/2020] [Accepted: 08/17/2020] [Indexed: 12/21/2022] Open
Abstract
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 (R2 = 0.30, 95% CI [0.24, 0.36]). The modality-specific GM and WM models showed similar performance (R2 = 0.22 [0.16, 0.27] and R2 = 0.24 [0.18, 0.30], respectively), while the FC model showed the lowest prediction accuracy (R2 = 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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Affiliation(s)
- Ann-Marie G de Lange
- Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
| | - Melis Anatürk
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Tobias Kaufmann
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - James H Cole
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK; Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Ludovica Griffanti
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Daria E A Jensen
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Nicola Filippini
- Department of Psychiatry, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Archana Singh-Manoux
- Epidemiology of Ageing and Neurodegenerative Diseases, Universit de Paris, INSERM U1153, Paris France; Department of Epidemiology and Public Health, University College London, London, UK
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
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45
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de Lange AG, Barth C, Kaufmann T, Anatürk M, Suri S, Ebmeier KP, Westlye LT. The maternal brain: Region-specific patterns of brain aging are traceable decades after childbirth. Hum Brain Mapp 2020; 41:4718-4729. [PMID: 32767637 PMCID: PMC7555081 DOI: 10.1002/hbm.25152] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 06/30/2020] [Accepted: 07/16/2020] [Indexed: 12/11/2022] Open
Abstract
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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Affiliation(s)
- Ann‐Marie G. de Lange
- Department of PsychiatryUniversity of OxfordOxfordUK
- Department of PsychologyUniversity of OsloOsloNorway
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Claudia Barth
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Tobias Kaufmann
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and AddictionOslo University HospitalOsloNorway
| | - Melis Anatürk
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | - Sana Suri
- Department of PsychiatryUniversity of OxfordOxfordUK
- Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
| | | | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- NORMENT, Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and AddictionOslo University HospitalOsloNorway
- KG Jebsen Centre for Neurodevelopmental DisordersUniversity of OsloOsloNorway
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Anatürk M, Suri S, Zsoldos E, Filippini N, Mahmood A, Singh-Manoux A, Kivimäki M, Mackay CE, Ebmeier KP, Sexton CE. Associations Between Longitudinal Trajectories of Cognitive and Social Activities and Brain Health in Old Age. JAMA Netw Open 2020; 3:e2013793. [PMID: 32816032 PMCID: PMC7441365 DOI: 10.1001/jamanetworkopen.2020.13793] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022] Open
Abstract
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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Affiliation(s)
- Melis Anatürk
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Nicola Filippini
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London, UK
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Université Paris-Descartes, Paris, France
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Clare E. Mackay
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford, UK
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Claire E. Sexton
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford, UK
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47
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Zsoldos E, Mahmood A, Filippini N, Suri S, Heise V, Griffanti L, Mackay CE, Singh-Manoux A, Kivimäki M, Ebmeier KP. Association of midlife stroke risk with structural brain integrity and memory performance at older ages: a longitudinal cohort study. Brain Commun 2020; 2:fcaa026. [PMID: 32954286 PMCID: PMC7491431 DOI: 10.1093/braincomms/fcaa026] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 01/23/2020] [Accepted: 03/03/2020] [Indexed: 01/13/2023] Open
Abstract
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 (N = 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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Affiliation(s)
- Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Abda Mahmood
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Nicola Filippini
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Verena Heise
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.,Nuffield Department of Population Health, University of Oxford, Big Data Institute, Oxford OX3 7LF, UK
| | - Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford OX3 9DU, UK
| | - Clare E Mackay
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, London WC1E 7HB, UK.,INSERM, U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, Paris, France
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London WC1E 7HB, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK
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48
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Demnitz N, Topiwala A, Zsoldos E, Stagg CJ, Emir UE, Johansen-Berg H, Ebmeier KP, Sexton CE. Alcohol consumption is associated with reduced creatine levels in the hippocampus of older adults. Psychiatry Res 2020; 295:111019. [PMID: 31785452 PMCID: PMC6961205 DOI: 10.1016/j.pscychresns.2019.111019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 11/15/2019] [Accepted: 11/15/2019] [Indexed: 12/22/2022]
Abstract
Besides its well established susceptibility to ageing, the hippocampus has also been shown to be affected by alcohol consumption. Proton spectroscopy (1H-MRS) of the hippocampus, particularly at high-field 7T MRI, may further our understanding of these associations. Here, we aimed to examine how hippocampal metabolites varied with age and alcohol consumption. Hippocampal metabolite spectra were acquired in 37 older adults using 7T 1H-MRS, from which we determined the absolute concentration of N-acetylaspartate (NAA), creatine, choline, myo-inositol, glutamate and glutamine. Thirty participants (mean age = 70.4 ± 4.7 years) also had self-reported data on weekly alcohol consumption. Total choline inversely correlated with age, although this did not survive multiple comparisons correction. Crucially, adults with a higher weekly alcohol consumption had significantly lower levels of creatine, suggesting a deficit in their hippocampal metabolism. These findings add to an increasing body of evidence linking alcohol to hippocampal function.
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Affiliation(s)
- Naiara Demnitz
- Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Anya Topiwala
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enikő Zsoldos
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Uzay E Emir
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Claire E Sexton
- Department of Psychiatry, University of Oxford, Oxford, UK; Global Brain Health Institute, Department of Neurology, University of California San Francisco, San Francisco, California, USA
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Walhovd KB, Fjell AM, Westerhausen R, Nyberg L, Ebmeier KP, Lindenberger U, Bartrés-Faz D, Baaré WF, Siebner HR, Henson R, Drevon CA, Strømstad Knudsen GP, Ljøsne IB, Penninx BW, Ghisletta P, Rogeberg O, Tyler L, Bertram L. Healthy minds 0–100 years: Optimising the use of European brain imaging cohorts (“Lifebrain”). Eur Psychiatry 2020; 50:47-56. [DOI: 10.1016/j.eurpsy.2017.12.006] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Revised: 10/04/2017] [Accepted: 10/05/2017] [Indexed: 12/26/2022] Open
Abstract
AbstractThe main objective of “Lifebrain” is to identify the determinants of brain, cognitive and mental (BCM) health at different stages of life. By integrating, harmonising and enriching major European neuroimaging studies across the life span, we will merge fine-grained BCM health measures of more than 5000 individuals. Longitudinal brain imaging, genetic and health data are available for a major part, as well as cognitive and mental health measures for the broader cohorts, exceeding 27,000 examinations in total. By linking these data to other databases and biobanks, including birth registries, national and regional archives, and by enriching them with a new online data collection and novel measures, we will address the risk factors and protective factors of BCM health. We will identify pathways through which risk and protective factors work and their moderators. Exploiting existing European infrastructures and initiatives, we hope to make major conceptual, methodological and analytical contributions towards large integrative cohorts and their efficient exploitation. We will thus provide novel information on BCM health maintenance, as well as the onset and course of BCM disorders. This will lay a foundation for earlier diagnosis of brain disorders, aberrant development and decline of BCM health, and translate into future preventive and therapeutic strategies. Aiming to improve clinical practice and public health we will work with stakeholders and health authorities, and thus provide the evidence base for prevention and intervention.
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50
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Sabia S, Fayosse A, Dumurgier J, Schnitzler A, Empana JP, Ebmeier KP, Dugravot A, Kivimäki M, Singh-Manoux A. Association of ideal cardiovascular health at age 50 with incidence of dementia: 25 year follow-up of Whitehall II cohort study. BMJ 2019; 366:l4414. [PMID: 31391187 PMCID: PMC6664261 DOI: 10.1136/bmj.l4414] [Citation(s) in RCA: 103] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/12/2019] [Indexed: 01/13/2023]
Abstract
OBJECTIVES To examine the association between the Life Simple 7 cardiovascular health score at age 50 and incidence of dementia. DESIGN Prospective cohort study. SETTING Civil service departments in London (Whitehall II study; study inception 1985-88). PARTICIPANTS 7899 participants with data on the cardiovascular health score at age 50. EXPOSURES The cardiovascular health score included four behavioural (smoking, diet, physical activity, body mass index) and three biological (fasting glucose, blood cholesterol, blood pressure) metrics, coded on a three point scale (0, 1, 2). The cardiovascular health score was the sum of seven metrics (score range 0-14) and was categorised into poor (scores 0-6), intermediate (7-11), and optimal (12-14) cardiovascular health. MAIN OUTCOME MEASURE Incident dementia, identified through linkage to hospital, mental health services, and mortality registers until 2017. RESULTS 347 incident cases of dementia were recorded over a median follow-up of 24.7 years. Compared with an incidence rate of dementia of 3.2 (95% confidence interval 2.5 to 4.0) per 1000 person years among the group with poor cardiovascular health, the absolute rate differences per 1000 person years were -1.5 (95% confidence interval -2.3 to -0.7) for the group with intermediate cardiovascular health and -1.9 (-2.8 to -1.1) for the group with optimal cardiovascular health. Higher cardiovascular health score was associated with a lower risk of dementia (hazard ratio 0.89 (0.85 to 0.95) per 1 point increment in the cardiovascular health score). Similar associations with dementia were observed for the behavioural and biological subscales (hazard ratios per 1 point increment in the subscores 0.87 (0.81 to 0.93) and 0.91 (0.83 to 1.00), respectively). The association between cardiovascular health at age 50 and dementia was also seen in people who remained free of cardiovascular disease over the follow-up (hazard ratio 0.89 (0.84 to 0.95) per 1 point increment in the cardiovascular health score). CONCLUSION Adherence to the Life Simple 7 ideal cardiovascular health recommendations in midlife was associated with a lower risk of dementia later in life.
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Affiliation(s)
- Séverine Sabia
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Aurore Fayosse
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
| | - Julien Dumurgier
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
- Cognitive Neurology Center, Lariboisière - Fernand Widal Hospital, AP-HP, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Alexis Schnitzler
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
| | - Jean-Philippe Empana
- Inserm, U970, Integrative Epidemiology of Cardiovascular Disease, Paris Descartes University, Paris, France
| | | | - Aline Dugravot
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, London, UK
- Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Archana Singh-Manoux
- Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, Université de Paris, 75010 Paris, France
- Department of Epidemiology and Public Health, University College London, London, UK
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