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Murray-Smith H, Barker S, Barkhof F, Barnes J, Brown TM, Captur G, R E Cartlidge M, Cash DM, Coath W, Davis D, Dickson JC, Groves J, Hughes AD, James SN, Keshavan A, Keuss SE, King-Robson J, Lu K, Malone IB, Nicholas JM, Rapala A, Scott CJ, Street R, Sudre CH, Thomas DL, Wong A, Wray S, Zetterberg H, Chaturvedi N, Fox NC, Crutch SJ, Richards M, Schott JM. Updating the study protocol: Insight 46 - a longitudinal neuroscience sub-study of the MRC National Survey of Health and Development - phases 2 and 3. BMC Neurol 2024; 24:40. [PMID: 38263061 PMCID: PMC10804658 DOI: 10.1186/s12883-023-03465-3] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/13/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Although age is the biggest known risk factor for dementia, there remains uncertainty about other factors over the life course that contribute to a person's risk for cognitive decline later in life. Furthermore, the pathological processes leading to dementia are not fully understood. The main goals of Insight 46-a multi-phase longitudinal observational study-are to collect detailed cognitive, neurological, physical, cardiovascular, and sensory data; to combine those data with genetic and life-course information collected from the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort); and thereby contribute to a better understanding of healthy ageing and dementia. METHODS/DESIGN Phase 1 of Insight 46 (2015-2018) involved the recruitment of 502 members of the NSHD (median age = 70.7 years; 49% female) and has been described in detail by Lane and Parker et al. 2017. The present paper describes phase 2 (2018-2021) and phase 3 (2021-ongoing). Of the 502 phase 1 study members who were invited to a phase 2 research visit, 413 were willing to return for a clinic visit in London and 29 participated in a remote research assessment due to COVID-19 restrictions. Phase 3 aims to recruit 250 study members who previously participated in both phases 1 and 2 of Insight 46 (providing a third data time point) and 500 additional members of the NSHD who have not previously participated in Insight 46. DISCUSSION The NSHD is the oldest and longest continuously running British birth cohort. Members of the NSHD are now at a critical point in their lives for us to investigate successful ageing and key age-related brain morbidities. Data collected from Insight 46 have the potential to greatly contribute to and impact the field of healthy ageing and dementia by combining unique life course data with longitudinal multiparametric clinical, imaging, and biomarker measurements. Further protocol enhancements are planned, including in-home sleep measurements and the engagement of participants through remote online cognitive testing. Data collected are and will continue to be made available to the scientific community.
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Affiliation(s)
- Heidi Murray-Smith
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK.
| | - Suzie Barker
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Centre for Medical Image Computing, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Thomas M Brown
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Gabriella Captur
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Molly R E Cartlidge
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - David M Cash
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - William Coath
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Daniel Davis
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - James Groves
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Josh King-Robson
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Kirsty Lu
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Ian B Malone
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Catherine J Scott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Rebecca Street
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Carole H Sudre
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
- Centre for Medical Image Computing, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Selina Wray
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Hong, Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, 1St Floor, 8-11 Queen Square, London, UK
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Keuss SE, Coath W, Cash DM, Barnes J, Nicholas JM, Lane CA, Parker TD, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris M, Lu K, James SN, Street R, Malone IB, Sudre CH, Thomas DL, Dickson JC, Barkhof F, Murray-Smith H, Wong A, Richards M, Fox NC, Schott JM. Rates of cortical thinning in Alzheimer's disease signature regions associate with vascular burden but not with β-amyloid status in cognitively normal adults at age 70. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332067. [PMID: 38199813 DOI: 10.1136/jnnp-2023-332067] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024]
Abstract
BACKGROUND Consistent patterns of reduced cortical thickness have been identified in early Alzheimer's disease (AD). However, the pathological factors that influence rates of cortical thinning within these AD signature regions remain unclear. METHODS Participants were from the Insight 46 substudy of the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort), a prospective longitudinal cohort study. Linear regression was used to examine associations of baseline cerebral β-amyloid (Aβ) deposition, measured using florbetapir positron emission tomography, and baseline white matter hyperintensity volume (WMHV) on MRI, a marker of cerebral small vessel disease, with subsequent longitudinal changes in AD signature cortical thickness quantified from baseline and repeat MRI (mean [SD] interval 2.4 [0.2] years). RESULTS In a population-based sample of 337 cognitively normal older white adults (mean [SD] age at baseline 70.5 [0.6] years; 48.1% female), higher global WMHV at baseline related to faster subsequent rates of cortical thinning in both AD signature regions (~0.15%/year faster per 10 mL additional WMHV), whereas baseline Aβ status did not. Among Aβ positive participants (n=56), there was some evidence that greater global Aβ standardised uptake value ratio at baseline related to faster cortical thinning in the AD signature Mayo region, but this did not reach statistical significance (p=0.08). CONCLUSIONS Cortical thinning within AD signature regions may develop via cerebrovascular pathways. Perhaps reflecting the age of the cohort and relatively low prevalence of Aβ-positivity, robust Aβ-related differences were not detected. Longitudinal follow-up incorporating additional biomarkers will allow assessment of how these relationships evolve closer to expected dementia onset.
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Affiliation(s)
- Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - William Coath
- 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
- Dementia Research Institute, University College London, London, UK
| | - Josephine Barnes
- 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 & Tropical Medicine, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain Sciences, Imperial 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 Z Wagen
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Mathew Storey
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthew Harris
- 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
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Rebecca Street
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
- Centre for Medical Imaging Computing, University College London, London, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain Repair and Neurorehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Frederik Barkhof
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Centre for Medical Imaging Computing, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - 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, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- Dementia Research Institute, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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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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James SN, Nicholas JM, Lu K, Keshavan A, Lane CA, Parker T, Buchanan SM, Keuss SE, Murray-Smith H, Wong A, Cash DM, Malone IB, Barnes J, Sudre CH, Coath W, Modat M, Ourselin S, Crutch SJ, Kuh D, Fox NC, Schott JM, Richards M. Adulthood cognitive trajectories over 26 years and brain health at 70 years of age: findings from the 1946 British Birth Cohort. Neurobiol Aging 2023; 122:22-32. [PMID: 36470133 PMCID: PMC10564626 DOI: 10.1016/j.neurobiolaging.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/06/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022]
Abstract
Few studies can address how adulthood cognitive trajectories relate to brain health in 70-year-olds. Participants (n = 468, 49% female) from the 1946 British birth cohort underwent 18F-Florbetapir PET/MRI. Cognitive function was measured in childhood (age 8 years) and across adulthood (ages 43, 53, 60-64 and 69 years) and was examined in relation to brain health markers of β-amyloid (Aβ) status, whole brain and hippocampal volume, and white matter hyperintensity volume (WMHV). Taking into account key contributors of adult cognitive decline including childhood cognition, those with greater Aβ and WMHV at age 70 years had greater decline in word-list learning memory in the preceding 26 years, particularly after age 60. In contrast, those with smaller whole brain and hippocampal volume at age 70 years had greater decline in processing search speed, subtly manifest from age 50 years. Subtle changes in memory and processing speed spanning 26 years of adulthood were associated with markers of brain health at 70 years of age, consistent with detectable prodromal cognitive effects in early older age.
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, 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, University of London, London, UK
| | - Kirsty Lu
- 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
| | - 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; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, UK; Department of Medicine, Division of Brain Sciences, Imperial College London
| | - Sarah M Buchanan
- 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
| | - 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, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastien Ourselin
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
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Wagen AZ, Coath W, Keshavan A, James SN, Parker TD, Lane CA, Buchanan SM, Keuss SE, Storey M, Lu K, Macdougall A, Murray-Smith H, Freiberger T, Cash DM, Malone IB, Barnes J, Sudre CH, Wong A, Pavisic IM, Street R, Crutch SJ, Escott-Price V, Leonenko G, Zetterberg H, Wellington H, Heslegrave A, Barkhof F, Richards M, Fox NC, Cole JH, Schott JM. Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study. Lancet Healthy Longev 2022; 3:e607-e616. [PMID: 36102775 PMCID: PMC10499760 DOI: 10.1016/s2666-7568(22)00167-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/29/2022] [Accepted: 06/30/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND A neuroimaging-based biomarker termed the brain age is thought to reflect variability in the brain's ageing process and predict longevity. Using Insight 46, a unique narrow-age birth cohort, we aimed to examine potential drivers and correlates of brain age. METHODS Participants, born in a single week in 1946 in mainland Britain, have had 24 prospective waves of data collection to date, including MRI and amyloid PET imaging at approximately 70 years old. Using MRI data from a previously defined selection of this cohort, we derived brain-predicted age from an established machine-learning model (trained on 2001 healthy adults aged 18-90 years); subtracting this from chronological age (at time of assessment) gave the brain-predicted age difference (brain-PAD). We tested associations with data from early life, midlife, and late life, as well as rates of MRI-derived brain atrophy. FINDINGS Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. We included 456 participants (225 female), with a mean chronological age of 70·7 years (SD 0·7; range 69·2 to 71·9). The mean brain-predicted age was 67·9 years (8·2, 46·3 to 94·3). Female sex was associated with a 5·4-year (95% CI 4·1 to 6·8) younger brain-PAD than male sex. An increase in brain-PAD was associated with increased cardiovascular risk at age 36 years (β=2·3 [95% CI 1·5 to 3·0]) and 69 years (β=2·6 [1·9 to 3·3]); increased cerebrovascular disease burden (1·9 [1·3 to 2·6]); lower cognitive performance (-1·3 [-2·4 to -0·2]); and increased serum neurofilament light concentration (1·2 [0·6 to 1·9]). Higher brain-PAD was associated with future hippocampal atrophy over the subsequent 2 years (0·003 mL/year [0·000 to 0·006] per 5-year increment in brain-PAD). Early-life factors did not relate to brain-PAD. Combining 12 metrics in a hierarchical partitioning model explained 33% of the variance in brain-PAD. INTERPRETATION Brain-PAD was associated with cardiovascular risk, and imaging and biochemical markers of neurodegeneration. These findings support brain-PAD as an integrative summary metric of brain health, reflecting multiple contributions to pathological brain ageing, and which might have prognostic utility. FUNDING Alzheimer's Research UK, Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association.
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Affiliation(s)
- Aaron Z Wagen
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK; Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK
| | - William Coath
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Brain Sciences, Imperial College London, London, UK; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Mathew Storey
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Kirsty Lu
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Amy Macdougall
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Tamar Freiberger
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - David M Cash
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK
| | - Ian B Malone
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Carole H Sudre
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Ivanna M Pavisic
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Rebecca Street
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | | | - Ganna Leonenko
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Henrik Zetterberg
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrietta Wellington
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Amanda Heslegrave
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Frederik Barkhof
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Vrije Universiteit, Amsterdam, Netherlands
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK
| | - James H Cole
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK.
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Mason SA, Al Saikhan L, Jones S, James SN, Murray-Smith H, Rapala A, Williams S, Sudre C, Wong B, Richards M, Fox NC, Hardy R, Schott JM, Chaturvedi N, Hughes AD. Association between carotid atherosclerosis and brain activation patterns during the Stroop task in older adults: An fNIRS investigation. Neuroimage 2022; 257:119302. [PMID: 35595200 PMCID: PMC10466022 DOI: 10.1016/j.neuroimage.2022.119302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 11/17/2022] Open
Abstract
There is an increasing body of evidence suggesting that vascular disease could contribute to cognitive decline and overt dementia. Of particular interest is atherosclerosis, as it is not only associated with dementia, but could be a potential mechanism through which cardiovascular disease directly impacts brain health. In this work, we evaluated the differences in functional near infrared spectroscopy (fNIRS)-based measures of brain activation, task performance, and the change in central hemodynamics (mean arterial pressure (MAP) and heart rate (HR)) during a Stroop color-word task in individuals with atherosclerosis, defined as bilateral carotid plaques (n = 33) and healthy age-matched controls (n = 33). In the healthy control group, the left prefrontal cortex (LPFC) was the only region showing evidence of activation when comparing the incongruous with the nominal Stroop test. A smaller extent of brain activation was observed in the Plaque group compared with the healthy controls (1) globally, as measured by oxygenated hemoglobin (p = 0.036) and (2) in the LPFC (p = 0.02) and left sensorimotor cortices (LMC)(p = 0.008) as measured by deoxygenated hemoglobin. There were no significant differences in HR, MAP, or task performance (both in terms of the time required to complete the task and number of errors made) between Plaque and control groups. These results suggest that carotid atherosclerosis is associated with altered functional brain activation patterns despite no evidence of impaired performance of the Stroop task or central hemodynamic changes.
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Affiliation(s)
- Sarah A Mason
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom.
| | - Lamia Al Saikhan
- Department of Cardiac Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, 2835 King Faisal Street, Damman, Kingdom of Saudi Arabia
| | - Siana Jones
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Centre for Medical Image Computing, Department of Computer Science, University College London, London UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Suzanne Williams
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Carole Sudre
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Centre for Medical Image Computing, Department of Computer Science, University College London, London UK; School of Biomedical Engineering, King's College, London UK
| | - Brian Wong
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom; Centre for Medical Image Computing, Department of Computer Science, University College London, London UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at University College London, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom.
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7
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Keuss SE, Coath W, Nicholas JM, Poole T, Barnes J, Cash DM, Lane CA, Parker TD, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris M, Malone IB, Sudre CH, Lu K, James SN, Street R, Thomas DL, Dickson JC, Murray-Smith H, Wong A, Freiberger T, Crutch S, Richards M, Fox NC, Schott JM. Associations of β-Amyloid and Vascular Burden With Rates of Neurodegeneration in Cognitively Normal Members of the 1946 British Birth Cohort. Neurology 2022; 99:e129-e141. [PMID: 35410910 PMCID: PMC9280996 DOI: 10.1212/wnl.0000000000200524] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 03/01/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The goals of this work were to quantify the independent and interactive associations of β-amyloid (Aβ) and white matter hyperintensity volume (WMHV), a marker of presumed cerebrovascular disease (CVD), with rates of neurodegeneration and to examine the contributions of APOE ε4 and vascular risk measured at different stages of adulthood in cognitively normal members of the 1946 British Birth Cohort. METHODS Participants underwent brain MRI and florbetapir-Aβ PET as part of Insight 46, an observational population-based study. Changes in whole-brain, ventricular, and hippocampal volume were directly measured from baseline and repeat volumetric T1 MRI with the boundary shift integral. Linear regression was used to test associations with baseline Aβ deposition, baseline WMHV, APOE ε4, and office-based Framingham Heart Study Cardiovascular Risk Score (FHS-CVS) and systolic blood pressure (BP) at ages 36, 53, and 69 years. RESULTS Three hundred forty-six cognitively normal participants (mean [SD] age at baseline scan 70.5 [0.6] years; 48% female) had high-quality T1 MRI data from both time points (mean [SD] scan interval 2.4 [0.2] years). Being Aβ positive at baseline was associated with 0.87-mL/y faster whole-brain atrophy (95% CI 0.03, 1.72), 0.39-mL/y greater ventricular expansion (95% CI 0.16, 0.64), and 0.016-mL/y faster hippocampal atrophy (95% CI 0.004, 0.027), while each 10-mL additional WMHV at baseline was associated with 1.07-mL/y faster whole-brain atrophy (95% CI 0.47, 1.67), 0.31-mL/y greater ventricular expansion (95% CI 0.13, 0.60), and 0.014-mL/y faster hippocampal atrophy (95% CI 0.006, 0.022). These contributions were independent, and there was no evidence that Aβ and WMHV interacted in their effects. There were no independent associations of APOE ε4 with rates of neurodegeneration after adjustment for Aβ status and WMHV, no clear relationships between FHS-CVS or systolic BP and rates of neurodegeneration when assessed across the whole sample, and no evidence that FHS-CVS or systolic BP acted synergistically with Aβ. DISCUSSION Aβ and presumed CVD have distinct and additive effects on rates of neurodegeneration in cognitively normal elderly. These findings have implications for the use of MRI measures as biomarkers of neurodegeneration and emphasize the importance of risk management and early intervention targeting both pathways.
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Affiliation(s)
- Sarah E Keuss
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - William Coath
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jennifer M Nicholas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Teresa Poole
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Josephine Barnes
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David M Cash
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Christopher A Lane
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Thomas D Parker
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ashvini Keshavan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah M Buchanan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Aaron Z Wagen
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Mathew Storey
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Matthew Harris
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ian B Malone
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Carole H Sudre
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Kirsty Lu
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah-Naomi James
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Rebecca Street
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David L Thomas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - John C Dickson
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Heidi Murray-Smith
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Andrew Wong
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Tamar Freiberger
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sebastian Crutch
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Marcus Richards
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Nick C Fox
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jonathan M Schott
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK.
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Lu K, Nicholas JM, Pertzov Y, Grogan J, Husain M, Pavisic IM, James SN, Parker TD, Lane CA, Keshavan A, Keuss SE, Buchanan SM, Murray-Smith H, Cash DM, Malone IB, Sudre CH, Coath W, Wong A, Henley SM, Fox NC, Richards M, Schott JM, Crutch SJ. Dissociable effects of APOE-ε4 and β-amyloid pathology on visual working memory. Nat Aging 2021; 1:1002-1009. [PMID: 34806027 PMCID: PMC7612005 DOI: 10.1038/s43587-021-00117-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 08/17/2021] [Indexed: 01/21/2023]
Abstract
Although APOE-ε4 carriers are at significantly higher risk of developing Alzheimer's disease than non-carriers1, controversial evidence suggests that APOE-ε4 might confer some advantages, explaining the survival of this gene (antagonistic pleiotropy)2,3. In a population-based cohort born in one week in 1946 (assessed aged 69-71), we assessed differential effects of APOE-ε4 and β-amyloid pathology (quantified using 18F-Florbetapir-PET) on visual working memory (object-location binding). In 398 cognitively normal participants, APOE-ε4 and β-amyloid had opposing effects on object identification, predicting better and poorer recall respectively. ε4-carriers also recalled locations more precisely, with a greater advantage at higher β-amyloid burden. These results provide evidence of superior visual working memory in ε4-carriers, showing that some benefits of this genotype are demonstrable in older age, even in the preclinical stages of Alzheimer's disease.
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Affiliation(s)
- Kirsty Lu
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer M. Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Yoni Pertzov
- Department of Psychology, The Hebrew University of Jerusalem, Israel
| | - John Grogan
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK
- Department of Experimental Psychology, University of Oxford, UK
| | - Ivanna M. Pavisic
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Thomas D. Parker
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher A. Lane
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E. Keuss
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M. Buchanan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B. Malone
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Carole H. Sudre
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - William Coath
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Susie M.D. Henley
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nick C. Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Jonathan M. Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sebastian J. Crutch
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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Pavisic IM, Lu K, Keuss SE, James SN, Lane CA, Parker TD, Keshavan A, Buchanan SM, Murray-Smith H, Cash DM, Coath W, Wong A, Fox NC, Crutch SJ, Richards M, Schott JM. Subjective cognitive complaints at age 70: associations with amyloid and mental health. J Neurol Neurosurg Psychiatry 2021; 92:1215-1221. [PMID: 34035132 PMCID: PMC8522456 DOI: 10.1136/jnnp-2020-325620] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/08/2021] [Accepted: 04/28/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To investigate subjective cognitive decline (SCD) in relation to β-amyloid pathology and to test for associations with anxiety, depression, objective cognition and family history of dementia in the Insight 46 study. METHODS Cognitively unimpaired ~70-year-old participants, all born in the same week in 1946 (n=460, 49% female, 18% amyloid-positive), underwent assessments including the SCD-Questionnaire (MyCog). MyCog scores were evaluated with respect to 18F-Florbetapir-PET amyloid status (positive/negative). Associations with anxiety, depression, objective cognition (measured by the Preclinical Alzheimer Cognitive Composite, PACC) and family history of dementia were also investigated. The informant's perspective on SCD was evaluated in relation to MyCog score. RESULTS Anxiety (mean (SD) trait anxiety score: 4.4 (3.9)) was associated with higher MyCog scores, especially in women. MyCog scores were higher in amyloid-positive compared with amyloid-negative individuals (adjusted means (95% CIs): 5.3 (4.4 to 6.1) vs 4.3 (3.9 to 4.7), p=0.044), after accounting for differences in anxiety. PACC (mean (SD) -0.05 (0.68)) and family history of dementia (prevalence: 23.9%) were not independently associated with MyCog scores. The informant's perception of SCD was generally in accordance with that of the participant. CONCLUSIONS This cross-sectional study demonstrates that symptoms of SCD are associated with both β-amyloid pathology, and more consistently, trait anxiety in a population-based cohort of older adults, at an age when those who are destined to develop dementia are still likely to be some years away from symptoms. This highlights the necessity of considering anxiety symptoms when assessing Alzheimer's disease pathology and SCD.
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Affiliation(s)
- Ivanna M Pavisic
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - William Coath
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
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Lane CA, Barnes J, Nicholas JM, Baker JW, Sudre CH, Cash DM, Parker TD, Malone IB, Lu K, James SN, Keshavan A, Buchanan S, Keuss S, Murray-Smith H, Wong A, Gordon E, Coath W, Modat M, Thomas D, Hardy R, Richards M, Fox NC, Schott JM. Investigating the relationship between BMI across adulthood and late life brain pathologies. Alzheimers Res Ther 2021; 13:91. [PMID: 33941254 PMCID: PMC8091727 DOI: 10.1186/s13195-021-00830-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 04/12/2021] [Indexed: 01/01/2023]
Abstract
Background In view of reported associations between high adiposity, particularly in midlife and late-life dementia risk, we aimed to determine associations between body mass index (BMI), and BMI changes across adulthood and brain structure and pathology at age 69–71 years. Methods Four hundred sixty-five dementia-free participants from Insight 46, a sub-study of the British 1946 birth cohort, who had cross-sectional T1/FLAIR volumetric MRI, and florbetapir amyloid-PET imaging at age 69–71 years, were included in analyses. We quantified white matter hyperintensity volume (WMHV) using T1 and FLAIR 3D-MRI; β-amyloid (Aβ) positivity/negativity using a SUVR approach; and whole brain (WBV) and hippocampal volumes (HV) using 3D T1-MRI. We investigated the influence of BMI, and BMI changes at and between 36, 43, 53, 60–64, 69 and 71 years, on late-life WMHV, Aβ-status, WBV and mean HV. Analyses were repeated using overweight and obese status. Results At no time-point was BMI, change in BMI or overweight/obese status associated with WMHV or WBV at age 69–71 years. Decreasing BMI in the 1–2 years before imaging was associated with an increased odds of being β-amyloid positive (OR 1.45, 95% confidence interval 1.09, 1.92). There were associations between being overweight and larger mean HV at ages 60–64 (β = 0.073 ml, 95% CI 0.009, 0.137), 69 (β = 0.076 ml, 95% CI 0.012, 0.140) and 71 years (β = 0.101 ml, 95% CI 0.037, 0.165). A similar, albeit weaker, trend was seen with obese status. Conclusions Using WMHV, β-amyloid status and brain volumes as indicators of brain health, we do not find evidence to explain reported associations between midlife obesity and late-life dementia risk. Declining BMI in later life may reflect preclinical Alzheimer’s disease. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00830-7.
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Affiliation(s)
- Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,Hoffmann-La Roche UK Ltd, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - John W Baker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | | | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Sarah Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Elizabeth Gordon
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David Thomas
- Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | | | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at UCL, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, Box 16, Queen Square, London, WC1N 3BG, UK. .,UK Dementia Research Institute at UCL, University College London, London, UK.
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11
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James SN, Nicholas JM, Lane CA, Parker TD, Lu K, Keshavan A, Buchanan SM, Keuss SE, Murray-Smith H, Wong A, Cash DM, Malone IB, Barnes J, Sudre CH, Coath W, Prosser L, Ourselin S, Modat M, Thomas DL, Cardoso J, Heslegrave A, Zetterberg H, Crutch SJ, Schott JM, Richards M, Fox NC. A population-based study of head injury, cognitive function and pathological markers. Ann Clin Transl Neurol 2021; 8:842-856. [PMID: 33694298 PMCID: PMC8045921 DOI: 10.1002/acn3.51331] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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: 02/04/2021] [Accepted: 02/12/2021] [Indexed: 02/01/2023] Open
Abstract
Objective To assess associations between head injury (HI) with loss of consciousness (LOC), ageing and markers of later‐life cerebral pathology; and to explore whether those effects may help explain subtle cognitive deficits in dementia‐free individuals. Methods Participants (n = 502, age = 69–71) from the 1946 British Birth Cohort underwent cognitive testing (subtests of Preclinical Alzheimer Cognitive Composite), 18F‐florbetapir Aβ‐PET and MR imaging. Measures include Aβ‐PET status, brain, hippocampal and white matter hyperintensity (WMH) volumes, normal appearing white matter (NAWM) microstructure, Alzheimer’s disease (AD)‐related cortical thickness, and serum neurofilament light chain (NFL). LOC HI metrics include HI occurring: (i) >15 years prior to the scan (ii) anytime up to age 71. Results Compared to those with no evidence of an LOC HI, only those reporting an LOC HI>15 years prior (16%, n = 80) performed worse on cognitive tests at age 69–71, taking into account premorbid cognition, particularly on the digit‐symbol substitution test (DSST). Smaller brain volume (BV) and adverse NAWM microstructural integrity explained 30% and 16% of the relationship between HI and DSST, respectively. We found no evidence that LOC HI was associated with Aβ load, hippocampal volume, WMH volume, AD‐related cortical thickness or NFL (all p > 0.01). Interpretation Having a LOC HI aged 50’s and younger was linked with lower later‐life cognitive function at age ~70 than expected. This may reflect a damaging but small impact of HI; explained in part by smaller BV and different microstructure pathways but not via pathology related to AD (amyloid, hippocampal volume, AD cortical thickness) or ongoing neurodegeneration (serum NFL).
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom.,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom.,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom.,Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Lloyd Prosser
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, Institute of Nuclear Medicine, University College London Hospitals, London, United Kingdom
| | - Amanda Heslegrave
- UK Dementia Research Institute at UCL, University College London, London, United Kingdom.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, University College London, London, United Kingdom.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,UK Dementia Research Institute at UCL, University College London, London, United Kingdom
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12
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Keshavan A, Pannee J, Karikari TK, Rodriguez JL, Ashton NJ, Nicholas JM, Cash DM, Coath W, Lane CA, Parker TD, Lu K, Buchanan SM, Keuss SE, James SN, Murray-Smith H, Wong A, Barnes A, Dickson JC, Heslegrave A, Portelius E, Richards M, Fox NC, Zetterberg H, Blennow K, Schott JM. Population-based blood screening for preclinical Alzheimer's disease in a British birth cohort at age 70. Brain 2021; 144:434-449. [PMID: 33479777 PMCID: PMC7940173 DOI: 10.1093/brain/awaa403] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/10/2020] [Accepted: 09/17/2020] [Indexed: 11/14/2022] Open
Abstract
Alzheimer's disease has a preclinical stage when cerebral amyloid-β deposition occurs before symptoms emerge, and when amyloid-β-targeted therapies may have maximum benefits. Existing amyloid-β status measurement techniques, including amyloid PET and CSF testing, are difficult to deploy at scale, so blood biomarkers are increasingly considered for screening. We compared three different blood-based techniques-liquid chromatography-mass spectrometry measures of plasma amyloid-β, and single molecule array (Simoa) measures of plasma amyloid-β and phospho-tau181-to detect cortical 18F-florbetapir amyloid PET positivity (defined as a standardized uptake value ratio of >0.61 between a predefined cortical region of interest and eroded subcortical white matter) in dementia-free members of Insight 46, a substudy of the population-based British 1946 birth cohort. We used logistic regression models with blood biomarkers as predictors of amyloid PET status, with or without age, sex and APOE ε4 carrier status as covariates. We generated receiver operating characteristics curves and quantified areas under the curves to compare the concordance of the different blood tests with amyloid PET. We determined blood test cut-off points using Youden's index, then estimated numbers needed to screen to obtain 100 amyloid PET-positive individuals. Of the 502 individuals assessed, 441 dementia-free individuals with complete data were included; 82 (18.6%) were amyloid PET-positive. The area under the curve for amyloid PET status using a base model comprising age, sex and APOE ε4 carrier status was 0.695 (95% confidence interval: 0.628-0.762). The two best-performing Simoa plasma biomarkers were amyloid-β42/40 (0.620; 0.548-0.691) and phospho-tau181 (0.707; 0.646-0.768), but neither outperformed the base model. Mass spectrometry plasma measures performed significantly better than any other measure (amyloid-β1-42/1-40: 0.817; 0.770-0.864 and amyloid-β composite: 0.820; 0.775-0.866). At a cut-off point of 0.095, mass spectrometry measures of amyloid-β1-42/1-40 detected amyloid PET positivity with 86.6% sensitivity and 71.9% specificity. Without screening, to obtain 100 PET-positive individuals from a population with similar amyloid PET positivity prevalence to Insight 46, 543 PET scans would need to be performed. Screening using age, sex and APOE ε4 status would require 940 individuals, of whom 266 would proceed to scan. Using mass spectrometry amyloid-β1-42/1-40 alone would reduce these numbers to 623 individuals and 243 individuals, respectively. Across a theoretical range of amyloid PET positivity prevalence of 10-50%, mass spectrometry measures of amyloid-β1-42/1-40 would consistently reduce the numbers proceeding to scans, with greater cost savings demonstrated at lower prevalence.
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Affiliation(s)
- Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Josef Pannee
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K Karikari
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Juan Lantero Rodriguez
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Nicholas J Ashton
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- National Institute for Health Research Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation Trust, 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, University of London, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - William Coath
- 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 D Parker
- 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
| | - Sarah M Buchanan
- 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
| | | | - 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, London, UK
| | - Anna Barnes
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, University College London Hospitals NHS Foundation Trust, London, UK
| | - Amanda Heslegrave
- UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, UK
| | - Erik Portelius
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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13
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Lu K, Nicholas JM, Weston PSJ, Stout JC, O’Regan AM, James SN, Buchanan SM, Lane CA, Parker TD, Keuss SE, Keshavan A, Murray-Smith H, Cash DM, Sudre CH, Malone IB, Coath W, Wong A, Richards M, Henley SMD, Fox NC, Schott JM, Crutch SJ. Visuomotor integration deficits are common to familial and sporadic preclinical Alzheimer's disease. Brain Commun 2021; 3:fcab003. [PMID: 33615219 PMCID: PMC7882207 DOI: 10.1093/braincomms/fcab003] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 12/04/2020] [Accepted: 12/08/2020] [Indexed: 11/26/2022] Open
Abstract
We investigated whether subtle visuomotor deficits were detectable in familial and sporadic preclinical Alzheimer's disease. A circle-tracing task-with direct and indirect visual feedback, and dual-task subtraction-was completed by 31 individuals at 50% risk of familial Alzheimer's disease (19 presymptomatic mutation carriers; 12 non-carriers) and 390 cognitively normal older adults (members of the British 1946 Birth Cohort, all born during the same week; age range at assessment = 69-71 years), who also underwent β-amyloid-PET/MRI to derive amyloid status (positive/negative), whole-brain volume and white matter hyperintensity volume. We compared preclinical Alzheimer's groups against controls cross-sectionally (mutation carriers versus non-carriers; amyloid-positive versus amyloid-negative) on speed and accuracy of circle-tracing and subtraction. Mutation carriers (mean 7 years before expected onset) and amyloid-positive older adults traced disproportionately less accurately than controls when visual feedback was indirect, and were slower at dual-task subtraction. In the older adults, the same pattern of associations was found when considering amyloid burden as a continuous variable (Standardized Uptake Value Ratio). The effect of amyloid was independent of white matter hyperintensity and brain volumes, which themselves were associated with different aspects of performance: greater white matter hyperintensity volume was also associated with disproportionately poorer tracing accuracy when visual feedback was indirect, whereas larger brain volume was associated with faster tracing and faster subtraction. Mutation carriers also showed evidence of poorer tracing accuracy when visual feedback was direct. This study provides the first evidence of visuomotor integration deficits common to familial and sporadic preclinical Alzheimer's disease, which may precede the onset of clinical symptoms by several years.
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Affiliation(s)
- Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK
| | - Philip S J Weston
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Julie C Stout
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Alison M O’Regan
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, London, WC1E 7HB, UK
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, London, WC1E 7HB, UK
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, SE1 7EU, UK
- Department of Medical Physics, University College London, London, WC1E 7JE, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, WC1E 7HB, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, London, WC1E 7HB, UK
| | - Susie M D Henley
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
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14
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Lane CA, Barnes J, Nicholas JM, Sudre CH, Cash DM, Malone IB, Parker TD, Keshavan A, Buchanan SM, Keuss SE, James SN, Lu K, Murray-Smith H, Wong A, Gordon E, Coath W, Modat M, Thomas D, Richards M, Fox NC, Schott JM. Associations Between Vascular Risk Across Adulthood and Brain Pathology in Late Life: Evidence From a British Birth Cohort. JAMA Neurol 2020; 77:175-183. [PMID: 31682678 PMCID: PMC6830432 DOI: 10.1001/jamaneurol.2019.3774] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Question When is vascular risk during adulthood (early adulthood, midlife, or late life) most strongly associated with late-life brain structure and pathology? Findings In a propective cohort of 463 participants free of dementia from the population-based Insight 46 study, higher vascular risk in early adulthood was most strongly associated with smaller whole-brain volumes and greater white matter–hyperintensity volumes at age 69 to 71 years. There were no associations at any age with amyloid status. Meaning These findings are consistent with vascular risk influencing late-life brain health via cerebral small-vessel disease and lower brain volumes but not amyloidosis; vascular risk screening and modification may need to be considered from early adulthood. Importance Midlife vascular risk burden is associated with late-life dementia. Less is known about if and how risk exposure in early adulthood influences late-life brain health. Objective To determine the associations between vascular risk in early adulthood, midlife, and late life with late-life brain structure and pathology using measures of white matter–hyperintensity volume, β-amyloid load, and whole-brain and hippocampal volumes. Design, Setting, and Participants This prospective longitudinal cohort study, Insight 46, is part of the Medical Research Council National Survey of Health and Development, which commenced in 1946. Participants had vascular risk factors evaluated at ages 36 years (early adulthood), 53 years (midlife), and 69 years (early late life). Participants were assessed with multimodal magnetic resonance imaging and florbetapir-amyloid positron emission tomography scans between May 2015 and January 2018 at University College London. Participants with at least 1 available imaging measure, vascular risk measurements at 1 or more points, and no dementia were included in analyses. Exposures Office-based Framingham Heart study–cardiovascular risk scores (FHS-CVS) were derived at ages 36, 53, and 69 years using systolic blood pressure, antihypertensive medication usage, smoking, diabetic status, and body mass index. Analysis models adjusted for age at imaging, sex, APOE genotype, socioeconomic position, and, where appropriate, total intracranial volume. Main Outcomes and Measures White matter–hyperintensity volume was generated from T1/fluid-attenuated inversion recovery scans using an automated technique and whole-brain volume and hippocampal volume were generated from automated in-house pipelines; β-amyloid status was determined using a gray matter/eroded subcortical white matter standardized uptake value ratio threshold of 0.61. Results A total of 502 participants were assessed as part of Insight 46, and 463 participants (236 male [51.0%]) with at least 1 available imaging measure (mean [SD] age at imaging, 70.7 [0.7] years; 83 β-amyloid positive [18.2%]) who fulfilled eligibility criteria were included. Among them, FHS-CVS increased with age (36 years: median [interquartile range], 2.7% [1.5%-3.6%]; 53 years: 10.9% [6.7%-15.6%]; 69 years: 24.3% [14.9%-34.9%]). At all points, these scores were associated with smaller whole-brain volumes (36 years: β coefficient per 1% increase, −3.6 [95% CI, −7.0 to −0.3]; 53 years: −0.8 [95% CI, −1.5 to −0.08]; 69 years: −0.6 [95% CI, −1.1 to −0.2]) and higher white matter–hyperintensity volume (exponentiated coefficient: 36 years, 1.09 [95% CI, 1.01-1.18]; 53 years, 1.02 [95% CI, 1.00-1.04]; 69 years, 1.01 [95% CI, 1.00-1.02]), with largest effect sizes at age 36 years. At no point were FHS-CVS results associated with β-amyloid status. Conclusions and Relevance Higher vascular risk is associated with smaller whole-brain volume and greater white matter–hyperintensity volume at age 69 to 71 years, with the strongest association seen with early adulthood vascular risk. There was no evidence that higher vascular risk influences amyloid deposition, at least up to age 71 years. Reducing vascular risk with appropriate interventions should be considered from early adulthood to maximize late-life brain health.
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Affiliation(s)
- Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,London School of Hygiene and Tropical Medicine, Department of Medical Statistics, University of London, London, United Kingdom
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Elizabeth Gordon
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marc Modat
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - David Thomas
- Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,UK Dementia Research Institute at UCL, University College London, London, United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,UK Dementia Research Institute at UCL, University College London, London, United Kingdom
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15
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Mason SA, Al Saikhan L, Jones S, Bale G, James SN, Murray-Smith H, Rapala A, Williams S, Wong B, Richards M, Fox NC, Hardy R, Schott JM, Chaturvedi N, Hughes AD. Study Protocol - Insight 46 Cardiovascular: A Sub-study of the MRC National Survey of Health and Development. Artery Res 2020; 26:170-179. [PMID: 32879639 DOI: 10.2991/artres.k.200417.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The commonest causes of dementia are Alzheimer's disease and vascular cognitive impairment. Although these conditions have been viewed as distinct entities, there is increasing evidence that neurodegenerative and vascular pathologies interact or overlap to cause cognitive decline, and that at least in some cases individuals at risk of cognitive decline exhibit abnormal cardiovascular physiology long before emergence of disease. However, the mechanisms linking haemodynamic disturbances with cognitive impairment and the various pathologies that cause dementia are poorly understood. A sub-sample of 502 participants from the Medical Research Council National Survey of Health and Development (NSHD) have participated in the first visit of a neuroscience sub-study referred to as Insight 46, where clinical, cognitive, imaging, and lifestyle data have been collected for the purpose of elucidating the pathological changes preceding dementia. This paper outlines the cardiovascular phenotyping performed in the follow-up visit of Insight 46, with the study participants now aged 74. In addition to standard cardiovascular assessments such as blood pressure measurements, echocardiography, and electrocardiography (ECG), functional Near Infrared Spectroscopy (fNIRS) has been included to provide an assessment of cerebrovascular function. A detailed description of the fNIRS protocol along with preliminary results from pilot data is presented. The combination of lifestyle data, brain structure/function, cognitive performance, and cardiovascular health obtained not only from Insight 46, but also from the whole NSHD provides an exciting opportunity to advance our understanding of the cardiovascular mechanisms underlying dementia and cognitive decline, and identify novel targets for intervention.
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Affiliation(s)
- Sarah Ann Mason
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Lamia Al Saikhan
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiac Technology, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, 2835 King Faisal Street, Dammam, Kingdom of Saudi Arabia
| | - Siana Jones
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Gemma Bale
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Alicja Rapala
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Suzanne Williams
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Brian Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing at UCL, Department of Population Science & Experimental Medicine, UCL Institute of Cardiovascular Science, University College London, London, UK
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16
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Parker T, Cash DM, Lane C, Lu K, Malone IB, Nicholas JM, James S, Keshavan A, Murray-Smith H, Wong A, Buchannan S, Keuss S, Sudre CH, Thomas D, Crutch S, Bamiou DE, Warren JD, Fox NC, Richards M, Schott JM. Pure tone audiometry and cerebral pathology in healthy older adults. J Neurol Neurosurg Psychiatry 2020; 91:172-176. [PMID: 31699832 PMCID: PMC6996095 DOI: 10.1136/jnnp-2019-321897] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/14/2019] [Accepted: 10/23/2019] [Indexed: 11/03/2022]
Abstract
BACKGROUND Hearing impairment may be a modifiable risk factor for dementia. However, it is unclear how hearing associates with pathologies relevant to dementia in preclinical populations. METHODS Data from 368 cognitively healthy individuals born during 1 week in 1946 (age range 69.2-71.9 years), who underwent structural MRI, 18F-florbetapir positron emission tomography, pure tone audiometry and cognitive testing as part of a neuroscience substudy the MRC National Survey of Health and Development were analysed. The aim of the analysis was to investigate whether pure tone audiometry performance predicted a range of cognitive and imaging outcomes relevant to dementia in older adults. RESULTS There was some evidence that poorer pure tone audiometry performance was associated with lower primary auditory cortex thickness, but no evidence that it predicted in vivo β-amyloid deposition, white matter hyperintensity volume, hippocampal volume or Alzheimer's disease-pattern cortical thickness. A negative association between pure tone audiometry and mini-mental state examination score was observed, but this was no longer evident after excluding a test item assessing repetition of a single phrase. CONCLUSION Pure tone audiometry performance did not predict concurrent β-amyloid deposition, small vessel disease or Alzheimer's disease-pattern neurodegeneration, and had limited impact on cognitive function, in healthy adults aged approximately 70 years.
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Affiliation(s)
- Thomas Parker
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - David M Cash
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Chris Lane
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Kirsty Lu
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Ian B Malone
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Jennifer M Nicholas
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Sarah James
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,MRC Unit for Lifelong Health and Ageing at UCL, UCL, London, UK
| | - Ashvini Keshavan
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Heidi Murray-Smith
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, UCL, London, UK
| | - Sarah Buchannan
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Sarah Keuss
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Carole H Sudre
- KCL School of Biomedical Engineering and Imaging Sciences, London, UK
| | - David Thomas
- Neuradiological Academic Unit, UCL, London, Greater London, UK
| | - Sebastian Crutch
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Doris-Eva Bamiou
- UCL Ear Institute and UCLH Biomedical Research Centre, National Institute for Health Research, UCL, London, UK
| | - Jason D Warren
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Nick C Fox
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, UCL, London, UK
| | - Jonathan M Schott
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
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17
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Lu K, Nicholas JM, Collins JD, James SN, Parker TD, Lane CA, Keshavan A, Keuss SE, Buchanan SM, Murray-Smith H, Cash DM, Sudre CH, Malone IB, Coath W, Wong A, Henley SMD, Crutch SJ, Fox NC, Richards M, Schott JM. Cognition at age 70: Life course predictors and associations with brain pathologies. Neurology 2019; 93:e2144-e2156. [PMID: 31666352 PMCID: PMC6937487 DOI: 10.1212/wnl.0000000000008534] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 06/12/2019] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE To investigate predictors of performance on a range of cognitive measures including the Preclinical Alzheimer Cognitive Composite (PACC) and test for associations between cognition and dementia biomarkers in Insight 46, a substudy of the Medical Research Council National Survey of Health and Development. METHODS A total of 502 individuals born in the same week in 1946 underwent cognitive assessment at age 69-71 years, including an adapted version of the PACC and a test of nonverbal reasoning. Performance was characterized with respect to sex, childhood cognitive ability, education, and socioeconomic position (SEP). In a subsample of 406 cognitively normal participants, associations were investigated between cognition and β-amyloid (Aβ) positivity (determined from Aβ-PET imaging), whole brain volumes, white matter hyperintensity volumes (WMHV), and APOE ε4. RESULTS Childhood cognitive ability was strongly associated with cognitive scores including the PACC more than 60 years later, and there were independent effects of education and SEP. Sex differences were observed on every PACC subtest. In cognitively normal participants, Aβ positivity and WMHV were independently associated with lower PACC scores, and Aβ positivity was associated with poorer nonverbal reasoning. Aβ positivity and WMHV were not associated with sex, childhood cognitive ability, education, or SEP. Normative data for 339 cognitively normal Aβ-negative participants are provided. CONCLUSIONS This study adds to emerging evidence that subtle cognitive differences associated with Aβ deposition are detectable in older adults, at an age when dementia prevalence is very low. The independent associations of childhood cognitive ability, education, and SEP with cognitive performance at age 70 have implications for interpretation of cognitive data in later life.
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Affiliation(s)
- Kirsty Lu
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK.
| | - Jennifer M Nicholas
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Jessica D Collins
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Sarah-Naomi James
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Thomas D Parker
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Christopher A Lane
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Ashvini Keshavan
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Sarah E Keuss
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Sarah M Buchanan
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Heidi Murray-Smith
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - David M Cash
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Carole H Sudre
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Ian B Malone
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - William Coath
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Andrew Wong
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Susie M D Henley
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Sebastian J Crutch
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Nick C Fox
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Marcus Richards
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK
| | - Jonathan M Schott
- From the Dementia Research Centre (K.L., J.D.C., T.D.P., C.A.L., A.K., S.E.K., S.M.B., H.M.-S., D.M.C., C.H.S., I.B.M., W.C., S.M.D.H., S.J.C., N.C.F., J.M.S.), UCL Queen Square Institute of Neurology, University College London; Department of Medical Statistics (J.M.N.), London School of Hygiene and Tropical Medicine; MRC Unit for Lifelong Health and Ageing at UCL (S.-N.J., A.W., M.R.); and School of Biomedical Engineering and Imaging Sciences (D.M.C., C.H.S.), King's College London, UK.
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18
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Parker TD, Cash DM, Lane CAS, Lu K, Malone IB, Nicholas JM, James SN, Keshavan A, Murray-Smith H, Wong A, Buchanan SM, Keuss SE, Sudre CH, Modat M, Thomas DL, Crutch SJ, Richards M, Fox NC, Schott JM. Hippocampal subfield volumes and pre-clinical Alzheimer's disease in 408 cognitively normal adults born in 1946. PLoS One 2019; 14:e0224030. [PMID: 31622410 PMCID: PMC6797197 DOI: 10.1371/journal.pone.0224030] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/03/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The human hippocampus comprises a number of interconnected histologically and functionally distinct subfields, which may be differentially influenced by cerebral pathology. Automated techniques are now available that estimate hippocampal subfield volumes using in vivo structural MRI data. To date, research investigating the influence of cerebral β-amyloid deposition-one of the earliest hypothesised changes in the pathophysiological continuum of Alzheimer's disease-on hippocampal subfield volumes in cognitively normal older individuals, has been limited. METHODS Using cross-sectional data from 408 cognitively normal individuals born in mainland Britain (age range at time of assessment = 69.2-71.9 years) who underwent cognitive assessment, 18F-Florbetapir PET and structural MRI on the same 3 Tesla PET/MR unit (spatial resolution 1.1 x 1.1 x 1.1. mm), we investigated the influences of β-amyloid status, age at scan, and global white matter hyperintensity volume on: CA1, CA2/3, CA4, dentate gyrus, presubiculum and subiculum volumes, adjusting for sex and total intracranial volume. RESULTS Compared to β-amyloid negative participants (n = 334), β-amyloid positive participants (n = 74) had lower volume of the presubiculum (3.4% smaller, p = 0.012). Despite an age range at scanning of just 2.7 years, older age at time of scanning was associated with lower CA1 (p = 0.007), CA4 (p = 0.004), dentate gyrus (p = 0.002), and subiculum (p = 0.035) volumes. There was no evidence that white matter hyperintensity volume was associated with any subfield volumes. CONCLUSION These data provide evidence of differential associations in cognitively normal older adults between hippocampal subfield volumes and β-amyloid deposition and, increasing age at time of scan. The relatively selective effect of lower presubiculum volume in the β-amyloid positive group potentially suggest that the presubiculum may be an area of early and relatively specific volume loss in the pathophysiological continuum of Alzheimer's disease. Future work using higher resolution imaging will be key to exploring these findings further.
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Affiliation(s)
- Thomas D. Parker
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - David M. Cash
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Christopher A. S. Lane
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Kirsty Lu
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ian B. Malone
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jennifer M. Nicholas
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Ashvini Keshavan
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Heidi Murray-Smith
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Sarah M. Buchanan
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah E. Keuss
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Carole H. Sudre
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Marc Modat
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sebastian J. Crutch
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Nick C. Fox
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jonathan M. Schott
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- * E-mail:
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19
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Lane CA, Barnes J, Nicholas JM, Sudre CH, Cash DM, Parker TD, Malone IB, Lu K, James SN, Keshavan A, Murray-Smith H, Wong A, Buchanan SM, Keuss SE, Gordon E, Coath W, Barnes A, Dickson J, Modat M, Thomas D, Crutch SJ, Hardy R, Richards M, Fox NC, Schott JM. Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): an epidemiological study. Lancet Neurol 2019; 18:942-952. [PMID: 31444142 PMCID: PMC6744368 DOI: 10.1016/s1474-4422(19)30228-5] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 05/08/2019] [Accepted: 05/09/2019] [Indexed: 01/06/2023]
Abstract
BACKGROUND Midlife hypertension confers increased risk for cognitive impairment in late life. The sensitive period for risk exposure and extent that risk is mediated through amyloid or vascular-related mechanisms are poorly understood. We aimed to identify if, and when, blood pressure or change in blood pressure during adulthood were associated with late-life brain structure, pathology, and cognition. METHODS Participants were from Insight 46, a neuroscience substudy of the ongoing longitudinal Medical Research Council National Survey of Health and Development, a birth cohort that initially comprised 5362 individuals born throughout mainland Britain in one week in 1946. Participants aged 69-71 years received T1 and FLAIR volumetric MRI, florbetapir amyloid-PET imaging, and cognitive assessment at University College London (London, UK); all participants were dementia-free. Blood pressure measurements had been collected at ages 36, 43, 53, 60-64, and 69 years. We also calculated blood pressure change variables between ages. Primary outcome measures were white matter hyperintensity volume (WMHV) quantified from multimodal MRI using an automated method, amyloid-β positivity or negativity using a standardised uptake value ratio approach, whole-brain and hippocampal volumes quantified from 3D-T1 MRI, and a composite cognitive score-the Preclinical Alzheimer Cognitive Composite (PACC). We investigated associations between blood pressure and blood pressure changes at and between 36, 43, 53, 60-64, and 69 years of age with WMHV using generalised linear models with a gamma distribution and log link function, amyloid-β status using logistic regression, whole-brain volume and hippocampal volumes using linear regression, and PACC score using linear regression, with adjustment for potential confounders. FINDINGS Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. 465 participants (238 [51%] men; mean age 70·7 years [SD 0·7]; 83 [18%] amyloid-β-positive) were included in imaging analyses. Higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) at age 53 years and greater increases in SBP and DBP between 43 and 53 years were positively associated with WMHV at 69-71 years of age (increase in mean WMHV per 10 mm Hg greater SBP 7%, 95% CI 1-14, p=0·024; increase in mean WMHV per 10 mm Hg greater DBP 15%, 4-27, p=0·0057; increase in mean WMHV per one SD change in SBP 15%, 3-29, p=0·012; increase in mean WMHV per 1 SD change in DBP 15%, 3-30, p=0·017). Higher DBP at 43 years of age was associated with smaller whole-brain volume at 69-71 years of age (-6·9 mL per 10 mm Hg greater DBP, -11·9 to -1·9, p=0·0068), as were greater increases in DBP between 36 and 43 years of age (-6·5 mL per 1 SD change, -11·1 to -1·9, p=0·0054). Greater increases in SBP between 36 and 43 years of age were associated with smaller hippocampal volumes at 69-71 years of age (-0·03 mL per 1 SD change, -0·06 to -0·001, p=0·043). Neither absolute blood pressure nor change in blood pressure predicted amyloid-β status or PACC score at 69-71 years of age. INTERPRETATION High and increasing blood pressure from early adulthood into midlife seems to be associated with increased WMHV and smaller brain volumes at 69-71 years of age. We found no evidence that blood pressure affected cognition or cerebral amyloid-β load at this age. Blood pressure monitoring and interventions might need to start around 40 years of age to maximise late-life brain health. FUNDING Alzheimer's Research UK, Medical Research Council, Dementias Platform UK, Wellcome Trust, Brain Research UK, Wolfson Foundation, Weston Brain Institute, Avid Radiopharmaceuticals.
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Affiliation(s)
- Christopher A Lane
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer M Nicholas
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK,Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, London, UK
| | - Carole H Sudre
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David M Cash
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Elizabeth Gordon
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - William Coath
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Anna Barnes
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Marc Modat
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - David Thomas
- Leonard Wolfson Experimental Neurology Centre and Academic Neuroradiological Unit, Department of Brain Repair and Rehabilitation, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca Hardy
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK,UK Dementia Research Institute at University College London, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK,UK Dementia Research Institute at University College London, University College London, London, UK,Correspondence to: Prof Jonathan M Schott, Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
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20
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Keuss SE, Parker TD, Lane CA, Hoskote C, Shah S, Cash DM, Keshavan A, Buchanan SM, Murray-Smith H, Wong A, James SN, Lu K, Collins J, Beasley DG, Malone IB, Thomas DL, Barnes A, Richards M, Fox N, Schott JM. Incidental findings on brain imaging and blood tests: results from the first phase of Insight 46, a prospective observational substudy of the 1946 British birth cohort. BMJ Open 2019; 9:e029502. [PMID: 31371298 PMCID: PMC6678011 DOI: 10.1136/bmjopen-2019-029502] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [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] [Indexed: 02/02/2023] Open
Abstract
OBJECTIVE To summarise the incidental findings detected on brain imaging and blood tests during the first wave of data collection for the Insight 46 study. DESIGN Prospective observational sub-study of a birth cohort. SETTING Single-day assessment at a research centre in London, UK. PARTICIPANTS 502 individuals were recruited from the MRC National Survey of Health and Development (NSHD), the 1946 British birth cohort, based on pre-specified eligibility criteria; mean age was 70.7 (SD: 0.7) and 49% were female. OUTCOME MEASURES Data regarding the number and types of incidental findings were summarised as counts and percentages, and 95% confidence intervals were calculated. RESULTS 93.8% of participants completed a brain scan (n=471); 4.5% of scanned participants had a pre-defined reportable abnormality on brain MRI (n=21); suspected vascular malformations and suspected intracranial mass lesions were present in 1.9% (n=9) and 1.5% (n=7) respectively; suspected cerebral aneurysms were the single most common vascular abnormality, affecting 1.1% of participants (n=5), and suspected meningiomas were the most common intracranial lesion, affecting 0.6% of participants (n=3); 34.6% of participants had at least one abnormality on clinical blood tests (n=169), but few reached the prespecified threshold for urgent action (n=11). CONCLUSIONS In older adults, aged 69-71 years, potentially serious brain MRI findings were detected in around 5% of participants, and clinical blood test abnormalities were present in around one third of participants. Knowledge of the expected prevalence of incidental findings in the general population at this age is useful in both research and clinical settings.
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Affiliation(s)
- Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Chandrashekar Hoskote
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Sachit Shah
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Jessica Collins
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Daniel G Beasley
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - David L Thomas
- Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Repair and Neurorehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Anna Barnes
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nick Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
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21
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Keshavan A, Lane CA, Parker TD, Lu K, Cash DM, Sudre CH, Nicholas JM, Heslegrave AJ, James SN, Murray-Smith H, Buchanan SM, Keuss SE, Thomas DL, Malone IB, Wong A, Richards M, Zetterberg H, Fox NC, Schott JM. P3-234: PLASMA AMYLOID, TAU AND SERUM NEUROFILAMENT LIGHT CHAIN IN INSIGHT 46: ASSOCIATIONS WITH COGNITION AND BRAIN IMAGING. Alzheimers Dement 2019. [DOI: 10.1016/j.jalz.2019.06.3264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Ashvini Keshavan
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Christopher A. Lane
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Thomas D. Parker
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Kirsty Lu
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - David M. Cash
- UCL Queen Square Institute of Neurology; London United Kingdom
| | - Carole H. Sudre
- Department of Medical Physics and Biomedical Engineering; UCL; London United Kingdom
- School of Biomedical Engineering and Imaging Sciences; King's College London; London United Kingdom
| | - Jennifer M. Nicholas
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
- Department of Medical Statistics; London School of Hygiene and Tropical Medicine; London United Kingdom
| | | | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
| | - Heidi Murray-Smith
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Sarah M. Buchanan
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Sarah E. Keuss
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - David L. Thomas
- UCL Queen Square Institute of Neurology; London United Kingdom
| | - Ian B. Malone
- UCL Queen Square Institute of Neurology; London United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
| | - Henrik Zetterberg
- U.K. Dementia Research Institute at UCL; London United Kingdom
- Clinical Neurochemistry Laboratory; Sahlgrenska University Hospital; Mölndal Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry; The Sahlgrenska Academy at University of Gothenburg; Mölndal Sweden
| | - Nick C. Fox
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
- U.K. Dementia Research Institute at UCL; London United Kingdom
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22
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James SN, Lane CA, Parker TD, Lu K, Keshavan A, Buchanan SM, Keuss SE, Cash DM, Malone IB, Nicholas JM, Murray-Smith H, Wong A, Fox NC, Schott JM, Richards M. O3-03-04: DIVERGENT ASSOCIATIONS BETWEEN LIFE COURSE COGNITIVE TRAJECTORIES AND BRAIN PATHOLOGIES: FINDINGS FROM THE 1946 BRITISH BIRTH COHORT. Alzheimers Dement 2019. [DOI: 10.1016/j.jalz.2019.06.4639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
| | - Christopher A. Lane
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Thomas D. Parker
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Kirsty Lu
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Ashvini Keshavan
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Sarah M. Buchanan
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Sarah E. Keuss
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - David M. Cash
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
- UCL Centre for Medical Image Computing; London United Kingdom
- Dementia Research Centre; UCL Institute of Neurology; London United Kingdom
| | - Ian B. Malone
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Jennifer M. Nicholas
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
- Department of Medical Statistics; London School of Hygiene and Tropical Medicine; London United Kingdom
| | - Heidi Murray-Smith
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
| | - Nick C. Fox
- UK Dementia Research Institute at UCL; London United Kingdom
- Dementia Research Centre, Department of Neurodegenerative Disease; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Jonathan M. Schott
- Dementia Research Centre; UCL Queen Square Institute of Neurology; London United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL; London United Kingdom
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23
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James SN, Lane CA, Parker TD, Lu K, Collins JD, Murray-Smith H, Byford M, Wong A, Keshavan A, Buchanan S, Keuss SE, Kuh D, Fox NC, Schott JM, Richards M. Using a birth cohort to study brain health and preclinical dementia: recruitment and participation rates in Insight 46. BMC Res Notes 2018; 11:885. [PMID: 30545411 PMCID: PMC6293512 DOI: 10.1186/s13104-018-3995-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [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: 10/17/2018] [Accepted: 12/06/2018] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE Identifying and recruiting people with early pre-symptomatic Alzheimer's disease to neuroimaging research studies is increasingly important. The extent to which results of these studies can be generalised depends on the recruitment and representativeness of the participants involved. We now report the recruitment and participation patterns from a neuroscience sub-study of the MRC National Survey of Health and Development, "Insight 46". This study aimed to recruit 500 participants for extensive clinical and neuropsychological testing, and neuroimaging. We investigate how sociodemographic factors, health conditions and health-related behaviours predict participation at different levels of recruitment. RESULTS We met our target recruitment (n = 502). Higher educational attainment and non-manual socio-economic position (SEP) were consistent predictors of recruitment. Health-related variables were also predictive at every level of recruitment; in particular higher cognition, not smoking and better self-rating health. Sex and APOE-e4 status were not predictors of participation at any level. Whilst recruitment targets were met, individuals with lower SEP, lower cognition, and more health problems are under-represented in Insight 46. Understanding the factors that influence recruitment are important when interpreting results; for Insight 46 it is likely that health-related outcomes and life course risks will under-estimate those seen in the general population.
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Christopher A. Lane
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Thomas D. Parker
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Kirsty Lu
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Jessica D. Collins
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | | | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah Buchanan
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah E. Keuss
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Nick C. Fox
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Institute of Neurology, University College London, London, UK
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Lane CA, Sudre CH, Barnes J, Nicholas JM, Hardy R, Parker TD, Murray-Smith H, Keshavan A, Cash DM, Malone IB, Wong A, Kuh D, Ourselin S, Cardoso MJ, Fox NC, Richards M, Schott JM. O2‐05‐01: INFLUENCES OF BLOOD PRESSURE AND BLOOD PRESSURE TRAJECTORIES ON CEREBRAL PATHOLOGY AT AGE 70: RESULTS FROM A BRITISH BIRTH COHORT. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.2663] [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: 11/25/2022]
Affiliation(s)
- Christopher A. Lane
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Carole H. Sudre
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUnited Kingdom
- Dementia Research Centre and Department of Neurodegenerative Disease, Institute of NeurologyUniversity College LondonLondonUnited Kingdom
| | - Jo Barnes
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Jennifer M. Nicholas
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
- Department of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Rebecca Hardy
- Medical Research Council Unit for Lifelong Health and AgeingUniversity College LondonLondonUnited Kingdom
| | - Thomas D. Parker
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Heidi Murray-Smith
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Ashvini Keshavan
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - David M. Cash
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Ian B. Malone
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and AgeingUniversity College LondonLondonUnited Kingdom
| | - Diana Kuh
- Medical Research Council Unit for Lifelong Health and AgeingUniversity College LondonLondonUnited Kingdom
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUnited Kingdom
| | - M. Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUnited Kingdom
| | - Nick C. Fox
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and AgeingUniversity College LondonLondonUnited Kingdom
| | - Jonathan M. Schott
- Dementia Research CentreUniversity College London Institute of NeurologyLondonUnited Kingdom
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Lane CA, Parker TD, Cash DM, Macpherson K, Donnachie E, Murray-Smith H, Barnes A, Barker S, Beasley DG, Bras J, Brown D, Burgos N, Byford M, Jorge Cardoso M, Carvalho A, Collins J, De Vita E, Dickson JC, Epie N, Espak M, Henley SMD, Hoskote C, Hutel M, Klimova J, Malone IB, Markiewicz P, Melbourne A, Modat M, Schrag A, Shah S, Sharma N, Sudre CH, Thomas DL, Wong A, Zhang H, Hardy J, Zetterberg H, Ourselin S, Crutch SJ, Kuh D, Richards M, Fox NC, Schott JM. Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development. BMC Neurol 2017; 17:75. [PMID: 28420323 PMCID: PMC5395844 DOI: 10.1186/s12883-017-0846-x] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [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: 01/11/2017] [Accepted: 03/21/2017] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Increasing age is the biggest risk factor for dementia, of which Alzheimer's disease is the commonest cause. The pathological changes underpinning Alzheimer's disease are thought to develop at least a decade prior to the onset of symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key pathological processes underpinning cognitive impairment - including β-amyloid depostion, vascular disease, network breakdown and atrophy - to be assessed repeatedly and non-invasively. This enables potential determinants of dementia to be delineated earlier, and therefore opens a pre-symptomatic window where intervention may prevent the onset of cognitive symptoms. METHODS/DESIGN This paper outlines the clinical, cognitive and imaging protocol of "Insight 46", a neuroscience sub-study of the MRC National Survey of Health and Development. This is one of the oldest British birth cohort studies and has followed 5362 individuals since their birth in England, Scotland and Wales during one week in March 1946. These individuals have been tracked in 24 waves of data collection incorporating a wide range of health and functional measures, including repeat measures of cognitive function. Now aged 71 years, a small fraction have overt dementia, but estimates suggest that ~1/3 of individuals in this age group may be in the preclinical stages of Alzheimer's disease. Insight 46 is recruiting 500 study members selected at random from those who attended a clinical visit at 60-64 years and on whom relevant lifecourse data are available. We describe the sub-study design and protocol which involves a prospective two time-point (0, 24 month) data collection covering clinical, neuropsychological, β-amyloid positron emission tomography and magnetic resonance imaging, biomarker and genetic information. Data collection started in 2015 (age 69) and aims to be completed in 2019 (age 73). DISCUSSION Through the integration of data on the socioeconomic environment and on physical, psychological and cognitive function from 0 to 69 years, coupled with genetics, structural and molecular imaging, and intensive cognitive and neurological phenotyping, Insight 46 aims to identify lifetime factors which influence brain health and cognitive ageing, with particular focus on Alzheimer's disease and cerebrovascular disease. This will provide an evidence base for the rational design of disease-modifying trials.
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Affiliation(s)
- Christopher A. Lane
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Thomas D. Parker
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Dave M. Cash
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Kirsty Macpherson
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Elizabeth Donnachie
- Leonard Wolfson Experimental Neurology Centre, Institute of Neurology, University College London, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Anna Barnes
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Suzie Barker
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Daniel G. Beasley
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Jose Bras
- Department of Molecular Neuroscience, Institute of Neurology, University College London, London, UK
- Department of Medical Sciences and Institute of Biomedicine - iBiMED, University of Aveiro, Aveiro, Portugal
| | - David Brown
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Ninon Burgos
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | | | - M. Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Ana Carvalho
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Jessica Collins
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Enrico De Vita
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - John C. Dickson
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Norah Epie
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Miklos Espak
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Susie M. D. Henley
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Chandrashekar Hoskote
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Michael Hutel
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Jana Klimova
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Ian B. Malone
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Pawel Markiewicz
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Andrew Melbourne
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Marc Modat
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Anette Schrag
- Department of Clinical Neuroscience, Institute of Neurology, University College London, London, UK
| | - Sachit Shah
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Nikhil Sharma
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
- National Hospital for Neurology and Neurosurgery, London, UK
| | - Carole H. Sudre
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Institute of Neurology, University College London, London, UK
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, University College London, London, UK
| | - John Hardy
- Reta Lila Weston Research Laboratories, Department of Molecular Neuroscience, Institute of Neurology, University College London, London, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, Institute of Neurology, University College London, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Sebastian J. Crutch
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing at UCL, London, UK
| | | | - Nick C. Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Jonathan M. Schott
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
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