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Liu L, Tu L, Shen Q, Bao Y, Xu F, Zhang D, Xu Y. Meta-analysis of the relationship between the number and location of perivascular spaces in the brain and cognitive function. Neurol Sci 2024:10.1007/s10072-024-07438-3. [PMID: 38459400 DOI: 10.1007/s10072-024-07438-3] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 03/01/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Cerebral perivascular spaces are part of the cerebral microvascular structure and play a role in lymphatic drainage and the removal of waste products from the brain. Relationships of the number and location of such spaces with cognition are unclear. OBJECTIVE To meta-analyze available data on potential associations of severity and location of perivascular spaces with cognitive performance. METHODS We searched PubMed, EMBASE, Web of Science and the Cochrane Central Registry of Controlled Trials for relevant studies published between January 2000 and July 2023. Performance on different cognitive domains was compared to the severity of perivascular spaces in different brain regions using comprehensive meta-analysis. When studies report unadjusted and adjusted means, we use adjusted means for meta-analysis. The study protocol is registered in the PROSPERO database (CRD42023443460). RESULTS We meta-analyzed data from 26 cross-sectional studies and two longitudinal studies involving 7908 participants. In most studies perivascular spaces was using a visual rating scale. A higher number of basal ganglia perivascular spaces was linked to lower general intelligence and attention. Moreover, increased centrum semiovale perivascular spaces were associated with worse general intelligence, executive function, language, and memory. Conversely, higher hippocampus perivascular spaces were associated with enhanced memory and executive function. Subgroup analyses revealed variations in associations among different disease conditions. CONCLUSIONS A higher quantity of perivascular spaces in the brain is correlated with impaired cognitive function. The location of these perivascular spaces and the underlying disease conditions may influence the specific cognitive domains that are affected. SYSTEMATIC REVIEW REGISTRATION The study protocol has been registered in the PROSPERO database (CRD42023443460).
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Affiliation(s)
- Ling Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liangdan Tu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiuyan Shen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Bao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Fang Xu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dan Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yanming Xu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Abstract
Cerebral small vessel disease is common in older adults and increases the risk of stroke, cognitive impairment, and dementia. While often attributed to midlife vascular risk factors such as hypertension, factors from earlier in life may contribute to later small vessel disease risk. In this review, we summarize current evidence for early-life effects on small vessel disease, stroke and dementia focusing on prenatal nutrition, and cognitive ability, education, and socioeconomic status in childhood. We discuss possible reasons for these associations, including differences in brain resilience and reserve, access to cognitive, social, and economic resources, and health behaviors, and we consider the extent to which these associations are independent of vascular risk factors. Although early-life factors, particularly education, are major risk factors for Alzheimer disease, they are less established in small vessel disease or vascular cognitive impairment. We discuss current knowledge, gaps in knowledge, targets for future research, clinical practice, and policy change.
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Affiliation(s)
- Ellen V. Backhouse
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC UK Dementia Research Institute (E.V.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
| | - James P. Boardman
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC Centre for Reproductive Health (J.P.B.), University of Edinburgh, Scotland, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC UK Dementia Research Institute (E.V.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- Edinburgh Imaging (J.M.W.), University of Edinburgh, Scotland, United Kingdom
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3
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James SN, Manning EN, Storey M, Nicholas JM, Coath W, Keuss SE, Cash DM, Lane CA, Parker T, Keshavan A, Buchanan SM, Wagen A, Harris M, Malone I, Lu K, Needham LP, Street R, Thomas D, Dickson J, Murray-Smith H, Wong A, Freiberger T, Crutch SJ, Fox NC, Richards M, Barkhof F, Sudre CH, Barnes J, Schott JM. Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds. Brain Commun 2023; 5:fcad225. [PMID: 37680671 PMCID: PMC10481255 DOI: 10.1093/braincomms/fcad225] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 05/30/2023] [Accepted: 08/17/2023] [Indexed: 09/09/2023] Open
Abstract
We investigate associations between normal-appearing white matter microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 birth cohort) underwent PET-MRI around age 70. Mean standardized normal-appearing white matter integrity metrics (fractional anisotropy, mean diffusivity, neurite density index and orientation dispersion index) were derived from diffusion MRI. Linear regression was used to test associations between normal-appearing white matter metrics and (i) concurrent measures, including whole brain volume, white matter hyperintensity volume, PET amyloid and cognition; (ii) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socio-economic position and genetic risk for Alzheimer's disease (APOE-ɛ4); (iii) systolic and diastolic blood pressure and cardiovascular health (Framingham Heart Study Cardiovascular Risk Score) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). Three hundred and sixty-two participants met inclusion criteria (mean age 70, 49% female). Higher white matter hyperintensity volume was associated with lower fractional anisotropy [b = -0.09 (95% confidence interval: -0.11, -0.06), P < 0.01], neurite density index [b = -0.17 (-0.22, -0.12), P < 0.01] and higher mean diffusivity [b = 0.14 (-0.10, -0.17), P < 0.01]; amyloid (in men) was associated with lower fractional anisotropy [b = -0.04 (-0.08, -0.01), P = 0.03)] and higher mean diffusivity [b = 0.06 (0.01, 0.11), P = 0.02]. Framingham Heart Study Cardiovascular Risk Score in later-life (age 69) was associated with normal-appearing white matter {lower fractional anisotropy [b = -0.06 (-0.09, -0.02) P < 0.01], neurite density index [b = -0.10 (-0.17, -0.03), P < 0.01] and higher mean diffusivity [b = 0.09 (0.04, 0.14), P < 0.01]}. Significant sex interactions (P < 0.05) emerged for midlife cardiovascular health (age 53) and normal-appearing white matter at 70: marginal effect plots demonstrated, in women only, normal-appearing white matter was associated with higher midlife Framingham Heart Study Cardiovascular Risk Score (lower fractional anisotropy and neurite density index), midlife systolic (lower fractional anisotropy, neurite density index and higher mean diffusivity) and diastolic (lower fractional anisotropy and neurite density index) blood pressure and greater blood pressure change between 43 and 53 years (lower fractional anisotropy and neurite density index), independently of white matter hyperintensity volume. In summary, poorer normal-appearing white matter microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how normal-appearing white matter can provide additional information to overt white matter disease. Our findings further show that greater 'midlife' cardiovascular risk and higher blood pressure were associated with poorer normal-appearing white matter microstructural integrity in females only, suggesting that women's brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health.
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Emily N Manning
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Mathew Storey
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Aaron Wagen
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Mathew Harris
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ian Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Louisa P Needham
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca Street
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospitals Foundation Trust, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
| | - Tamar Freiberger
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
| | - Frederik Barkhof
- Centre for Medical Image Computing, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
- Centre for Medical Image Computing, University College London, London, UK
- School of Biomedical Engineering, King’s College, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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de Souza EA, Silva SA, Vieira BH, Salmon CEG. fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance. Intelligence 2023. [DOI: 10.1016/j.intell.2023.101727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Stammen C, Fraenz C, Grazioplene RG, Schlüter C, Merhof V, Johnson W, Güntürkün O, DeYoung CG, Genç E. Robust associations between white matter microstructure and general intelligence. Cereb Cortex 2023:6994402. [PMID: 36682883 DOI: 10.1093/cercor/bhac538] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 01/24/2023] Open
Abstract
Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.
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Affiliation(s)
- Christina Stammen
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139 Dortmund, Germany
| | - Christoph Fraenz
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139 Dortmund, Germany
| | | | - Caroline Schlüter
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, 44801 Bochum, Germany
| | - Viola Merhof
- Chair of Research Methods and Psychological Assessment, University of Mannheim, 68161 Mannheim, Germany
| | - Wendy Johnson
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, United Kingdom
| | - Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, 44801 Bochum, Germany
| | - Colin G DeYoung
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Erhan Genç
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139 Dortmund, Germany
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Frischkorn GT, Wilhelm O, Oberauer K. Process-oriented intelligence research: A review from the cognitive perspective. Intelligence 2022. [DOI: 10.1016/j.intell.2022.101681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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7
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Libecap TJ, Zachariou V, Bauer CE, Wilcock DM, Jicha GA, Raslau FD, Gold BT. Enlarged Perivascular Spaces Are Negatively Associated With Montreal Cognitive Assessment Scores in Older Adults. Front Neurol 2022; 13:888511. [PMID: 35847209 PMCID: PMC9283758 DOI: 10.3389/fneur.2022.888511] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022] Open
Abstract
Emerging evidence suggests that enlarged perivascular spaces (ePVS) may be a clinically significant neuroimaging marker of global cognitive function related to cerebral small vessel disease (cSVD). We tested this possibility by assessing the relationship between ePVS and both a standardized measure of global cognitive function, the Montreal Cognitive Assessment (MoCA), and an established marker of cSVD, white matter hyperintensity volume (WMH) volume. One hundred and eleven community-dwelling older adults (56-86) underwent neuroimaging and MoCA testing. Quantification of region-specific ePVS burden was performed using a previously validated visual rating method and WMH volumes were computed using the standard ADNI pipeline. Separate linear regression models were run with ePVS as a predictor of MoCA scores and whole brain WMH volume. Results indicated a negative association between MoCA scores and both total ePVS counts (P ≤ 0.001) and centrum semiovale ePVS counts (P ≤ 0.001), after controlling for other relevant cSVD variables. Further, WMH volumes were positively associated with total ePVS (P = 0.010), basal ganglia ePVS (P ≤ 0.001), and centrum semiovale ePVS (P = 0.027). Our results suggest that ePVS burden, particularly in the centrum semiovale, may be a clinically significant neuroimaging marker of global cognitive dysfunction related to cSVD.
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Affiliation(s)
- Timothy J. Libecap
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Valentinos Zachariou
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Christopher E. Bauer
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Donna M. Wilcock
- Department of Physiology, College of Medicine, University of Kentucky, Lexington, KY, United States
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Gregory A. Jicha
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
- Department of Neurology, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Flavius D. Raslau
- Department of Radiology, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Brian T. Gold
- Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, United States
- Sanders-Brown Center on Aging, College of Medicine, University of Kentucky, Lexington, KY, United States
- Magnetic Resonance Imaging and Spectroscopy Center, College of Medicine, University of Kentucky, Lexington, KY, United States
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Riedel L, van den Heuvel MP, Markett S. Trajectory of rich club properties in structural brain networks. Hum Brain Mapp 2022; 43:4239-4253. [PMID: 35620874 PMCID: PMC9435005 DOI: 10.1002/hbm.25950] [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: 11/16/2021] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 11/06/2022] Open
Abstract
Many organizational principles of structural brain networks are established before birth and undergo considerable developmental changes afterwards. These include the topologically central hub regions and a densely connected rich club. While several studies have mapped developmental trajectories of brain connectivity and brain network organization across childhood and adolescence, comparatively little is known about subsequent development over the course of the lifespan. Here, we present a cross-sectional analysis of structural brain network development in N = 8066 participants aged 5-80 years. Across all brain regions, structural connectivity strength followed an "inverted-U"-shaped trajectory with vertex in the early 30s. Connectivity strength of hub regions showed a similar trajectory and the identity of hub regions remained stable across all age groups. While connectivity strength declined with advancing age, the organization of hub regions into a rich club did not only remain intact but became more pronounced, presumingly through a selected sparing of relevant connections from age-related connectivity loss. The stability of rich club organization in the face of overall age-related decline is consistent with a "first come, last served" model of neurodevelopment, where the first principles to develop are the last to decline with age. Rich club organization has been shown to be highly beneficial for communicability and higher cognition. A resilient rich club might thus be protective of a functional loss in late adulthood and represent a neural reserve to sustain cognitive functioning in the aging brain.
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Affiliation(s)
- Levin Riedel
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin School of Mind and Brain, Berlin, Germany
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sebastian Markett
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
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Li X, Salami A, Avelar-Pereira B, Bäckman L, Persson J. White-Matter Integrity and Working Memory: Links to Aging and Dopamine-Related Genes. eNeuro 2022; 9:ENEURO. [PMID: 35346961 DOI: 10.1523/ENEURO.0413-21.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/22/2022] [Accepted: 02/07/2022] [Indexed: 11/21/2022] Open
Abstract
Working memory, a core function underlying many higher-level cognitive processes, requires cooperation of multiple brain regions. White matter refers to myelinated axons, which are critical to interregional brain communication. Past studies on the association between white-matter integrity and working memory have yielded mixed findings. Using voxelwise tract-based spatial statistics analysis, we investigated this relationship in a sample of 328 healthy adults from 25 to 80 years of age. Given the important role of dopamine (DA) in working-memory functioning and white matter, we also analyzed the effects of dopamine-related genes on them. There were associations between white-matter integrity and working memory in multiple tracts, indicating that working-memory functioning relies on global connections between different brain areas across the adult life span. Moreover, a mediation analysis suggested that white-matter integrity contributes to age-related differences in working memory. Finally, there was an effect of the COMT Val158Met polymorphism on white-matter integrity, such that Val/Val carriers had lower fractional anisotropy values than any Met carriers in the internal capsule, corona radiata, and posterior thalamic radiation. As this polymorphism has been associated with dopaminergic tone in the prefrontal cortex, this result provides evidence for a link between DA neurotransmission and white matter. Together, the results support a link between white-matter integrity and working memory, and provide evidence for its interplay with age- and DA-related genes.
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Hamilton O, Cox SR, Ballerini L, Bastin ME, Corley J, Gow AJ, Muñoz Maniega S, Redmond P, Valdés Hernández MDC, Wardlaw JM, Deary IJ. Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort. Neurobiol Aging 2021; 105:25-34. [PMID: 34022536 PMCID: PMC8345313 DOI: 10.1016/j.neurobiolaging.2021.04.007] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 01/27/2021] [Accepted: 04/13/2021] [Indexed: 01/08/2023]
Abstract
Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.
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Affiliation(s)
- Okl Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - S R Cox
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - L Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - M E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - J Corley
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - A J Gow
- Department of Psychology and the Centre for Applied Behavioural Sciences, School of Social Sciences, Heriot-Watt University, Edinburgh, UK, EH14 4AS
| | - S Muñoz Maniega
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - P Redmond
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - M Del C Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - J M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Dementia Research Institute, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB; Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ.
| | - I J Deary
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ.
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Hillary RF, Stevenson AJ, Cox SR, McCartney DL, Harris SE, Seeboth A, Higham J, Sproul D, Taylor AM, Redmond P, Corley J, Pattie A, Hernández MDCV, Muñoz-Maniega S, Bastin ME, Wardlaw JM, Horvath S, Ritchie CW, Spires-Jones TL, McIntosh AM, Evans KL, Deary IJ, Marioni RE. An epigenetic predictor of death captures multi-modal measures of brain health. Mol Psychiatry 2021; 26:3806-3816. [PMID: 31796892 PMCID: PMC8550950 DOI: 10.1038/s41380-019-0616-9] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [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: 07/30/2019] [Revised: 11/14/2019] [Accepted: 11/20/2019] [Indexed: 11/08/2022]
Abstract
Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Anne Seeboth
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jon Higham
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Duncan Sproul
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz-Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Tara L Spires-Jones
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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12
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Hoagey DA, Lazarus LTT, Rodrigue KM, Kennedy KM. The effect of vascular health factors on white matter microstructure mediates age-related differences in executive function performance. Cortex 2021; 141:403-420. [PMID: 34130048 PMCID: PMC8319097 DOI: 10.1016/j.cortex.2021.04.016] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 12/11/2020] [Accepted: 04/08/2021] [Indexed: 01/03/2023]
Abstract
Even within healthy aging, vascular risk factors can detrimentally influence cognition, with executive functions (EF) particularly vulnerable. Fronto-parietal white matter (WM) connectivity in part, supports EF and may be particularly sensitive to vascular risk. Here, we utilized structural equation modeling in 184 healthy adults (aged 20-94 years of age) to test the hypotheses that: 1) fronto-parietal WM microstructure mediates age effects on EF; 2) higher blood pressure (BP) and white matter hyperintensity (WMH) burden influences this association. All participants underwent comprehensive cognitive and neuropsychological testing including tests of processing speed, executive function (with a focus on tasks that require switching and inhibition) and completed an MRI scanning session that included FLAIR imaging for semi-automated quantification of white matter hyperintensity burden and diffusion-weighted imaging for tractography. Structural equation models were specified with age (as a continuous variable) and blood pressure predicting within-tract WMH burden and fractional anisotropy predicting executive function and processing speed. Results indicated that fronto-parietal white matter of the genu of the corpus collosum, superior longitudinal fasciculus, and the inferior frontal occipital fasciculus (but not cortico-spinal tract) mediated the association between age and EF. Additionally, increased systolic blood pressure and white matter hyperintensity burden within these white matter tracts contribute to worsening white matter health and are important factors underlying age-brain-behavior associations. These findings suggest that aging brings about increases in both BP and WMH burden, which may be involved in the degradation of white matter connectivity and in turn, negatively impact executive functions as we age.
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Affiliation(s)
- David A Hoagey
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
| | - Linh T T Lazarus
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Karen M Rodrigue
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
| | - Kristen M Kennedy
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA.
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13
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Statsenko Y, Habuza T, Charykova I, Gorkom KNV, Zaki N, Almansoori TM, Baylis G, Ljubisavljevic M, Belghali M. Predicting Age From Behavioral Test Performance for Screening Early Onset of Cognitive Decline. Front Aging Neurosci 2021; 13:661514. [PMID: 34322006 PMCID: PMC8312225 DOI: 10.3389/fnagi.2021.661514] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/07/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each functional domain separately by applying different behavioral tasks whereby the tests reflect the conceptual structure of cognition. Such an approach has limitations that are described in the article. Objective: Our aim was to improve the diagnosis of early cognitive decline. We estimated the onset of cognitive decline in a healthy population, using behavioral tests, and predicted the age group of an individual. The comparison between the predicted ("cognitive") and chronological age will contribute to the early diagnosis of accelerated aging. Materials and Methods: We used publicly available datasets (POBA, SSCT) and Pearson correlation coefficients to assess the relationship between age and tests results, Kruskal-Wallis test to compare distribution, clustering methods to find an onset of cognitive decline, feature selection to enhance performance of the clustering algorithms, and classification methods to predict an age group from cognitive tests results. Results: The major results of the psychophysiological tests followed a U-shape function across the lifespan, which reflected the known inverted function of white matter volume changes. Optimal values were observed in those aged over 35 years, with a period of stability and accelerated decline after 55-60 years of age. The shape of the age-related variance of the performance of major cognitive tests was linear, which followed the trend of lifespan gray matter volume changes starting from adolescence. There was no significant sex difference in lifelong dynamics of major tests estimates. The performance of the classification model for identifying subject age groups was high. Conclusions: ML models can be designed and utilized as computer-aided detectors of neurocognitive decline. Our study demonstrated great promise for the utility of classification models to predict age-related changes. These findings encourage further explorations combining several tests from the cognitive and psychophysiological test battery to derive the most reliable set of tests toward the development of a highly-accurate ML model.
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Affiliation(s)
- Yauhen Statsenko
- College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.,Big Data Analytics Center (BIDAC), United Arab Emirates University, Al Ain, United Arab Emirates
| | - Tetiana Habuza
- Big Data Analytics Center (BIDAC), United Arab Emirates University, Al Ain, United Arab Emirates.,College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Inna Charykova
- Laboratory of Psychology, Republican Scientific-Practical Center of Sports, Minsk, Belarus
| | - Klaus Neidl-Van Gorkom
- College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Nazar Zaki
- Big Data Analytics Center (BIDAC), United Arab Emirates University, Al Ain, United Arab Emirates.,College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Taleb M Almansoori
- College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Gordon Baylis
- College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Milos Ljubisavljevic
- College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Maroua Belghali
- INSERM, COMETE, GIP CYCERON, Normandie University, UNICAEN, Caen, Research Unit: Aging, Health and Diseases, Caen, France.,College of Education, United Arab Emirates University, Al Ain, United Arab Emirates
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14
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d'Arbeloff T, Elliott ML, Knodt AR, Sison M, Melzer TR, Ireland D, Ramrakha S, Poulton R, Caspi A, Moffitt TE, Hariri AR. Midlife Cardiovascular Fitness Is Reflected in the Brain's White Matter. Front Aging Neurosci 2021; 13:652575. [PMID: 33889085 PMCID: PMC8055854 DOI: 10.3389/fnagi.2021.652575] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 03/05/2021] [Indexed: 12/18/2022] Open
Abstract
Disappointing results from clinical trials designed to delay structural brain decline and the accompanying increase in risk for dementia in older adults have precipitated a shift in testing promising interventions from late in life toward midlife before irreversible damage has accumulated. This shift, however, requires targeting midlife biomarkers that are associated with clinical changes manifesting only in late life. Here we explored possible links between one putative biomarker, distributed integrity of brain white matter, and two intervention targets, cardiovascular fitness and healthy lifestyle behaviors, in midlife. At age 45, fractional anisotropy (FA) derived from diffusion weighted MRI was used to estimate the microstructural integrity of distributed white matter tracts in a population-representative birth cohort. Age-45 cardiovascular fitness (VO2Max; N = 801) was estimated from heart rates obtained during submaximal exercise tests; age-45 healthy lifestyle behaviors were estimated using the Nyberg Health Index (N = 854). Ten-fold cross-validated elastic net predictive modeling revealed that estimated VO2Max was modestly associated with distributed FA. In contrast, there was no significant association between Nyberg Health Index scores and FA. Our findings suggest that cardiovascular fitness levels, but not healthy lifestyle behaviors, are associated with the distributed integrity of white matter in the brain in midlife. These patterns could help inform future clinical intervention research targeting ADRDs.
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Affiliation(s)
- Tracy d'Arbeloff
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Maxwell L Elliott
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Annchen R Knodt
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Maria Sison
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
| | - Tracy R Melzer
- New Zealand Brain Research Institute, Christchurch, New Zealand.,Department of Medicine, University of Otago, Christchurch, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Avshalom Caspi
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States.,Social, Genetic, & Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom.,Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
| | - Terrie E Moffitt
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States.,Social, Genetic, & Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, United Kingdom.,Department of Psychiatry & Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States.,Center for Genomic and Computational Biology, Duke University, Durham, NC, United States
| | - Ahmad R Hariri
- Department of Psychology & Neuroscience, Duke University, Durham, NC, United States
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15
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Abstract
Introduction Cerebellum cortex fractional anisotropy is a proxy of the integrity of the cerebellum cortex. However, less is known about how it is shaped by race and socioeconomic status (SES) indicators such as parental education and household income. Purpose In a national sample of American pre-adolescents, this study had two aims: to test the effects of two SES indicators, namely parental education and household income, on cerebellum cortex fractional anisotropy, and to explore racial differences in these effects. Methods Using data from the Adolescent Brain Cognitive Development (ABCD) study, we analyzed the diffusion Magnetic Resonance Imaging (dMRI) data of 9565, 9-10-year-old pre-adolescents. The main outcomes were cerebellum cortex fractional anisotropy separately calculated for right and left hemispheres using dMRI. The independent variables were parental education and household income; both treated as categorical variables. Age, sex, ethnicity, and family marital status were the covariates. Race was the moderator. To analyze the data, we used mixed-effects regression models without and with interaction terms. We controlled for propensity score and MRI device. Results High parental education and household income were associated with lower right and left cerebellum cortex fractional anisotropy. In the pooled sample, we found significant interactions between race and parental education and household income, suggesting that the effects of parental education and household income on the right and left cerebellum cortex fractional anisotropy are all significantly larger for White than for Black pre-adolescents. Conclusions The effects of SES indicators, namely parental education and household income, on pre-adolescents' cerebellum cortex microstructure and integrity are weaker in Black than in White families. This finding is in line with the Marginalization-related Diminished Returns (MDRs), defined as weaker effects of SES indicators for Blacks and other racial and minority groups than for Whites.
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16
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Thomas MB, Raghava JM, Pantelis C, Rostrup E, Nielsen MØ, Jensen MH, Glenthøj BY, Mandl RCW, Ebdrup BH, Fagerlund B. Associations between cognition and white matter microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls: A multivariate pattern analysis. Cortex 2021; 139:282-297. [PMID: 33933719 DOI: 10.1016/j.cortex.2021.03.003] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 01/19/2021] [Accepted: 03/01/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Cognitive functions have been associated with white matter (WM) microstructure in schizophrenia, but most studies are limited by examining only select cognitive measures and single WM tracts in chronic, medicated patients. It is unclear if the cognition-WM relationship differs between antipsychotic-naïve patients with schizophrenia and healthy controls, as differential associations have not been directly examined. Here we examine if there are differential patterns of associations between cognition and WM microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls, and we characterize reliable contributors to the pattern of associations across multiple cognitive domains and WM regions, in order to elucidate white matter contribution to the neural underpinnings of cognitive deficits. METHODS Thirty-six first-episode antipsychotic-naïve patients with schizophrenia and 52 matched healthy controls underwent cognitive tests and diffusion-weighted imaging on a 3T Magnetic Resonance Imaging scanner. Using a multivariate partial least squares correlation analysis, we included 14 cognitive variables and mean fractional anisotropy values of 48 WM regions. RESULTS Initial analyses showed significant group differences in both measures of WM and cognition. There was no group interaction effect in the pattern of associations between cognition and WM microstructure. The combined analysis of patients and controls lead to a significant pattern of associations (omnibus test p = .015). Thirty-four regions and seven cognitive functions contributed reliably to the associations. CONCLUSIONS The lack of an interaction effect suggests similar associations in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls. This, together with the differences in both WM and cognitive measurements, supports the involvement of WM in cognitive deficits in schizophrenia. Our findings add to the field by showing a coherent picture of the overall pattern of association between cognition and WM. These findings increase our understanding of the impact of WM on cognition, contributing to the search for neuromarkers of cognitive deficits in schizophrenia.
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Affiliation(s)
- Marie B Thomas
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
| | - Jayachandra M Raghava
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Christos Pantelis
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, Victoria, Australia.
| | - Egill Rostrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Mette Ø Nielsen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Maria H Jensen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Birte Y Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - René C W Mandl
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; UMC Brain Center, University Medical Center Utrecht, Utrecht, Netherlands.
| | - Bjørn H Ebdrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Birgitte Fagerlund
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
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17
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d'Arbeloff T, Cooke M, Knodt AR, Sison M, Melzer TR, Ireland D, Poulton R, Ramrakha S, Moffitt TE, Caspi A, Hariri AR. Is cardiovascular fitness associated with structural brain integrity in midlife? Evidence from a population-representative birth cohort study. Aging (Albany NY) 2020; 12:20888-20914. [PMID: 33082296 PMCID: PMC7655208 DOI: 10.18632/aging.104112] [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] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 08/09/2020] [Indexed: 12/31/2022]
Abstract
Improving cardiovascular fitness may buffer against age-related cognitive decline and mitigate dementia risk by staving off brain atrophy. However, it is unclear if such effects reflect factors operating in childhood (neuroselection) or adulthood (neuroprotection). Using data from 807 members of the Dunedin Study, a population-representative birth cohort, we investigated associations between cardiovascular fitness and structural brain integrity at age 45, and the extent to which associations reflected possible neuroselection or neuroprotection by controlling for childhood IQ. Higher fitness, as indexed by VO2Max, was not associated with average cortical thickness, total surface area, or subcortical gray matter volume including the hippocampus. However, higher fitness was associated with thicker cortex in prefrontal and temporal regions as well as greater cerebellar gray matter volume. Higher fitness was also associated with decreased hippocampal fissure volume. These associations were unaffected by the inclusion of childhood IQ in analyses. In contrast, a higher rate of decline in cardiovascular fitness from 26 to 45 years was not robustly associated with structural brain integrity. Our findings are consistent with a neuroprotective account of adult cardiovascular fitness but suggest that effects are not uniformly observed across the brain and reflect contemporaneous fitness more so than decline over time.
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Affiliation(s)
- Tracy d'Arbeloff
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Megan Cooke
- Center for Addiction Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Annchen R Knodt
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Maria Sison
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Tracy R Melzer
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - David Ireland
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, NZ
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, NZ
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, NZ
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
- Social, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27708, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
- Social, Genetic, and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, De Crespigny Park, Denmark Hill, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC 27708, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC 27708, USA
| | - Ahmad R Hariri
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
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18
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Abstract
AbstractThe prospect of improving or maintaining cognitive functioning has provoked a steadily increasing number of cognitive training interventions over the last years, especially for clinical and elderly populations. However, there are discrepancies between the findings of the studies. One of the reasons behind these heterogeneous findings is that there are vast inter-individual differences in how people benefit from the training and in the extent that training-related gains are transferred to other untrained tasks and domains. In this paper, we address the value of incorporating neural measures to cognitive training studies in order to fully understand the mechanisms leading to inter-individual differences in training gains and their generalizability to other tasks. Our perspective is that it is necessary to collect multimodal neural measures in the pre- and post-training phase, which can enable us to understand the factors contributing to successful training outcomes. More importantly, this understanding can enable us to predict who will benefit from different types of interventions, thereby allowing the development of individually tailored intervention programs.
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19
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Zarnani K, Smith SM, Alfaro-Almagro F, Fagerlund B, Lauritzen M, Rostrup E, Nichols TE. Discovering correlates of age-related decline in a healthy late-midlife male birth cohort. Aging (Albany NY) 2020; 12:16709-16743. [PMID: 32913141 PMCID: PMC7521526 DOI: 10.18632/aging.103345] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 05/01/2020] [Indexed: 01/24/2023]
Abstract
Studies exploring age-related brain and cognitive change have identified substantial heterogeneity among individuals, but the underlying reasons for the differential trajectories remain largely unknown. We investigated cross-sectional and longitudinal associations between brain-imaging phenotypes (IDPs) and cognitive ability, and how these relations may be modified by common risk and protective factors. Participants were recruited from the 1953 Danish Male Birth Cohort (N=123), a longitudinal study of cognitive and brain ageing. Childhood IQ and socio-demographic factors are available for these participants who have been assessed regularly on multiple IDPs and behavioural factors in midlife. Using Pearson correlations and canonical correlation analysis (CCA), we explored the relation between 454 IDPs and 114 behavioural variables. CCA identified a single mode of population covariation coupling cross-subject longitudinal changes in brain structure to changes in cognitive performance and to a range of age-related covariates (r=0.92, Pcorrected < 0.001). Specifically, this CCA-mode indicated that; decreases in IQ and speed assessed tasks, higher rates of familial myocardial infarct, less physical activity, and poorer mental health are associated with larger decreases in whole brain grey matter and white matter. We found no evidence supporting the role of baseline scores as predictors of impending brain and behavioural change in late-midlife.
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Affiliation(s)
- Kiyana Zarnani
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Denmark
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Neurophysiology, Rigshospitalet-Glostrup, Denmark
| | - Egill Rostrup
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Denmark
| | - Thomas E. Nichols
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Big Data Institute, Li Ka Shing, Centre For Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK
- Department of Statistics, University of Warwick, Coventry, UK
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20
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Vohra R, Campbell MD, Park J, Whang S, Gravelle K, Wang YN, Hwang JH, Marcinek DJ, Lee D. Increased tumour burden alters skeletal muscle properties in the KPC mouse model of pancreatic cancer. JCSM Rapid Commun 2020; 3:44-55. [PMID: 33073264 PMCID: PMC7566781 DOI: 10.1002/rco2.13] [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] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
BACKGROUND Cancer cachexia is a multifactorial wasting syndrome that is characterized by the loss of skeletal muscle mass and weakness, which compromises physical function, reduces quality of life, and ultimately can lead to mortality. Experimental models of cancer cachexia have recapitulated this skeletal muscle atrophy and consequent decline in muscle force generating capacity. We address these issues in a novel transgenic mouse model Kras, Trp53 and Pdx-1-Cre (KPC) of pancreatic ductal adenocarcinoma (PDA) using multi-parametric magnetic resonance (mp-MR) measures. METHODS KPC mice (n = 10) were divided equally into two groups (n = 5/group) depending on the size of the tumor i.e. tumor size <250 mm3 and >250 mm3. Using mp-MR measures, we demonstrated the changes in the gastrocnemius muscle at the microstructural level. In addition, we evaluated skeletal muscle contractile function in KPC mice using an in vivo approach. RESULTS Increase in tumor size resulted in decrease in gastrocnemius maximum cross sectional area, decrease in T2 relaxation time, increase in magnetization transfer ratio, decrease in mean diffusivity, and decrease in radial diffusivity of water across the muscle fibers. Finally, we detected significant decrease in absolute and specific force production of gastrocnemius muscle with increase in tumor size. CONCLUSIONS Our findings indicate that increase in tumor size may cause alterations in structural and functional parameters of skeletal muscles and that MR parameters may be used as sensitive biomarkers to noninvasively detect structural changes in cachectic muscles.
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Affiliation(s)
- Ravneet Vohra
- Department of Radiology, University of Washington, Seattle,
USA
| | | | - Joshua Park
- Department of Radiology, University of Washington, Seattle,
USA
| | - Stella Whang
- Department of Medicine, University of Washington, Seattle,
USA
| | - Kayla Gravelle
- Department of Medicine, University of Washington, Seattle,
USA
| | - Yak-Nam Wang
- Applied Physics Laboratory, University of Washington,
Seattle, USA
| | - Joo-Ha Hwang
- Division of Gastroenterology and Hepatology, Stanford
University, Stanford, USA
| | | | - Donghoon Lee
- Department of Radiology, University of Washington, Seattle,
USA
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21
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de Boer JN, van Hoogdalem M, Mandl RCW, Brummelman J, Voppel AE, Begemann MJH, van Dellen E, Wijnen FNK, Sommer IEC. Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts. NPJ Schizophr 2020; 6:10. [PMID: 32313047 DOI: 10.1038/s41537-020-0099-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 02/28/2020] [Indexed: 01/04/2023]
Abstract
Language deviations are a core symptom of schizophrenia. With the advances in computational linguistics, language can be easily assessed in exact and reproducible measures. This study investigated how language characteristics relate to schizophrenia diagnosis, symptom, severity and integrity of the white matter language tracts in patients with schizophrenia and healthy controls. Spontaneous speech was recorded and diffusion tensor imaging was performed in 26 schizophrenia patients and 22 controls. We were able to classify both groups with a sensitivity of 89% and a specificity of 82%, based on mean length of utterance and clauses per utterance. Language disturbances were associated with negative symptom severity. Computational language measures predicted language tract integrity in patients (adjusted R2 = 0.467) and controls (adjusted R2 = 0.483). Quantitative language analyses have both clinical and biological validity, offer a simple, helpful marker of both severity and underlying pathology, and provide a promising tool for schizophrenia research and clinical practice.
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22
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Lehmann N, Villringer A, Taubert M. Colocalized White Matter Plasticity and Increased Cerebral Blood Flow Mediate the Beneficial Effect of Cardiovascular Exercise on Long-Term Motor Learning. J Neurosci 2020; 40:2416-2429. [PMID: 32041897 PMCID: PMC7083530 DOI: 10.1523/jneurosci.2310-19.2020] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 12/12/2019] [Accepted: 01/21/2020] [Indexed: 12/11/2022] Open
Abstract
Cardiovascular exercise (CE) is a promising intervention strategy to facilitate cognition and motor learning in healthy and diseased populations of all ages. CE elevates humoral parameters, such as growth factors, and stimulates brain changes potentially relevant for learning and behavioral adaptations. However, the causal relationship between CE-induced brain changes and human's ability to learn remains unclear. We tested the hypothesis that CE elicits a positive effect on learning via alterations in brain structure (morphological changes of gray and white matter) and function (functional connectivity and cerebral blood flow in resting state). We conducted a randomized controlled trial with healthy male and female human participants to compare the effects of a 2 week CE intervention against a non-CE control group on subsequent learning of a challenging new motor task (dynamic balancing; DBT) over 6 consecutive weeks. We used multimodal neuroimaging [T1-weighted magnetic resonance imaging (MRI), diffusion-weighted MRI, perfusion-weighted MRI, and resting state functional MRI] to investigate the neural mechanisms mediating between CE and learning. As expected, subjects receiving CE subsequently learned the DBT at a higher rate. Using a modified nonparametric combination approach along with multiple mediator analysis, we show that this learning boost was conveyed by CE-induced increases in cerebral blood flow in frontal brain regions and changes in white matter microstructure in frontotemporal fiber tracts. Our study revealed neural mechanisms for the CE-learning link within the brain, probably allowing for a higher flexibility to adapt to highly novel environmental stimuli, such as learning a complex task.SIGNIFICANCE STATEMENT It is established that cardiovascular exercise (CE) is an effective approach to promote learning and memory, yet little is known about the underlying neural transfer mechanisms through which CE acts on learning. We provide evidence that CE facilitates learning in human participants via plasticity in prefrontal white matter tracts and a colocalized increase in cerebral blood flow. Our findings are among the first to demonstrate a transfer potential of experience-induced brain plasticity. In addition to practical implications for health professionals and coaches, our work paves the way for future studies investigating effects of CE in patients suffering from prefrontal hypoperfusion or white matter diseases.
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Affiliation(s)
- Nico Lehmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany,
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, 39104 Magdeburg, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Mind and Brain Institute, Charité and Humboldt University, 10117 Berlin, Germany, and
| | - Marco Taubert
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, 39104 Magdeburg, Germany
- Center for Behavioral and Brain Science, Otto von Guericke University, 39106 Magdeburg, Germany
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23
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Góngora D, Vega‐Hernández M, Jahanshahi M, Valdés‐Sosa PA, Bringas‐Vega ML. Crystallized and fluid intelligence are predicted by microstructure of specific white-matter tracts. Hum Brain Mapp 2020; 41:906-916. [PMID: 32026600 PMCID: PMC7267934 DOI: 10.1002/hbm.24848] [Citation(s) in RCA: 20] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 09/19/2019] [Accepted: 10/17/2019] [Indexed: 01/10/2023] Open
Abstract
Studies of the neural basis of intelligence have focused on comparing brain imaging variables with global scales instead of the cognitive domains integrating these scales or quotients. Here, the relation between mean tract-based fractional anisotropy (mTBFA) and intelligence indices was explored. Deterministic tractography was performed using a regions of interest approach for 10 white-matter fascicles along which the mTBFA was calculated. The study sample included 83 healthy individuals from the second wave of the Cuban Human Brain Mapping Project, whose WAIS-III intelligence quotients and indices were obtained. Inspired by the "Watershed model" of intelligence, we employed a regularized hierarchical Multiple Indicator, Multiple Causes model (MIMIC), to assess the association of mTBFA with intelligence scores, as mediated by latent variables summarizing the indices. Regularized MIMIC, used due to the limited sample size, selected relevant mTBFA by means of an elastic net penalty and achieved good fits to the data. Two latent variables were necessary to describe the indices: Fluid intelligence (Perceptual Organization and Processing Speed indices) and Crystallized Intelligence (Verbal Comprehension and Working Memory indices). Regularized MIMIC revealed effects of the forceps minor tract on crystallized intelligence and of the superior longitudinal fasciculus on fluid intelligence. The model also detected the significant effect of age on both latent variables.
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Affiliation(s)
- Daylín Góngora
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- Cuban Neuroscience CenterHavanaCuba
| | | | - Marjan Jahanshahi
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- UCL Queen Square Institute of NeurologyLondonUK
| | - Pedro A. Valdés‐Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- Cuban Neuroscience CenterHavanaCuba
| | - Maria L. Bringas‐Vega
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengduChina
- Cuban Neuroscience CenterHavanaCuba
| | - CHBMP
- Cuban Neuroscience CenterHavanaCuba
- Ministry of Science, Technology and Environment of CubaHavanaCuba
- Ministry of Public Health of Republic of CubaHavanaCuba
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24
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Sagnier S, Catheline G, Dilharreguy B, Linck PA, Coupé P, Munsch F, Bigourdan A, Debruxelles S, Poli M, Olindo S, Renou P, Rouanet F, Dousset V, Berthoz S, Tourdias T, Sibon I. Normal-Appearing White Matter Integrity Is a Predictor of Outcome After Ischemic Stroke. Stroke 2020; 51:449-456. [PMID: 31906830 DOI: 10.1161/strokeaha.119.026886] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background and Purpose- The aim of the present study was to evaluate the relationship between normal-appearing white matter (NAWM) integrity and postischemic stroke recovery in 4 main domains including cognition, mood, gait, and dependency. Methods- A prospective study was conducted, including patients diagnosed for an ischemic supratentorial stroke on a 3T brain MRI performed 24 to 72 hours after symptom onset. Clinical assessment 1 year after stroke included a Montreal Cognitive Assessment, an Isaacs set test, a Zazzo cancelation task, a Hospital Anxiety and Depression scale, a 10-meter walking test, and a modified Rankin Scale (mRS). Diffusion tensor imaging parameters in the NAWM were computed using FMRIB (Functional Magnetic Resonance Imaging of the Brain) Diffusion Toolbox. The relationships between mean NAWM diffusion tensor imaging parameters and the clinical scores were assessed using linear and ordinal regression analyses, including the volumes of white matter hyperintensities, gray matter, and ischemic stroke as radiological covariates. Results- Two hundred seven subjects were included (66±13 years old; 67% men; median National Institutes of Health Stroke Scale score, 3; interquartile range, 2-6). In the models including only radiological variables, NAWM fractional anisotropy was associated with the mRS and the cognitive scores. After adjusting for demographic confounders, NAWM fractional anisotropy remained a significant predictor of mRS (β=-0.24; P=0.04). Additional path analysis showed that NAWM fractional anisotropy had a direct effect on mRS (β=-0.241; P=0.001) and a less important indirect effect mediating white matter hyperintensity burden. Similar results were found with mean diffusivity, axial diffusivity, and radial diffusivity. In further subgroup analyses, a relationship between NAWM integrity in widespread white matter tracts, mRS, and Isaacs set test was found in right hemispheric strokes. Conclusions- NAWM diffusion tensor imaging parameters measured early after an ischemic stroke are independent predictors of functional outcome and may be additional markers to include in studies evaluating poststroke recovery.
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Affiliation(s)
- Sharmila Sagnier
- From the UMR-5287-CNRS, Université de Bordeaux, EPHE PSL Research University, France (S.S., G.C., B.D., S.B., I.S.).,CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - Gwenaëlle Catheline
- From the UMR-5287-CNRS, Université de Bordeaux, EPHE PSL Research University, France (S.S., G.C., B.D., S.B., I.S.)
| | - Bixente Dilharreguy
- From the UMR-5287-CNRS, Université de Bordeaux, EPHE PSL Research University, France (S.S., G.C., B.D., S.B., I.S.)
| | | | - Pierrick Coupé
- UMR-5800-CNRS, Université de Bordeaux, LaBRI, Talence, France (P.C.)
| | - Fanny Munsch
- Beth Israel Deaconess Medical Center, Harvard University, Boston, MA (F.M.)
| | - Antoine Bigourdan
- CHU de Bordeaux, Neuroradiologie, France (P.-A.L., A.B., V.D., T.T.)
| | - Sabrina Debruxelles
- CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - Mathilde Poli
- CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - Stéphane Olindo
- CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - Pauline Renou
- CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - François Rouanet
- CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
| | - Vincent Dousset
- CHU de Bordeaux, Neuroradiologie, France (P.-A.L., A.B., V.D., T.T.).,INSERM-U862, Neurocentre Magendie, Bordeaux, France (V.D., T.T.)
| | - Sylvie Berthoz
- From the UMR-5287-CNRS, Université de Bordeaux, EPHE PSL Research University, France (S.S., G.C., B.D., S.B., I.S.).,Département de Psychiatrie de l'Adolescent et du Jeune Adulte, Institut Mutualiste Montsouris, Paris, France (S.B.)
| | - Thomas Tourdias
- CHU de Bordeaux, Neuroradiologie, France (P.-A.L., A.B., V.D., T.T.).,INSERM-U862, Neurocentre Magendie, Bordeaux, France (V.D., T.T.)
| | - Igor Sibon
- From the UMR-5287-CNRS, Université de Bordeaux, EPHE PSL Research University, France (S.S., G.C., B.D., S.B., I.S.).,CHU de Bordeaux, Unité Neuro-vasculaire, France (S.S., S.D., M.P., S.O., P.R., F.R., I.S.)
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25
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Tsai YJ, Huang CJ, Hung CL, Kao SC, Lin CF, Hsieh SS, Hung TM. Muscular fitness, motor competence, and processing speed in preschool children. European Journal of Developmental Psychology 2019. [DOI: 10.1080/17405629.2019.1661835] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Yu-Jung Tsai
- Department of Physical Education, National Taiwan Normal University, Taipei, Taiwan (R.O.C.)
| | - Chung-Ju Huang
- Graduate Institute of Sport Pedagogy, University of Taipei, Taipei, Taiwan (R.O.C.)
| | - Chiao-Ling Hung
- Department of Athletics, National Taiwan University, Taipei, Taiwan (R.O.C.)
| | - Shih-Chun Kao
- Department of Health and Kinesiology, Purdue University, West Lafayette, IN, USA
| | - Chi-Fang Lin
- Department of Physical Education, National Taiwan Normal University, Taipei, Taiwan (R.O.C.)
| | - Shu-Shih Hsieh
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Tsung-Min Hung
- Department of Physical Education, National Taiwan Normal University, Taipei, Taiwan (R.O.C.)
- Institute for Research Excellence in Learning Science, National Taiwan Normal University, Taipei, Taiwan (R.O.C.)
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26
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Atalay K, Barrett GF, Staneva A. The effect of retirement on elderly cognitive functioning. J Health Econ 2019; 66:37-53. [PMID: 31108435 DOI: 10.1016/j.jhealeco.2019.04.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 03/09/2019] [Accepted: 04/25/2019] [Indexed: 05/25/2023]
Abstract
Cognitive functioning exhibits a clear lifecycle pattern with a general deterioration over older ages. This article estimates the short-term effect of retirement on cognitive performance of elderly Australians by exploiting the exogenous variation in retirement decisions induced by changes in social security eligibility rules. The empirical results show that on average retirement has a negative but modest effect on cognition, and the rate of cognitive decline with age is greater for men than women. The results for women display no significant effects on working memory and speed of information processing. The article further adds to the literature by providing evidence on the possible mechanisms through which retirement could affect individual's cognitive performance. We find that moving into retirement leads women to increase the time spent in mental and household activities, which may in part explain the modest effect we observe for women.
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Affiliation(s)
- Kadir Atalay
- School of Economics, The University of Sydney, Australia
| | | | - Anita Staneva
- School of Economics, The University of Sydney, Australia.
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27
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Booth T, Dykiert D, Corley J, Gow AJ, Morris Z, Muñoz Maniega S, Royle NA, Del C Valdés Hernández M, Starr JM, Penke L, Bastin ME, Wardlaw JM, Deary IJ. Reaction time variability and brain white matter integrity. Neuropsychology 2019; 33:642-657. [PMID: 31246073 PMCID: PMC6683973 DOI: 10.1037/neu0000483] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Objective: Mean speed of responding is the most commonly used measure in the assessment of reaction time (RT). An alternative measure is intraindividual variability (IIV): the inconsistency of responding across multiple trials of a test. IIV has been suggested as an important indicator of central nervous system functioning, and as such, there has been increasing interest in the associations between IIV and brain imaging metrics. Results however, have been inconsistent. The present seeks to provide a comprehensive evaluation of the associations between a variety of measures of brain white matter integrity and individual differences in choice RT (CRT) IIV. Method: MRI brain scans of members of the Lothian Birth Cohort 1936 were assessed to obtain measures of the volume and severity of white matter hyperintensities, and the integrity of brain white matter tracts. CRT was assessed with a 4 CRT task on a separate occasion. Data were analyzed using multiple regression (N range = 358–670). Results: Greater volume of hyperintensities and more severe hyperintensities in frontal regions were associated with higher CRT IIV. White matter tract integrity, as assessed by both fractional anisotropy and mean diffusivity, showed the smallest effect sizes in associations with CRT IIV. Associations with hyperintensities were attenuated and no longer significant after controlling for M CRT. Conclusions: Taken together, the results of the present study suggested that IIV was not incrementally predictive of white matter integrity over mean speed. This is in contrast to previous reports, and highlights the need for further study. Variability in speeded cognitive test performance has been argued to be a potential early marker of cognitive decline and progression into mild cognitive impairment in aging. Evidence as to the robustness of the relationship, and the potential neurological underpinnings is varied. Our results suggest that average speeded performance, not variability, may be more reliably related to various measures of the brain. These findings are in contrast to much of the extant literature, highlighting the need for further research.
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Affiliation(s)
- Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology
| | | | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology
| | - Alan J Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology
| | - Zoe Morris
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, The University of Edinburgh
| | | | | | | | | | - Lars Penke
- Centre for Cognitive Ageing and Cognitive Epidemiology
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology
| | - Joanna M Wardlaw
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, The University of Edinburgh
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology
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28
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Nicholls LAB, English B. Multimodal coding and strategic approach in young and older adults’ visual working memory performance. Aging, Neuropsychology, and Cognition 2019; 27:83-113. [DOI: 10.1080/13825585.2019.1585515] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
| | - Brad English
- Nottinghamshire Healthcare NHS Foundation Trust, Clinical Psychology Department, Fern House, Highbury Hospital, Nottingham, UK
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29
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Jansen PR, Muetzel RL, Polderman TJ, Jaddoe VW, Verhulst FC, van der Lugt A, Tiemeier H, Posthuma D, White T. Polygenic Scores for Neuropsychiatric Traits and White Matter Microstructure in the Pediatric Population. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2019; 4:243-50. [DOI: 10.1016/j.bpsc.2018.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 07/08/2018] [Accepted: 07/09/2018] [Indexed: 12/31/2022]
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30
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Roquet A, Hinault T, Badier JM, Lemaire P. Aging and Sequential Strategy Interference: A Magnetoencephalography Study in Arithmetic Problem Solving. Front Aging Neurosci 2018; 10:232. [PMID: 30135650 PMCID: PMC6092518 DOI: 10.3389/fnagi.2018.00232] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [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: 02/21/2018] [Accepted: 07/17/2018] [Indexed: 11/13/2022] Open
Abstract
This study investigated age-related changes in the neural bases of sequential strategy interference. Sequential strategy interference refers to decreased strategy interference (i.e., poorer performance when the cued strategy is not the best) after executing a poorer strategy relative to after a better strategy. Young and older adults performed a computational estimation task (e.g., providing approximate products to two-digit multiplication problems, like 38 × 74) and were matched on behavioral sequential strategy interference effects. Analyses of magnetoencephalography (MEG) data revealed differences between young and older adults in brain activities underlying sequential strategy interference. More specifically, relative to young adults, older adults showed additional recruitments in frontal, temporal, and parietal regions. Also, age-related differences were found in the temporal dynamics of brain activations, with modulations occurring both earlier and later in older than young adults. These results suggest that highly functioning older adults rely on additional mechanisms to process sequential strategy interference as efficiently as young adults. Our findings inform mechanisms by which highly functioning older adults obtain as good performance as young adults, and suggest that these older adults may compensate deleterious effects of aging to efficiently execute arithmetic strategies.
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Affiliation(s)
| | - Thomas Hinault
- Aix-Marseille Université & CNRS, Marseille, France.,Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - Jean-Michel Badier
- Aix-Marseille Université, INS, Marseille, France.,INSERM U1106, Marseille, France
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31
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Early JJ, Cole KL, Williamson JM, Swire M, Kamadurai H, Muskavitch M, Lyons DA. An automated high-resolution in vivo screen in zebrafish to identify chemical regulators of myelination. eLife 2018; 7:35136. [PMID: 29979149 PMCID: PMC6056238 DOI: 10.7554/elife.35136] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [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: 01/16/2018] [Accepted: 07/05/2018] [Indexed: 12/23/2022] Open
Abstract
Myelinating oligodendrocytes are essential for central nervous system (CNS) formation and function. Their disruption is implicated in numerous neurodevelopmental, neuropsychiatric and neurodegenerative disorders. However, recent studies have indicated that oligodendrocytes may be tractable for treatment of disease. In recent years, zebrafish have become well established for the study of myelinating oligodendrocyte biology and drug discovery in vivo. Here, by automating the delivery of zebrafish larvae to a spinning disk confocal microscope, we were able to automate high-resolution imaging of myelinating oligodendrocytes in vivo. From there, we developed an image analysis pipeline that facilitated a screen of compounds with epigenetic and post-translational targets for their effects on regulating myelinating oligodendrocyte number. This screen identified novel compounds that strongly promote myelinating oligodendrocyte formation in vivo. Our imaging platform and analysis pipeline is flexible and can be employed for high-resolution imaging-based screens of broad interest using zebrafish.
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Affiliation(s)
- Jason J Early
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,United Kingdom Zebrafish screening facility, University of Edinburgh, Edinburgh, United Kingdom
| | - Katy Lh Cole
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jill M Williamson
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthew Swire
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,MRC Centre for Regenerative Medicine, Edinburgh, United Kingdom
| | | | | | - David A Lyons
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.,United Kingdom Zebrafish screening facility, University of Edinburgh, Edinburgh, United Kingdom
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32
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Hallgrímsson HT, Cieslak M, Foschini L, Grafton ST, Singh AK. Spatial coherence of oriented white matter microstructure: Applications to white matter regions associated with genetic similarity. Neuroimage 2018; 172:390-403. [PMID: 29410205 DOI: 10.1016/j.neuroimage.2018.01.050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 12/31/2017] [Accepted: 01/19/2018] [Indexed: 11/26/2022] Open
Abstract
We present a method to discover differences between populations with respect to the spatial coherence of their oriented white matter microstructure in arbitrarily shaped white matter regions. This method is applied to diffusion MRI scans of a subset of the Human Connectome Project dataset: 57 pairs of monozygotic and 52 pairs of dizygotic twins. After controlling for morphological similarity between twins, we identify 3.7% of all white matter as being associated with genetic similarity (35.1 k voxels, p<10-4, false discovery rate 1.5%), 75% of which spatially clusters into twenty-two contiguous white matter regions. Furthermore, we show that the orientation similarity within these regions generalizes to a subset of 47 pairs of non-twin siblings, and show that these siblings are on average as similar as dizygotic twins. The regions are located in deep white matter including the superior longitudinal fasciculus, the optic radiations, the middle cerebellar peduncle, the corticospinal tract, and within the anterior temporal lobe, as well as the cerebellum, brain stem, and amygdalae. These results extend previous work using undirected fractional anisotrophy for measuring putative heritable influences in white matter. Our multidirectional extension better accounts for crossing fiber connections within voxels. This bottom up approach has at its basis a novel measurement of coherence within neighboring voxel dyads between subjects, and avoids some of the fundamental ambiguities encountered with tractographic approaches to white matter analysis that estimate global connectivity.
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Affiliation(s)
| | - Matthew Cieslak
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA
| | - Luca Foschini
- Department of Computer Science, University of California, Santa Barbara, CA 93106, USA
| | - Scott T Grafton
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA
| | - Ambuj K Singh
- Department of Computer Science, University of California, Santa Barbara, CA 93106, USA
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Cole JH, Ritchie SJ, Bastin ME, Valdés Hernández MC, Muñoz Maniega S, Royle N, Corley J, Pattie A, Harris SE, Zhang Q, Wray NR, Redmond P, Marioni RE, Starr JM, Cox SR, Wardlaw JM, Sharp DJ, Deary IJ. Brain age predicts mortality. Mol Psychiatry 2018; 23:1385-1392. [PMID: 28439103 PMCID: PMC5984097 DOI: 10.1038/mp.2017.62] [Citation(s) in RCA: 362] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 01/18/2017] [Accepted: 02/17/2017] [Indexed: 12/30/2022]
Abstract
Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.
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Affiliation(s)
- J H Cole
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, UK,Medicine, Imperial College London, Computational, Cognitive and Clinical Neuroimaging Laboratory, Burlington Danes Building, Du Cane Road, London W12 0NN, UK. E-mail:
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - M C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - N Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Q Zhang
- Institute for Molecular Bioscience, The University of Queensland, QLD, Australia
| | - N R Wray
- Institute for Molecular Bioscience, The University of Queensland, QLD, Australia,Queensland Brain Institute, The University of Queensland, QLD, Australia
| | - P Redmond
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - R E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Centre for Genomic and Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK,Queensland Brain Institute, The University of Queensland, QLD, Australia
| | - J M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - D J Sharp
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh, UK
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Abstract
In the face of shifting demographics and an increase in human longevity, it is important to examine carefully what is known about cognitive ageing, and to identify and promote possibly malleable lifestyle and health-related factors that might mitigate age-associated cognitive decline. The Lothian Birth Cohorts of 1921 (LBC1921, n = 550) and 1936 (LBC1936, n = 1091) are longitudinal studies of cognitive and brain ageing based in Scotland. Childhood IQ data are available for these participants, who were recruited in later life and then followed up regularly. This overview summarises some of the main LBC findings to date, illustrating the possible genetic and environmental contributions to cognitive function (level and change) and brain imaging biomarkers in later life. Key associations include genetic variation, health and fitness, psychosocial and lifestyle factors, and aspects of the brain's structure. It addresses some key methodological issues such as confounding by early-life intelligence and social factors and emphasises areas requiring further investigation. Overall, the findings that have emerged from the LBC studies highlight that there are multiple correlates of cognitive ability level in later life, many of which have small effects, that there are as yet few reliable predictors of cognitive change, and that not all of the correlates have independent additive associations. The concept of marginal gains, whereby there might be a cumulative effect of small incremental improvements across a wide range of lifestyle and health-related factors, may offer a useful way to think about and promote a multivariate recipe for healthy cognitive and brain ageing.
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Affiliation(s)
- J Corley
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - S R Cox
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
| | - I J Deary
- Department of Psychology,The University of Edinburgh,Edinburgh,UK
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35
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Field TS, Doubal FN, Johnson W, Backhouse E, McHutchison C, Cox S, Corley J, Pattie A, Gow AJ, Shenkin S, Cvoro V, Morris Z, Staals J, Bastin M, Deary IJ, Wardlaw JM. Early life characteristics and late life burden of cerebral small vessel disease in the Lothian Birth Cohort 1936. Aging (Albany NY) 2016; 8:2039-61. [PMID: 27652981 DOI: 10.18632/aging.101043] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 09/04/2016] [Indexed: 11/25/2022]
Abstract
It is unknown whether relations between early-life factors and overall health in later life apply to burden of cerebral small vessel disease (cSVD), a major cause of stroke and dementia. We explored relations between early-life factors and cSVD in the Lothian Birth Cohort, a healthy aging cohort. Participants were recruited at age 70 (N = 1091); most had completed a test of cognitive ability at age 11 as part of the Scottish Mental Survey of 1947. Of those, 700 participants had brain MRI that could be rated for cSVD conducted at age 73. Presence of lacunes, white matter hyperintensities, microbleeds, and perivascular spaces were summed in a score of 0-4 representing all MRI cSVD features. We tested associations with early-life factors using multivariate logistic regression. Greater SVD score was significantly associated with lower age-11 IQ (OR higher SVD score per SD age-11 IQ = .78, 95%CI 0.65-.95, p=.01). The associations between SVD score and own job class (OR higher job class, .64 95%CI .43-.95, p=.03), age-11 deprivation index (OR per point deprivation score, 1.08, 95%CI 1.00-1.17, p=.04), and education (OR some qualifying education, .60 95%CI .37-.98, p=.04) trended towards significance (p<.05 for all) but did not meet thresholds for multiple testing. No early-life factor was significantly associated with any one individual score component. Early-life factors may contribute to age-73 burden of cSVD. These relations, and the potential for early social interventions to improve brain health, deserve further study.
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36
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Alloza C, Bastin ME, Cox SR, Gibson J, Duff B, Semple SI, Whalley HC, Lawrie SM. Central and non-central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia. Hum Brain Mapp 2017; 38:5919-5930. [PMID: 28881417 DOI: 10.1002/hbm.23798] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 08/02/2017] [Accepted: 08/24/2017] [Indexed: 12/25/2022] Open
Abstract
Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder. However, the importance of non-central networks still remains unclear. Thus, we specifically examined network-averaged fractional anisotropy (mean edge weight) in central and non-central subnetworks. Connections with the highest betweenness centrality within the average network (>75% of centrality values) were selected to represent the central subnetwork. The remaining connections were assigned to the non-central subnetwork. Additionally, we calculated graph theory measures from the average network (connections that occur in at least 2/3 of participants). Density, strength, global efficiency, and clustering coefficient were significantly lower in patients compared with healthy controls for the average network (pFDR < 0.05). All metrics across networks were significantly associated with intelligence (pFDR < 0.05). There was a tendency towards significance for a correlation between intelligence and PGRS for schizophrenia (r = -0.508, p = 0.052) that was significantly mediated by central and non-central mean edge weight and every graph metric from the average network. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. Hum Brain Mapp 38:5919-5930, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Clara Alloza
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom.,Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, United Kingdom.,Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, United Kingdom
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom.,Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom.,Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, United Kingdom
| | - Jude Gibson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Barbara Duff
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Scott I Semple
- Clinical Research Imaging Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
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Johnson CL, Telzer EH. Magnetic resonance elastography for examining developmental changes in the mechanical properties of the brain. Dev Cogn Neurosci 2017; 33:176-181. [PMID: 29239832 PMCID: PMC5832528 DOI: 10.1016/j.dcn.2017.08.010] [Citation(s) in RCA: 35] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Revised: 08/19/2017] [Accepted: 08/28/2017] [Indexed: 12/13/2022] Open
Abstract
Magnetic resonance elastography (MRE) is a quantitative imaging technique for noninvasively characterizing tissue mechanical properties, and has recently emerged as a valuable tool for neuroimaging. The measured mechanical properties reflect the microstructural composition and organization of neural tissue, and have shown significant effects in many neurological conditions and normal, healthy aging, and evidence has emerged supporting novel relationships between mechanical structure and cognitive function. The sensitivity of MRE to brain structure, function, and health make it an ideal technique for studying the developing brain; however, brain MRE studies on children and adolescents have only just begun. In this article, we review brain MRE and its findings, discuss its potential role in developmental neuroimaging, and provide suggestions for researchers interested in adopting this technique.
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Affiliation(s)
- Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, 150 Academy St., Newark, DE 19716, United States.
| | - Eva H Telzer
- Department of Psychology and Neuroscience, University of North Carolina, 235 E Cameron Ave, Chapel Hill, NC 27599, United States.
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38
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Kochan NA, Bunce D, Pont S, Crawford JD, Brodaty H, Sachdev PS. Is intraindividual reaction time variability an independent cognitive predictor of mortality in old age? Findings from the Sydney Memory and Ageing Study. PLoS One 2017; 12:e0181719. [PMID: 28792946 DOI: 10.1371/journal.pone.0181719] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 07/06/2017] [Indexed: 11/24/2022] Open
Abstract
Intraindividual variability of reaction time (IIVRT), a proposed cognitive marker of neurobiological disturbance, increases in old age, and has been associated with dementia and mortality. The extent to which IIVRT is an independent predictor of mortality, however, is unclear. This study investigated the association of IIVRT and all-cause mortality while accounting for cognitive level, incident dementia and biomedical risk factors in 861 participants aged 70–90 from the Sydney Memory and Ageing Study. Participants completed two computerised reaction time (RT) tasks (76 trials in total) at baseline, and comprehensive medical and neuropsychological assessments every 2 years. Composite RT measures were derived from the two tasks—the mean RT and the IIVRT measure computed from the intraindividual standard deviation of the RTs (with age and time-on-task effects partialled out). Consensus dementia diagnoses were made by an expert panel of clinicians using clinical criteria, and mortality data were obtained from a state registry. Cox proportional hazards models estimated the association of IIVRT and mean RT with survival time over 8 years during which 191 (22.2%) participants died. Greater IIVRT but not mean RT significantly predicted survival time after adjusting for age, sex, global cognition score, cardiovascular risk index and apolipoprotein ɛ4 status. After excluding incident dementia cases, the association of IIVRT with mortality changed very little. Our findings suggest that greater IIVRT uniquely predicts shorter time to death and that lower global cognition and prodromal dementia in older individuals do not explain this relationship.
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Haynes BI, Bauermeister S, Bunce D. A Systematic Review of Longitudinal Associations Between Reaction Time Intraindividual Variability and Age-Related Cognitive Decline or Impairment, Dementia, and Mortality. J Int Neuropsychol Soc 2017; 23:431-45. [PMID: 28462758 DOI: 10.1017/S1355617717000236] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Intraindividual variability (IIV) in reaction time refers to the trial-to-trial fluctuations in responding across a given cognitive task. Cross-sectional research suggests that IIV increases with normal and neuropathological ageing and it may serve as a marker of neurobiological integrity. This raises the possibility that IIV may also predict future cognitive decline and, indeed, neuropathology. Therefore, we conducted a systematic review to address these issues. METHODS A search of electronic databases Embase, Medline, PsycINFO, and Web of Science was completed on May 17, 2016 that identified longitudinal investigations of IIV in middle-aged or older adults. RESULTS A total of 688 studies were initially identified of which 22 met the inclusion criteria. Nine included longitudinal IIV measures and 17 predicted subsequent outcome (cognitive decline or impairment, dementia, mortality) from baseline IIV. The results suggested IIV increased over time, particularly in participants aged over 75 years. Greater baseline IIV was consistently associated with increased risk of adverse outcomes including cognitive decline or impairment, and mortality. CONCLUSIONS Increased IIV over time is associated with normal ageing. However, further increases in IIV over and above those found in normal ageing may be a risk factor for future cognitive impairment or mortality. Measures of IIV may, therefore, have considerable potential as a supplement to existing clinical assessment to aid identification of individuals at risk of adverse outcomes such as dementia or death. (JINS, 2017, 23, 431-445).
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Haynes BI, Bunce D, Kochan NA, Wen W, Brodaty H, Sachdev PS. Associations between reaction time measures and white matter hyperintensities in very old age. Neuropsychologia 2017; 96:249-255. [PMID: 28115193 DOI: 10.1016/j.neuropsychologia.2017.01.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Revised: 12/23/2016] [Accepted: 01/20/2017] [Indexed: 10/20/2022]
Abstract
In old age, a relationship has been reported between intraindividual variability (IIV) in reaction time and white matter integrity as evidenced by white matter hyperintensities (WMH). However, it is unclear how far such associations are due to incipient neurodegenerative pathology in the samples investigated. The present study examined the relationship between IIV and WMH in older individuals (N=526) drawn from the Sydney Memory and Ageing Study. Using a complex reaction time (RT) task, greater IIV and mean-RT were related to a higher WMH burden in the frontal lobe. Critically, significant associations remained having taken future dementia into account suggesting that they were not explained by incipient dementia. Additionally, independent measures of executive function accounted for the association between RT metrics and WHM. The results are consistent with the view that frontally-supported cognitive processes are involved in IIV-WMH relations, and that RT measures are sensitive to compromise in white matter structures in non-demented older individuals.
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Affiliation(s)
- Becky I Haynes
- School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - David Bunce
- School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK; Centre for Health Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia.
| | - Nicole A Kochan
- Centre for Health Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick, NSW 2031, Australia
| | - Wei Wen
- Centre for Health Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick, NSW 2031, Australia
| | - Henry Brodaty
- Centre for Health Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; Dementia Collaborative Research Centre, School of Psychiatry, UNSW Medicine, The University of New South Wales, Sydney, NSW 2052, Australia; Academic Department for Old Age Psychiatry, Prince of Wales Hospital, Avoca Street, Randwick, NSW 2031, Australia
| | - Perminder S Sachdev
- Centre for Health Brain Ageing (CHeBA), School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, Barker Street, Randwick, NSW 2031, Australia
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41
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Cox SR, Dickie DA, Ritchie SJ, Karama S, Pattie A, Royle NA, Corley J, Aribisala BS, Valdés Hernández M, Muñoz Maniega S, Starr JM, Bastin ME, Evans AC, Wardlaw JM, Deary IJ. Associations between education and brain structure at age 73 years, adjusted for age 11 IQ. Neurology 2016; 87:1820-1826. [PMID: 27664981 PMCID: PMC5089529 DOI: 10.1212/wnl.0000000000003247] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 07/07/2016] [Indexed: 11/20/2022] Open
Abstract
Objective: To investigate how associations between education and brain structure in older age were affected by adjusting for IQ measured at age 11. Methods: We analyzed years of full-time education and measures from an MRI brain scan at age 73 in 617 community-dwelling adults born in 1936. In addition to average and vertex-wise cortical thickness, we measured total brain atrophy and white matter tract fractional anisotropy. Associations between brain structure and education were tested, covarying for sex and vascular health; a second model also covaried for age 11 IQ. Results: The significant relationship between education and average cortical thickness (β = 0.124, p = 0.004) was reduced by 23% when age 11 IQ was included (β = 0.096, p = 0.041). Initial associations between longer education and greater vertex-wise cortical thickness were significant in bilateral temporal, medial-frontal, parietal, sensory, and motor cortices. Accounting for childhood intelligence reduced the number of significant vertices by >90%; only bilateral anterior temporal associations remained. Neither education nor age 11 IQ was significantly associated with total brain atrophy or tract-averaged fractional anisotropy. Conclusions: The association between years of education and brain structure ≈60 years later was restricted to cortical thickness in this sample; however, the previously reported associations between longer education and a thicker cortex are likely to be overestimates in terms of both magnitude and distribution. This finding has implications for understanding, and possibly ameliorating, life-course brain health.
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Affiliation(s)
- Simon R Cox
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria.
| | - David Alexander Dickie
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Stuart J Ritchie
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Sherif Karama
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Alison Pattie
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Natalie A Royle
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Janie Corley
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Benjamin S Aribisala
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Maria Valdés Hernández
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Susana Muñoz Maniega
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - John M Starr
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Mark E Bastin
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Alan C Evans
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Joanna M Wardlaw
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
| | - Ian J Deary
- From the Centre for Cognitive Ageing and Cognitive Epidemiology (S.R.C., S.J.R., A.P., N.A.R., B.S.A., M.V.H., S.M.M., J.M.S., M.E.B., J.M.W., I.J.D.), Department of Psychology (S.R.C., S.J.R., A.P., J.C., I.J.D.), Brain Research Imaging Centre (D.A.D.,N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), Neuroimaging Sciences, Centre for Clinical Brain Sciences, and Alzheimer Scotland Dementia Research Centre (J.M.S.), University of Edinburgh; Scottish Imaging Network (S.R.C., D.A.D., N.A.R., B.S.A., M.V.H., S.M.M., M.E.B., J.M.W.), a Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK; Department of Neurology and Neurosurgery (S.K., A.C.E.), McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal; Department of Psychiatry (S.K.), Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada; and Department of Computer Science (B.S.A.), Lagos State University, Lagos, Nigeria
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Golan D, Gross B, Miller A, Klil-Drori S, Lavi I, Shiller M, Honigman S, Almog R, Segol O. Cognitive Function of Patients with Crohn's Disease is Associated with Intestinal Disease Activity. Inflamm Bowel Dis 2016; 22:364-71. [PMID: 26398711 DOI: 10.1097/MIB.0000000000000594] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Systemic inflammation and nutritional deficiencies are characteristics of Crohn's disease (CD) and have been suggested to influence cognitive performance. This study assessed cognitive function in patients with CD. METHODS Participants were adult patients with CD arriving at routine follow-up. Subjective cognitive complaints, depression, anxiety, fatigue, and sleep were evaluated by validated questionnaires. CD characteristics, blood tests, and Crohn's disease activity index were obtained. Nutritional risk index was derived from serum albumin and change in body weight. Montreal cognitive assessment was used for screening. Patients with either subjective cognitive complaints or Montreal cognitive assessment score ≤ 26 were tested by a computerized cognitive testing battery, with analysis of scores in 7 cognitive domains (CogDs) and an average of the CogD scores-global cognitive score (GCS). Impaired CogD was defined as scoring more than 1 SD below age and education adjusted average. RESULTS A total of 105 patients were recruited and 61 were tested with computerized cognitive testing battery. Mean age was 39 ± 13 and mean education years were 14 ± 2. The most commonly impaired CogDs were information processing speed (33%) and verbal function (28%). Crohn's disease activity index, nutritional risk index, and hemoglobin were significantly correlated with GCS (r = -0.34, 0.39, 0.33; P = 0.007, 0.003, 0.01). Linear regression revealed significant correlations between Crohn's disease activity index, nutritional risk index, and GCS (β = -0.3, 0.29; P = 0.03, 0.04), independent of depression. This model explained 24% of the variance in GCS. CONCLUSIONS Cognitive performance is related to CD activity and nutritional status. The results provide insight into potential influence of nutrition and inflammation on cognitive function. Further studies on cognitive function of patients with CD are warranted.
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Magistro D, Takeuchi H, Nejad KK, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T, Yamamoto Y, Hanawa S, Araki T, Hashizume H, Sassa Y, Kawashima R. The Relationship between Processing Speed and Regional White Matter Volume in Healthy Young People. PLoS One 2015; 10:e0136386. [PMID: 26397946 PMCID: PMC4580478 DOI: 10.1371/journal.pone.0136386] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 08/04/2015] [Indexed: 12/21/2022] Open
Abstract
Processing speed is considered a key cognitive resource and it has a crucial role in all types of cognitive performance. Some researchers have hypothesised the importance of white matter integrity in the brain for processing speed; however, the relationship at the whole-brain level between white matter volume (WMV) and processing speed relevant to the modality or problem used in the task has never been clearly evaluated in healthy people. In this study, we used various tests of processing speed and Voxel-Based Morphometry (VBM) analyses, it is involves a voxel-wise comparison of the local volume of gray and white, to assess the relationship between processing speed and regional WMV (rWMV). We examined the association between processing speed and WMV in 887 healthy young adults (504 men and 383 women; mean age, 20.7 years, SD, 1.85). We performed three different multiple regression analyses: we evaluated rWMV associated with individual differences in the simple processing speed task, word-colour and colour-word tasks (processing speed tasks with words) and the simple arithmetic task, after adjusting for age and sex. The results showed a positive relationship at the whole-brain level between rWMV and processing speed performance. In contrast, the processing speed performance did not correlate with rWMV in any of the regions examined. Our results support the idea that WMV is associated globally with processing speed performance regardless of the type of processing speed task.
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Affiliation(s)
- Daniele Magistro
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- * E-mail:
| | - Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Keyvan Kashkouli Nejad
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yasuyuki Taki
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Devision of Meidcal Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Department of Radiology and Nuclear Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Atsushi Sekiguchi
- Devision of Meidcal Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Rui Nouchi
- Human and Social Response Research Division, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Yuka Kotozaki
- Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, JapanJapan Society for the Promotion of Science, Tokyo, Japan
| | - Seishu Nakagawa
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Carlos Makoto Miyauchi
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Kunio Iizuka
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Ryoichi Yokoyama
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Takamitsu Shinada
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yuki Yamamoto
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Sugiko Hanawa
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Tsuyoshi Araki
- Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, JapanJapan Society for the Promotion of Science, Tokyo, Japan
| | - Hiroshi Hashizume
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yuko Sassa
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Ryuta Kawashima
- Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, JapanJapan Society for the Promotion of Science, Tokyo, Japan
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Sala M, de Roos A, Blauw GJ, Middelkoop HAM, Jukema JW, Mooijaart SP, van Buchem MA, de Craen AJM, van der Grond J. Association between changes in brain microstructure and cognition in older subjects at increased risk for vascular disease. BMC Neurol 2015; 15:133. [PMID: 26249665 PMCID: PMC4545822 DOI: 10.1186/s12883-015-0396-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Accepted: 07/28/2015] [Indexed: 11/30/2022] Open
Abstract
Background The purpose of this study is to investigate whether changes in brain microstructure, detected by magnetization transfer imaging, are associated with cognition in older subjects at increased risk for vascular disease. Methods One hundred ninety three nondemented subjects (105 men, mean age 77 ± 3 years) from the Prospective Study of Pravastatin in the Elderly at Risk were included. To assess cross-sectional associations between magnetization transfer ratio (MTR) peak height and cognitive test scores, general linear model multivariate analysis was performed. Models were adjusted for age, sex, education level, vascular risk factors, individual white matter lesion volume, and brain atrophy. A repeated measures general linear model was used to investigate whether MTR peak height relates to cognitive test performance at baseline and 3.3-year follow-up. Results Cross-sectionally, MTR peak height was associated with performance on the STROOP test (unstandardized β = −0.27, p = 0.045), delayed Picture Word Learning (PWL) test (β = 0.48, p = 0.007), and the Letter Digit Coding test (β = 1.1, p = 0.006). Repeated measures general linear model analysis showed that individuals with low MTR peak height at baseline performed worse on the STROOP test compared to subjects with intermediate MTR peak height (mean time to complete the test at baseline and follow-up, lower versus middle tertile of MTR peak height: 61.6 versus 52.7 s, p = 0.019) or compared to subjects with high MTR peak height (p = 0.046). Similarly, low MTR peak height was associated with worse performance on the immediate (lower versus middle tertile, p = 0.023; lower versus higher tertile, p = 0.032) and delayed PWL test (lower versus middle, p = 0.004; lower versus higher, p = 0.012) at baseline and follow-up testing. Conclusions MTR peak height is associated with cognitive function in older subjects at increased risk for vascular disease. Electronic supplementary material The online version of this article (doi:10.1186/s12883-015-0396-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Michiel Sala
- Department of Radiology, C3-Q, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands.
| | - Albert de Roos
- Department of Radiology, C3-Q, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands.
| | | | | | - J Wouter Jukema
- Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Simon P Mooijaart
- Gerontology and Geriatrics, Leiden, The Netherlands. .,Consortium for Healthy Ageing, Leiden, The Netherlands.
| | - Mark A van Buchem
- Department of Radiology, C3-Q, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands. .,Consortium for Healthy Ageing, Leiden, The Netherlands.
| | - Anton J M de Craen
- Gerontology and Geriatrics, Leiden, The Netherlands. .,Consortium for Healthy Ageing, Leiden, The Netherlands.
| | - Jeroen van der Grond
- Department of Radiology, C3-Q, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands. .,Consortium for Healthy Ageing, Leiden, The Netherlands.
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Caprihan A, Jones T, Chen H, Lemke N, Abbott C, Qualls C, Canive J, Gasparovic C, Bustillo JR. The Paradoxical Relationship between White Matter, Psychopathology and Cognition in Schizophrenia: A Diffusion Tensor and Proton Spectroscopic Imaging Study. Neuropsychopharmacology 2015; 40:2248-57. [PMID: 25786581 DOI: 10.1038/npp.2015.72] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Revised: 02/23/2015] [Accepted: 02/24/2015] [Indexed: 12/19/2022]
Abstract
White matter disruption has been repeatedly documented in schizophrenia consistent with microstructural disorganization (reduced fractional anisotropy (FA)) and axonal dysfunction (reduced N-acetylaspartate NAAc). However, the clinical significance of these abnormalities is poorly understood. Diffusion tensor and proton spectroscopic imaging where used to assess FA, axial diffusivity and radial diffusivity (RD), and supra-ventricular white matter NAAc, respectively, in 64 schizophrenia and 64 healthy subjects. Schizophrenia patients had reduced FA across several regions, with additional regions where FA correlated positively with positive symptoms severity. These regions included genu, body and splenium of corpus callosum, anterior and superior corona radiata, superior longitudinal and inferior fronto-occipital fasciculi, and internal capsule. The FA/symptoms relationships corresponded with opposite correlations between RD and positive symptoms. The schizophrenia group (SP group) had progressively reduced NAAc with age, and NAAc correlated negatively with positive symptoms. Cognition correlated positively with both FA and NAAc in controls, whereas in the SP group it had a negative correlation with NAAc and no significant relationship with FA. Antipsychotic dose did not account for the results. Correlates of psychosis, cognitive and negative symptoms can be found in white matter. The significant correlations between positive symptoms in schizophrenia and diffusion and NAAc measures suggest decreased axonal density with increased glial cells and higher myelination in this subpopulation. A separate set of abnormal relationships between cognition and FA/RD, as well as with NAAc, converge to suggest that in schizophrenia, white matter microstructure supports the two core illness domains: psychosis and cognitive/negative symptoms.
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Trifiletti DM, Lee CC, Schlesinger D, Larner JM, Xu Z, Sheehan JP. Leukoencephalopathy After Stereotactic Radiosurgery for Brain Metastases. Int J Radiat Oncol Biol Phys 2015; 93:870-8. [PMID: 26530756 DOI: 10.1016/j.ijrobp.2015.07.2280] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2014] [Revised: 07/19/2015] [Accepted: 07/21/2015] [Indexed: 11/19/2022]
Abstract
PURPOSE Although the use of stereotactic radiosurgery (SRS) in the treatment of multiple brain metastases has increased dramatically during the past decade to avoid the neurocognitive dysfunction induced by whole brain radiation therapy (WBRT), the cumulative neurocognitive effect of numerous SRS sessions remains unknown. Because leukoencephalopathy is a sensitive marker for radiation-induced central nervous system damage, we studied the clinical and dosimetric predictors of SRS-induced leukoencephalopathy. METHODS AND MATERIALS Patients treated at our institution with at least 2 sessions of SRS for brain metastases from 2007 to 2013 were reviewed. The pre- and post-SRS magnetic resonance imaging sequences were reviewed and graded for white matter changes associated with radiation leukoencephalopathy using a previously validated scale. Patient characteristics and SRS dosimetric parameters were reviewed for factors that contributed to leukoencephalopathy using Cox proportional hazards modeling. RESULTS A total of 103 patients meeting the inclusion criteria were identified. The overall incidence of leukoencephalopathy was 29% at year 1, 38% at year 2, and 53% at year 3. Three factors were associated with radiation-induced leukoencephalopathy: (1) the use of WBRT (P=.019); (2) a higher SRS integral dose to the cranium (P=.036); and (3) the total number of intracranial metastases (P=.003). CONCLUSIONS Our results have established that WBRT plus SRS produces leukoencephalopathy at a much higher rate than SRS alone. In addition, for patients who did not undergo WBRT before SRS, the integral dose was associated with the development of leukoencephalopathy. As the survival of patients with central nervous system metastases increases and as the neurotoxicity of chemotherapeutic and targeted agents becomes established, these 3 potential risk factors will be important to consider.
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Affiliation(s)
- Daniel M Trifiletti
- Department of Radiation Oncology, University of Virginia Health System, Charlottesville, Virginia.
| | - Cheng-Chia Lee
- Department of Neurosurgery, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - David Schlesinger
- Department of Radiation Oncology, University of Virginia Health System, Charlottesville, Virginia; Department of Neurological Surgery, University of Virginia Health System, Charlottesville, Virginia
| | - James M Larner
- Department of Radiation Oncology, University of Virginia Health System, Charlottesville, Virginia
| | - Zhiyuan Xu
- Department of Neurological Surgery, University of Virginia Health System, Charlottesville, Virginia
| | - Jason P Sheehan
- Department of Radiation Oncology, University of Virginia Health System, Charlottesville, Virginia; Department of Neurological Surgery, University of Virginia Health System, Charlottesville, Virginia
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Brown LA, Brockmole JR, Gow AJ, Deary IJ. Processing speed and visuospatial executive function predict visual working memory ability in older adults. Exp Aging Res 2015; 38:1-19. [PMID: 22224947 DOI: 10.1080/0361073x.2012.636722] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
UNLABELLED BACKGROUND/STUDY CONTEXT: Visual working memory (VWM) has been shown to be particularly age sensitive. Determining which measures share variance with this cognitive ability in older adults may help to elucidate the key factors underlying the effects of aging. METHODS Predictors of VWM (measured by a modified Visual Patterns Test) were investigated in a subsample (N = 44, mean age = 73) of older adults from the Lothian Birth Cohort 1936 (LBC1936; Deary et al., 2007 , BMC Geriatrics, 7, 28). Childhood intelligence (Moray House Test) and contemporaneous measures of processing speed (four-choice reaction time), executive function (verbal fluency; block design), and spatial working memory (backward spatial span), were assessed as potential predictors. RESULTS All contemporaneous measures except verbal fluency were significantly associated with VWM, and processing speed had the largest effect size (r = -.53, p < .001). In linear regression analysis, even after adjusting for childhood intelligence, processing speed and the executive measure associated with visuospatial organization accounted for 35% of the variance in VWM. CONCLUSION Processing speed may affect VWM performance in older adults via speed of encoding and/or rate of rehearsal, while executive resources specifically associated with visuospatial material are also important.
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Affiliation(s)
- Louise A Brown
- Department of Psychology, The University of Edinburgh, Edinburgh, UK.
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Affiliation(s)
- Joanna M Wardlaw
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
| | - Maria C Valdés Hernández
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
| | - Susana Muñoz-Maniega
- Division of Neuroimaging Sciences and Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (J.M.W., M.C.V.H., S.M.M.)
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Graveson J, Bauermeister S, McKeown D, Bunce D. Intraindividual Reaction Time Variability, Falls, and Gait in Old Age: A Systematic Review. J Gerontol B Psychol Sci Soc Sci 2015; 71:857-64. [DOI: 10.1093/geronb/gbv027] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 03/23/2015] [Indexed: 12/14/2022] Open
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