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Thanaraju A, Marzuki AA, Chan JK, Wong KY, Phon-Amnuaisuk P, Vafa S, Chew J, Chia YC, Jenkins M. Structural and functional brain correlates of socioeconomic status across the life span: A systematic review. Neurosci Biobehav Rev 2024; 162:105716. [PMID: 38729281 DOI: 10.1016/j.neubiorev.2024.105716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.
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Affiliation(s)
- Arjun Thanaraju
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia.
| | - Aleya A Marzuki
- Department for Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Germany
| | - Jee Kei Chan
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Kean Yung Wong
- Sensory Neuroscience and Nutrition Lab, University of Otago, New Zealand
| | - Paveen Phon-Amnuaisuk
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Samira Vafa
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Jactty Chew
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Yook Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Michael Jenkins
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
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2
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Yu J. Age-related decline in thickness and surface area in the cortical surface and hippocampus: lifespan trajectories and decade-by-decade analyses. GeroScience 2024:10.1007/s11357-024-01220-1. [PMID: 38831181 DOI: 10.1007/s11357-024-01220-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 05/21/2024] [Indexed: 06/05/2024] Open
Abstract
Previous studies on age-related changes in cortical and hippocampal morphology were not designed or able to reveal the complex spatial patterns of changes across the lifespan. To this end, the current study examined these changes in a decade-by-decade manner by comparing consecutive age decades at the vertex-wise level. Additionally, the lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled and plotted out to provide an overview of their age-related changes. Using two lifespan datasets (Ntotal = 1378; 18 ≤ age ≤ 100), vertex-wise thickness and surface area measurements were extracted from the cortical and unfolded hippocampal surfaces and analyzed using whole-brain/hippocampus vertex-wise analyses. Lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled with generalized additive models for location, scale, and shape. These models revealed fairly linear declines in both cortical measures and inverted U-shaped trajectories for both hippocampal measures. Across the different age decades, the sizes and locations of cortical thinning clusters were highly variable across the age decades. No significant clusters of cortical surface area changes were observed across the age decades. Significant clusters of hippocampal surface area and thickness reduction were not observed until the 70s. Generally, the agreement between datasets on the hippocampal findings was much higher than those of the cortical surface. These findings revealed important nuances in the age-related changes of cortical and hippocampal morphology and cautioned against using lifespan trajectories to infer decade-by-decade changes in the cortical surface and the hippocampus.
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Affiliation(s)
- Junhong Yu
- Psychology, School of Social Sciences, Nanyang Technological University, 48 Nanyang Avenue, Singapore, 639798, Singapore.
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3
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Baranyi G, Buchanan CR, Conole ELS, Backhouse EV, Maniega SM, Valdés Hernández MDC, Bastin ME, Wardlaw J, Deary IJ, Cox SR, Pearce J. Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936. Mol Psychiatry 2024:10.1038/s41380-024-02591-9. [PMID: 38773266 DOI: 10.1038/s41380-024-02591-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 04/29/2024] [Accepted: 05/02/2024] [Indexed: 05/23/2024]
Abstract
Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.
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Affiliation(s)
- Gergő Baranyi
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK.
| | - Colin R Buchanan
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Eleanor L S Conole
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - María Del C Valdés Hernández
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Joanna Wardlaw
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
- Centre for Clinical Brain Sciences (CCBS), The University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK
| | - Jamie Pearce
- Centre for Research on Environment, Society and Health, School of GeoSciences, The University of Edinburgh, Edinburgh, UK
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4
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Schrempft S, Trofimova O, Künzi M, Ramponi C, Lutti A, Kherif F, Latypova A, Vollenweider P, Marques-Vidal P, Preisig M, Kliegel M, Stringhini S, Draganski B. The Neurobiology of Life Course Socioeconomic Conditions and Associated Cognitive Performance in Middle to Late Adulthood. J Neurosci 2024; 44:e1231232024. [PMID: 38499361 PMCID: PMC11044112 DOI: 10.1523/jneurosci.1231-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 01/18/2024] [Accepted: 01/23/2024] [Indexed: 03/20/2024] Open
Abstract
Despite major advances, our understanding of the neurobiology of life course socioeconomic conditions is still scarce. This study aimed to provide insight into the pathways linking socioeconomic exposures-household income, last known occupational position, and life course socioeconomic trajectories-with brain microstructure and cognitive performance in middle to late adulthood. We assessed socioeconomic conditions alongside quantitative relaxometry and diffusion-weighted magnetic resonance imaging indicators of brain tissue microstructure and cognitive performance in a sample of community-dwelling men and women (N = 751, aged 50-91 years). We adjusted the applied regression analyses and structural equation models for the linear and nonlinear effects of age, sex, education, cardiovascular risk factors, and the presence of depression, anxiety, and substance use disorders. Individuals from lower-income households showed signs of advanced brain white matter (WM) aging with greater mean diffusivity (MD), lower neurite density, lower myelination, and lower iron content. The association between household income and MD was mediated by neurite density (B = 0.084, p = 0.003) and myelination (B = 0.019, p = 0.009); MD partially mediated the association between household income and cognitive performance (B = 0.017, p < 0.05). Household income moderated the relation between WM microstructure and cognitive performance, such that greater MD, lower myelination, or lower neurite density was only associated with poorer cognitive performance among individuals from lower-income households. Individuals from higher-income households showed preserved cognitive performance even with greater MD, lower myelination, or lower neurite density. These findings provide novel mechanistic insights into the associations between socioeconomic conditions, brain anatomy, and cognitive performance in middle to late adulthood.
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Affiliation(s)
- Stephanie Schrempft
- Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals, Geneva CH-1205, Switzerland
| | - Olga Trofimova
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne CH-1015, Switzerland
- Swiss Institute of Bioinformatics, Lausanne CH-1015, Switzerland
| | - Morgane Künzi
- Swiss National Centre of Competences in Research, "LIVES - Overcoming Vulnerability: Life Course Perspectives," University of Lausanne and University of Geneva, Lausanne CH-1015 and Carouge CH-1227, Switzerland
- Department of Psychology, University of Geneva, Geneva CH-1205, Switzerland
- Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Carouge CH-1227, Switzerland
| | - Cristina Ramponi
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Adeliya Latypova
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
| | - Martin Preisig
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne CH-1008, Switzerland
| | - Matthias Kliegel
- Swiss National Centre of Competences in Research, "LIVES - Overcoming Vulnerability: Life Course Perspectives," University of Lausanne and University of Geneva, Lausanne CH-1015 and Carouge CH-1227, Switzerland
- Department of Psychology, University of Geneva, Geneva CH-1205, Switzerland
- Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Carouge CH-1227, Switzerland
| | - Silvia Stringhini
- Unit of Population Epidemiology, Division of Primary Care, Geneva University Hospitals, Geneva CH-1205, Switzerland
- Department of Health and Community Medicine, Faculty of Medicine, University of Geneva, Geneva CH-1211, Switzerland
- University Centre for General Medicine and Public Health, University of Lausanne, Lausanne CH-1005, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne CH-1011, Switzerland
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, D-04303 Leipzig, Germany
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5
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Tang R, Elman JA, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Gustavson DE, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS. Childhood Disadvantage Moderates Late Midlife Default Mode Network Cortical Microstructure and Visual Memory Association. J Gerontol A Biol Sci Med Sci 2024; 79:glad114. [PMID: 37096346 DOI: 10.1093/gerona/glad114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Childhood disadvantage is a prominent risk factor for cognitive and brain aging. Childhood disadvantage is associated with poorer episodic memory in late midlife and functional and structural brain abnormalities in the default mode network (DMN). Although age-related changes in DMN are associated with episodic memory declines in older adults, it remains unclear if childhood disadvantage has an enduring impact on this later-life brain-cognition relationship earlier in the aging process. Here, within the DMN, we examined whether its cortical microstructural integrity-an early marker of structural vulnerability that increases the risk for future cognitive decline and neurodegeneration-is associated with episodic memory in adults at ages 56-66, and whether childhood disadvantage moderates this association. METHODS Cortical mean diffusivity (MD) obtained from diffusion magnetic resonance imaging was used to measure microstructural integrity in 350 community-dwelling men. We examined both visual and verbal episodic memory in relation to DMN MD and divided participants into disadvantaged and nondisadvantaged groups based on parental education and occupation. RESULTS Higher DMN MD was associated with poorer visual memory but not verbal memory (β = -0.11, p = .040 vs β = -0.04, p = .535). This association was moderated by childhood disadvantage and was significant only in the disadvantaged group (β = -0.26, p = .002 vs β = -0.00, p = .957). CONCLUSIONS Lower DMN cortical microstructural integrity may reflect visual memory vulnerability in cognitively normal adults earlier in the aging process. Individuals who experienced childhood disadvantage manifested greater vulnerability to cortical microstructure-related visual memory dysfunction than their nondisadvantaged counterparts who exhibited resilience in the face of low cortical microstructural integrity.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Daniel E Gustavson
- Institute for Behavior Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
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6
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Corbin N, Oliveira R, Raynaud Q, Di Domenicantonio G, Draganski B, Kherif F, Callaghan MF, Lutti A. Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans. J Neurosci Methods 2023; 398:109950. [PMID: 37598941 DOI: 10.1016/j.jneumeth.2023.109950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/30/2023] [Accepted: 08/12/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses. NEW METHOD The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images. RESULTS QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy. COMPARISON WITH EXISTING METHODS QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis. CONCLUSION QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.
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Affiliation(s)
- Nadège Corbin
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/University Bordeaux, Bordeaux, France; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rita Oliveira
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Quentin Raynaud
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia Di Domenicantonio
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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7
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García-García I, Donica O, Cohen AA, Gonseth Nusslé S, Heini A, Nusslé S, Pichard C, Rietschel E, Tanackovic G, Folli S, Draganski B. Maintaining brain health across the lifespan. Neurosci Biobehav Rev 2023; 153:105365. [PMID: 37604360 DOI: 10.1016/j.neubiorev.2023.105365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/24/2023] [Accepted: 08/17/2023] [Indexed: 08/23/2023]
Abstract
Across the lifespan, the human body and brain endure the impact of a plethora of exogenous and endogenous factors that determine the health outcome in old age. The overwhelming inter-individual variance spans between progressive frailty with loss of autonomy to largely preserved physical, cognitive, and social functions. Understanding the mechanisms underlying the diverse aging trajectories can inform future strategies to maintain a healthy body and brain. Here we provide a comprehensive overview of the current literature on lifetime factors governing brain health. We present the growing body of evidence that unhealthy alimentary regime, sedentary behaviour, sleep pathologies, cardio-vascular risk factors, and chronic inflammation exert their harmful effects in a cumulative and gradual manner, and that timely and efficient intervention could promote healthy and successful aging. We discuss the main effects and interactions between these risk factors and the resulting brain health outcomes to follow with a description of current strategies aiming to eliminate, treat, or counteract the risk factors. We conclude that the detailed insights about modifiable risk factors could inform personalized multi-domain strategies for brain health maintenance on the background of increased longevity.
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Affiliation(s)
- Isabel García-García
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Centre for Research in Neurosciences, Lausanne University Hospital, University of Lausanne, Switzerland; Clinique la Prairie, Montreux, Switzerland
| | | | - Armand Aaron Cohen
- Department of Geriatrics and Rehabilitation, Hadassah University Medical Center Mount Scopus, Jerusalem, Israel
| | | | | | | | - Claude Pichard
- Nutrition Unit, University Hospital of Geneva, Geneva, Switzerland
| | | | | | | | - Bogdan Draganski
- Laboratory for Research in Neuroimaging (LREN), Department of Clinical Neurosciences, Centre for Research in Neurosciences, Lausanne University Hospital, University of Lausanne, Switzerland; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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8
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Kilpatrick LA, Zhang K, Dong TS, Gee GC, Beltran-Sanchez H, Wang M, Labus JS, Naliboff BD, Mayer EA, Gupta A. Mediation of the association between disadvantaged neighborhoods and cortical microstructure by body mass index. COMMUNICATIONS MEDICINE 2023; 3:122. [PMID: 37714947 PMCID: PMC10504354 DOI: 10.1038/s43856-023-00350-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/21/2023] [Indexed: 09/17/2023] Open
Abstract
BACKGROUND Living in a disadvantaged neighborhood is associated with worse health outcomes, including brain health, yet the underlying biological mechanisms are incompletely understood. We investigated the relationship between neighborhood disadvantage and cortical microstructure, assessed as the T1-weighted/T2-weighted ratio (T1w/T2w) on magnetic resonance imaging, and the potential mediating roles of body mass index (BMI) and stress, as well as the relationship between trans-fatty acid intake and cortical microstructure. METHODS Participants comprised 92 adults (27 men; 65 women) who underwent neuroimaging and provided residential address information. Neighborhood disadvantage was assessed as the 2020 California State area deprivation index (ADI). The T1w/T2w ratio was calculated at four cortical ribbon levels (deep, lower-middle, upper-middle, and superficial). Perceived stress and BMI were assessed as potential mediating factors. Dietary data was collected in 81 participants. RESULTS Here, we show that worse ADI is positively correlated with BMI (r = 0.27, p = .01) and perceived stress (r = 0.22, p = .04); decreased T1w/T2w ratio in middle/deep cortex in supramarginal, temporal, and primary motor regions (p < .001); and increased T1w/T2w ratio in superficial cortex in medial prefrontal and cingulate regions (p < .001). Increased BMI partially mediates the relationship between worse ADI and observed T1w/T2w ratio increases (p = .02). Further, trans-fatty acid intake (high in fried fast foods and obesogenic) is correlated with these T1w/T2w ratio increases (p = .03). CONCLUSIONS Obesogenic aspects of neighborhood disadvantage, including poor dietary quality, may disrupt information processing flexibility in regions involved in reward, emotion regulation, and cognition. These data further suggest ramifications of living in a disadvantaged neighborhood on brain health.
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Affiliation(s)
- Lisa A Kilpatrick
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA.
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA.
| | - Keying Zhang
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
| | - Tien S Dong
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Gilbert C Gee
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- California Center for Population Research, University of California, Los Angeles, CA, USA
| | - Hiram Beltran-Sanchez
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
- California Center for Population Research, University of California, Los Angeles, CA, USA
| | - May Wang
- Department of Community Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Jennifer S Labus
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Bruce D Naliboff
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Emeran A Mayer
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA
| | - Arpana Gupta
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Goodman-Luskin Microbiome Center, University of California, Los Angeles, CA, USA.
- G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, CA, USA.
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Kilpatrick L, Zhang K, Dong T, Gee G, Beltran-Sanchez H, Wang M, Labus J, Naliboff B, Mayer E, Gupta A. Mediating role of obesity on the association between disadvantaged neighborhoods and intracortical myelination. RESEARCH SQUARE 2023:rs.3.rs-2592087. [PMID: 36993600 PMCID: PMC10055549 DOI: 10.21203/rs.3.rs-2592087/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We investigated the relationship between neighborhood disadvantage (area deprivation index [ADI]) and intracortical myelination (T1-weighted/T2-weighted ratio at deep to superficial cortical levels), and the potential mediating role of the body mass index (BMI) and perceived stress in 92 adults. Worse ADI was correlated with increased BMI and perceived stress (p's<.05). Non-rotated partial least squares analysis revealed associations between worse ADI and decreased myelination in middle/deep cortex in supramarginal, temporal, and primary motor regions and increased myelination in superficial cortex in medial prefrontal and cingulate regions (p<.001); thus, neighborhood disadvantage may influence the flexibility of information processing involved in reward, emotion regulation, and cognition. Structural equation modelling revealed increased BMI as partially mediating the relationship between worse ADI and observed myelination increases (p=.02). Further, trans-fatty acid intake was correlated with observed myelination increases (p=.03), suggesting the importance of dietary quality. These data further suggest ramifications of neighborhood disadvantage on brain health.
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Affiliation(s)
| | | | - Tien Dong
- University of California Los Angeles
| | | | | | - May Wang
- University of California Los Angeles
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