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Leckey CA, Coulton JB, Giovannucci TA, He Y, Aslanyan A, Laban R, Heslegrave A, Doykov I, Ammoscato F, Chataway J, De Angelis F, Gnanapavan S, Byrne LM, Schott JM, Wild EJ, Barthelémy NR, Zetterberg H, Wray S, Bateman RJ, Mills K, Paterson RW. CSF neurofilament light chain profiling and quantitation in neurological diseases. Brain Commun 2024; 6:fcae132. [PMID: 38707707 PMCID: PMC11069115 DOI: 10.1093/braincomms/fcae132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 05/07/2024] Open
Abstract
Neurofilament light chain is an established marker of neuroaxonal injury that is elevated in CSF and blood across various neurological diseases. It is increasingly used in clinical practice to aid diagnosis and monitor progression and as an outcome measure to assess safety and efficacy of disease-modifying therapies across the clinical translational neuroscience field. Quantitative methods for neurofilament light chain in human biofluids have relied on immunoassays, which have limited capacity to describe the structure of the protein in CSF and how this might vary in different neurodegenerative diseases. In this study, we characterized and quantified neurofilament light chain species in CSF across neurodegenerative and neuroinflammatory diseases and healthy controls using targeted mass spectrometry. We show that the quantitative immunoprecipitation-tandem mass spectrometry method developed in this study strongly correlates to single-molecule array measurements in CSF across the broad spectrum of neurodegenerative diseases and was replicable across mass spectrometry methods and centres. In summary, we have created an accurate and cost-effective assay for measuring a key biomarker in translational neuroscience research and clinical practice, which can be easily multiplexed and translated into clinical laboratories for the screening and monitoring of neurodegenerative disease or acute brain injury.
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Affiliation(s)
- Claire A Leckey
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Translational Mass Spectrometry Research Group, UCL Great Ormond Street Hospital Institute of Child Health, University College London, London, WC1N 1EH, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
| | - John B Coulton
- Department of Neurology, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
- Tracy Family SILQ Center, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
| | - Tatiana A Giovannucci
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Yingxin He
- Department of Neurology, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
- Tracy Family SILQ Center, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
| | - Aram Aslanyan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Rhiannon Laban
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Amanda Heslegrave
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Ivan Doykov
- Translational Mass Spectrometry Research Group, UCL Great Ormond Street Hospital Institute of Child Health, University College London, London, WC1N 1EH, UK
| | - Francesca Ammoscato
- Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Blizard Institute, Centre for Neuroscience, London, E1 2AT, UK
| | - Jeremy Chataway
- Department of Neuroinflammation, Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1B 5EH, UK
- National Institute for Health and Care Research, University College London Hospitals, Biomedical Research Centre, London, W1T 7DN, UK
| | - Floriana De Angelis
- Department of Neuroinflammation, Faculty of Brain Sciences, Queen Square Multiple Sclerosis Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1B 5EH, UK
- National Institute for Health and Care Research, University College London Hospitals, Biomedical Research Centre, London, W1T 7DN, UK
| | | | - Lauren M Byrne
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Edward J Wild
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Nicolas R Barthelémy
- Department of Neurology, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
- Tracy Family SILQ Center, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 43180, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 43180, 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, WI53792, USA
| | - Selina Wray
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
- Tracy Family SILQ Center, Washington University School of Medicine, Washington University in St Louis, St Louis, MO 63110, USA
| | - Kevin Mills
- Translational Mass Spectrometry Research Group, UCL Great Ormond Street Hospital Institute of Child Health, University College London, London, WC1N 1EH, UK
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, University College London, London, WC1E 6BT, UK
- Department of Neurology, Darent Valley Hospital, Dartford, Kent, DA2 8DA, UK
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Bollack A, Collij LE, García DV, Shekari M, Altomare D, Payoux P, Dubois B, Grau-Rivera O, Boada M, Marquié M, Nordberg A, Walker Z, Scheltens P, Schöll M, Wolz R, Schott JM, Gismondi R, Stephens A, Buckley C, Frisoni GB, Hanseeuw B, Visser PJ, Vandenberghe R, Drzezga A, Yaqub M, Boellaard R, Gispert JD, Markiewicz P, Cash DM, Farrar G, Barkhof F. Investigating reliable amyloid accumulation in Centiloids: Results from the AMYPAD Prognostic and Natural History Study. Alzheimers Dement 2024. [PMID: 38574374 DOI: 10.1002/alz.13761] [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: 10/09/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION To support clinical trial designs focused on early interventions, our study determined reliable early amyloid-β (Aβ) accumulation based on Centiloids (CL) in pre-dementia populations. METHODS A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease-Prognostic and Natural History Study (AMYPAD-PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid-PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub-populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision-recall analyses. Accumulation rates were examined using linear mixed-effect models. RESULTS Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aβ-accumulators. Rates of amyloid accumulation were tracer-independent, lower for APOE ε4 non-carriers, and for subjects with higher levels of education. DISCUSSION Our results support a 12-20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations.
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Affiliation(s)
- Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, London, UK
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Amsterdam Neuroscience, Brain Imaging, VU University Amsterdam, Amsterdam, The Netherlands
| | - David Vállez García
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Instituto de investigaciones médicas Hospital del Mar (IMIM), Barcelona, Spain
| | - Daniele Altomare
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Pierre Payoux
- Department of Nuclear Medicine, Imaging Pole, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, CHU Purpan, Pavillon Baudot, Place du Docteur Joseph Baylac, Toulouse, France
| | - Bruno Dubois
- Department of Neurology, Salpêtrière Hospital, AP-HP, Sorbonne University, Paris, France
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Mercè Boada
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Marta Marquié
- Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, UK
- Essex Partnership University NHS Foundation Trust, The Lodge, Wickford, UK
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Alzheimercentrum Amsterdam, Amsterdam, The Netherlands
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, The University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | | | | | | | - Giovanni B Frisoni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Bernard Hanseeuw
- Department of Neurology, Institute of Neuroscience, Université Catholique de Louvain, Cliniques Universitaires Saint-Luc, Brussels, Belgium
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
- WELBIO Department, WEL Research Institute, Wavre, Belgium
| | - Pieter Jelle Visser
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, LBI - KU Leuven Brain Institute, Leuven, Belgium
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital Cologne, Universitätsklinikums Köln, Köln, Germany
- Molecular Organization of the Brain, Institute for Neuroscience and Medicine, INM-2), Forschungszentrum Jülich GmbH, Jülich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
- Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain
| | - Pawel Markiewicz
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, London, UK
- Computer Science and Informatics, School of Engineering, London South Bank University, London, UK
| | - David M Cash
- Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | | | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, The Netherlands
- Queen Square Institute of Neurology, University College London, London, UK
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Parker TD, Hardy C, Keuss S, Coath W, Cash DM, Lu K, Nicholas JM, James SN, Sudre C, Crutch S, Bamiou DE, Warren JD, Fox NC, Richards M, Schott JM. Peripheral hearing loss at age 70 predicts brain atrophy and associated cognitive change. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-333101. [PMID: 38569877 DOI: 10.1136/jnnp-2023-333101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/04/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Hearing loss has been proposed as a modifiable risk factor for dementia. However, the relationship between hearing, neurodegeneration, and cognitive change, and the extent to which pathological processes such as Alzheimer's disease and cerebrovascular disease influence these relationships, is unclear. METHODS Data from 287 adults born in the same week of 1946 who underwent baseline pure tone audiometry (mean age=70.6 years) and two time point cognitive assessment/multimodal brain imaging (mean interval 2.4 years) were analysed. Hearing impairment at baseline was defined as a pure tone average of greater than 25 decibels in the best hearing ear. Rates of change for whole brain, hippocampal and ventricle volume were estimated from structural MRI using the Boundary Shift Integral. Cognition was assessed using the Pre-clinical Alzheimer's Cognitive Composite. Regression models were performed to evaluate how baseline hearing impairment associated with subsequent brain atrophy and cognitive decline after adjustment for a range of confounders including baseline β-amyloid deposition and white matter hyperintensity volume. RESULTS 111 out of 287 participants had hearing impairment. Compared with those with preserved hearing, hearing impaired individuals had faster rates of whole brain atrophy, and worse hearing (higher pure tone average) predicted faster rates of hippocampal atrophy. In participants with hearing impairment, faster rates of whole brain atrophy predicted greater cognitive change. All observed relationships were independent of β-amyloid deposition and white matter hyperintensity volume. CONCLUSIONS Hearing loss may influence dementia risk via pathways distinct from those typically implicated in Alzheimer's and cerebrovascular disease in cognitively unimpaired older adults.
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Affiliation(s)
- Thomas D Parker
- Department of Brain Sciences, Imperial College London, London, UK
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
- UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
| | - Chris Hardy
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - Sarah Keuss
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - William Coath
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - David M Cash
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Kirsty Lu
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - Jennifer M Nicholas
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Carole Sudre
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
- Centre for Medical Image Computing, University College London, London, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastian Crutch
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - Doris-Eva Bamiou
- UCL Ear Institute and UCLH Biomedical Research Centre, National Institute for Health Research, University College London, London, UK
| | - Jason D Warren
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - Nick C Fox
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- The Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, UK
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Biesbroek JM, Coenen M, DeCarli C, Fletcher EM, Maillard PM, Barkhof F, Barnes J, Benke T, Chen CPLH, Dal‐Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Hilal S, Hofer E, Koek HL, Maier AB, McCreary CR, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Sudre CH, Steketee RME, Teunissen CE, van den Berg E, van der Flier WM, Venketasubramanian N, Venkatraghavan V, Vernooij MW, Wolters FJ, Xin X, Kuijf HJ, Biessels GJ. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients. Alzheimers Dement 2024; 20:2980-2989. [PMID: 38477469 PMCID: PMC11032573 DOI: 10.1002/alz.13765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.
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Graham N, Zimmerman K, Heslegrave AJ, Keshavan A, Moro F, Abed-Maillard S, Bernini A, Dunet V, Garbero E, Nattino G, Chieregato A, Fainardi E, Baciu C, Gradisek P, Magnoni S, Oddo M, Bertolini G, Schott JM, Zetterberg H, Sharp D. Alzheimer's disease marker phospho-tau181 is not elevated in the first year after moderate-to-severe TBI. J Neurol Neurosurg Psychiatry 2024; 95:356-359. [PMID: 37833041 PMCID: PMC10958285 DOI: 10.1136/jnnp-2023-331854] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/19/2023] [Indexed: 10/15/2023]
Abstract
BACKGROUND Traumatic brain injury (TBI) is associated with the tauopathies Alzheimer's disease and chronic traumatic encephalopathy. Advanced immunoassays show significant elevations in plasma total tau (t-tau) early post-TBI, but concentrations subsequently normalise rapidly. Tau phosphorylated at serine-181 (p-tau181) is a well-validated Alzheimer's disease marker that could potentially seed progressive neurodegeneration. We tested whether post-traumatic p-tau181 concentrations are elevated and relate to progressive brain atrophy. METHODS Plasma p-tau181 and other post-traumatic biomarkers, including total-tau (t-tau), neurofilament light (NfL), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP), were assessed after moderate-to-severe TBI in the BIO-AX-TBI cohort (first sample mean 2.7 days, second sample within 10 days, then 6 weeks, 6 months and 12 months, n=42). Brain atrophy rates were assessed in aligned serial MRI (n=40). Concentrations were compared patients with and without Alzheimer's disease, with healthy controls. RESULTS Plasma p-tau181 concentrations were significantly raised in patients with Alzheimer's disease but not after TBI, where concentrations were non-elevated, and remained stable over one year. P-tau181 after TBI was not predictive of brain atrophy rates in either grey or white matter. In contrast, substantial trauma-associated elevations in t-tau, NfL, GFAP and UCH-L1 were seen, with concentrations of NfL and t-tau predictive of brain atrophy rates. CONCLUSIONS Plasma p-tau181 is not significantly elevated during the first year after moderate-to-severe TBI and levels do not relate to neuroimaging measures of neurodegeneration.
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Affiliation(s)
- Neil Graham
- Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
| | - Karl Zimmerman
- Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
| | | | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Federico Moro
- Laboratory of Acute Brain Injury and Neuroprotection, Department of Acute Brain and Cardiovascular Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
- Dipartimento di Anestesia e Rianimazione, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Samia Abed-Maillard
- Neuroscience Critical Care Research Group, Department of Intensive Care Medicine, CHUV Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Adriano Bernini
- Department of Clinical Neurosciences, CHUV Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Vincent Dunet
- Department of Medical Radiology, CHUV Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Elena Garbero
- Laboratory of Clinical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Italy
| | - Giovanni Nattino
- Laboratory of Clinical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Italy
| | - Arturo Chieregato
- Terapia Intensiva ad indirizzo Neurologico & Neurochirurgico, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Enrico Fainardi
- Department of Experimental and Clinical Sciences, Careggi University Hospital and University of Firenze, Florence, Italy
| | - Camelia Baciu
- Terapia Intensiva ad indirizzo Neurologico & Neurochirurgico, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Primoz Gradisek
- Clinical Department of Anaesthesiology and Intensive Therapy, University Medical Center, Ljubljana, Slovenia
| | - Sandra Magnoni
- Department of Anesthesia and Intensive Care, Santa Chiara Hospital, Trento, Italy
| | - Mauro Oddo
- Neuroscience Critical Care Research Group, Department of Intensive Care Medicine, CHUV Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Directorate for Innovation and Clinical Research, CHUV Lausanne University Hospital, Lausanne, Switzerland
| | - Guido Bertolini
- Laboratory of Clinical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Ranica, Italy
| | - Jonathan M Schott
- UK Dementia Research Institute, University College London, London, UK
- Dementia Research Centre and Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute, University College London, London, UK
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - David Sharp
- Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
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Green RE, Sudre CH, Warren‐Gash C, Butt J, Waterboer T, Hughes AD, Schott JM, Richards M, Chaturvedi N, Williams DM. Common infections and neuroimaging markers of dementia in three UK cohort studies. Alzheimers Dement 2024; 20:2128-2142. [PMID: 38248636 PMCID: PMC10984486 DOI: 10.1002/alz.13613] [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: 07/20/2023] [Revised: 10/13/2023] [Accepted: 11/25/2023] [Indexed: 01/23/2024]
Abstract
INTRODUCTION We aimed to investigate associations between common infections and neuroimaging markers of dementia risk (brain volume, hippocampal volume, white matter lesions) across three population-based studies. METHODS We tested associations between serology measures (pathogen serostatus, cumulative burden, continuous antibody responses) and outcomes using linear regression, including adjustments for total intracranial volume and scanner/clinic information (basic model), age, sex, ethnicity, education, socioeconomic position, alcohol, body mass index, and smoking (fully adjusted model). Interactions between serology measures and apolipoprotein E (APOE) genotype were tested. Findings were meta-analyzed across cohorts (Nmain = 2632; NAPOE-interaction = 1810). RESULTS Seropositivity to John Cunningham virus associated with smaller brain volumes in basic models (β = -3.89 mL [-5.81, -1.97], Padjusted < 0.05); these were largely attenuated in fully adjusted models (β = -1.59 mL [-3.55, 0.36], P = 0.11). No other relationships were robust to multiple testing corrections and sensitivity analyses, but several suggestive associations were observed. DISCUSSION We did not find clear evidence for relationships between common infections and markers of dementia risk. Some suggestive findings warrant testing for replication.
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Affiliation(s)
- Rebecca E. Green
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Carole H. Sudre
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringCentre for Medical Image Computing (CMIC)University College London (UCL)LondonUK
| | - Charlotte Warren‐Gash
- Faculty of Epidemiology and Population HealthLondon School of Hygiene and Tropical MedicineLondonUK
| | - Julia Butt
- Division of Infections and Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Tim Waterboer
- Division of Infections and Cancer EpidemiologyGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Alun D. Hughes
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | | | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
| | - Dylan M. Williams
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
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7
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Hardy J, Schott JM. Identifying Genetic Risk for Amyloid-Related Imaging Abnormalities. Neurology 2024; 102:e208096. [PMID: 38165303 DOI: 10.1212/wnl.0000000000208096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
In the last 2 years, there have been 3 successful trials of antiamyloid antibodies in Alzheimer disease (AD): aducanemab, now controversially US Food and Drug Administration-approved under the accelerated approval pathway1; lecanemab, now FDA-approved2; and donanemab, now going through the approval process.3 All 3 share a common broad mechanism, that is, antibody-mediated removal of β-amyloid (Aβ) from the brain, and this is almost certainly the basis of their therapeutic action.4 When used in the earliest symptomatic stages of AD, all have modest clinical effects, all clear Aβ from the brain, and all show evidence for some changes in molecular markers believed to be downstream of Aβ accumulation in keeping with disease modification.4 However, all these drugs-and several other antiamyloid immunotherapies that failed to show positive effects in clinical trials (e.g. bapineuzemab and gantenerumab)5,6-have the troubling adverse event of antibody-related imaging abnormalities (ARIA). ARIA can take the form of vasogenic edema or sulcal effusion (ARIA-E) or haemosiderin deposition due to hemorrhage (ARIA-H).7 In vivo, ARIA is detected using MRI: ARIA-E is visible on fluid attenuation inversion recovery sequences; ARIA-H is best seen on iron-sensitive (T2* or susceptibility-weighted imaging) as microbleeds and/or superficial hemosiderin deposition. The pathophysiology of ARIA has yet to be fully determined but may result from antibody-mediated breakdown of amyloid plaques releasing Aβ which is deposited in vessels leading to increased cerebral amyloid angiopathy or alterations in perivascular clearance or inflammation, possibly through complement activation.8.
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Affiliation(s)
- John Hardy
- From the Department of Neurodegenerative Disease (J.H., J.M.S.), UCL Institute of Neurology, London, UK
| | - Jonathan M Schott
- From the Department of Neurodegenerative Disease (J.H., J.M.S.), UCL Institute of Neurology, London, UK
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8
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Banerjee G, Farmer SF, Hyare H, Jaunmuktane Z, Mead S, Ryan NS, Schott JM, Werring DJ, Rudge P, Collinge J. Iatrogenic Alzheimer's disease in recipients of cadaveric pituitary-derived growth hormone. Nat Med 2024; 30:394-402. [PMID: 38287166 PMCID: PMC10878974 DOI: 10.1038/s41591-023-02729-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 10/03/2023] [Accepted: 11/17/2023] [Indexed: 01/31/2024]
Abstract
Alzheimer's disease (AD) is characterized pathologically by amyloid-beta (Aβ) deposition in brain parenchyma and blood vessels (as cerebral amyloid angiopathy (CAA)) and by neurofibrillary tangles of hyperphosphorylated tau. Compelling genetic and biomarker evidence supports Aβ as the root cause of AD. We previously reported human transmission of Aβ pathology and CAA in relatively young adults who had died of iatrogenic Creutzfeldt-Jakob disease (iCJD) after childhood treatment with cadaver-derived pituitary growth hormone (c-hGH) contaminated with both CJD prions and Aβ seeds. This raised the possibility that c-hGH recipients who did not die from iCJD may eventually develop AD. Here we describe recipients who developed dementia and biomarker changes within the phenotypic spectrum of AD, suggesting that AD, like CJD, has environmentally acquired (iatrogenic) forms as well as late-onset sporadic and early-onset inherited forms. Although iatrogenic AD may be rare, and there is no suggestion that Aβ can be transmitted between individuals in activities of daily life, its recognition emphasizes the need to review measures to prevent accidental transmissions via other medical and surgical procedures. As propagating Aβ assemblies may exhibit structural diversity akin to conventional prions, it is possible that therapeutic strategies targeting disease-related assemblies may lead to selection of minor components and development of resistance.
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Affiliation(s)
- Gargi Banerjee
- MRC Prion Unit at UCL and UCL Institute of Prion Diseases, London, UK
- National Prion Clinic, National Hospital for Neurology and Neurosurgery, London, UK
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Harpreet Hyare
- UCL Queen Square Institute of Neurology, London, UK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Zane Jaunmuktane
- Department of Clinical and Movement Neurosciences and Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
- Division of Neuropathology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Simon Mead
- MRC Prion Unit at UCL and UCL Institute of Prion Diseases, London, UK
- National Prion Clinic, National Hospital for Neurology and Neurosurgery, London, UK
| | - Natalie S Ryan
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - David J Werring
- Stroke Research Centre, UCL Queen Square Institute of Neurology, London, UK
- Stroke Service, National Hospital for Neurology and Neurosurgery, London, UK
| | - Peter Rudge
- MRC Prion Unit at UCL and UCL Institute of Prion Diseases, London, UK
- National Prion Clinic, National Hospital for Neurology and Neurosurgery, London, UK
| | - John Collinge
- MRC Prion Unit at UCL and UCL Institute of Prion Diseases, London, UK.
- National Prion Clinic, National Hospital for Neurology and Neurosurgery, London, UK.
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9
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Macdougall A, Whitfield T, Needham K, Schott JM, Frost C, Walker Z. Predicting progression to Alzheimer's disease dementia using cognitive measures. Int J Geriatr Psychiatry 2024; 39:e6067. [PMID: 38323729 DOI: 10.1002/gps.6067] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 01/27/2024] [Indexed: 02/08/2024]
Abstract
OBJECTIVES It is important to determine if cognitive measures identified as being prognostic in dementia research cohorts also have utility in memory clinics. We aimed to identify measures with the greatest power to predict future Alzheimer's disease (AD) dementia in a clinical setting where expensive biomarkers are not widely available. METHODS This study utilized routine Memory Clinic data collected over 18 years. From 2214 patients assessed in the clinic, we selected 328 patients with an initial diagnosis of subjective cognitive decline or mild cognitive impairment. We compared two types of statistical model for the prediction of AD dementia. The first model included baseline cognitive test scores only, while the second model also included change scores between baseline and the first follow-up. RESULTS Baseline scores on tests of global cognitive function (Mini-mental state examination and Cambridge Cognitive Examination-Revised), verbal episodic memory and psychomotor speed were the best predictors of conversion to AD dementia. The inclusion of cognitive change scores over 1 year of follow-up improved predictive accuracy versus baseline scores alone. CONCLUSIONS We found that the best cognitive predictors of AD dementia in a clinical setting were similar to those previously identified using research cohorts. Taking change in cognitive function into account enabled the onset of AD dementia to be predicted with greater accuracy.
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Affiliation(s)
- Amy Macdougall
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Tim Whitfield
- Division of Psychiatry, University College London, London, UK
| | - Kelly Needham
- School of Health and Related Research (ScHARR), The University of Sheffield, Sheffield, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Chris Frost
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, UK
- Essex Partnership University NHS Foundation Trust, Wickford, UK
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10
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Young AL, Oxtoby NP, Garbarino S, Fox NC, Barkhof F, Schott JM, Alexander DC. Data-driven modelling of neurodegenerative disease progression: thinking outside the black box. Nat Rev Neurosci 2024; 25:111-130. [PMID: 38191721 DOI: 10.1038/s41583-023-00779-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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] [Accepted: 11/30/2023] [Indexed: 01/10/2024]
Abstract
Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.
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Affiliation(s)
- Alexandra L Young
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Neil P Oxtoby
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
| | - Sara Garbarino
- Life Science Computational Laboratory, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Daniel C Alexander
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
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11
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Chapleau M, La Joie R, Yong K, Agosta F, Allen IE, Apostolova L, Best J, Boon BDC, Crutch S, Filippi M, Fumagalli GG, Galimberti D, Graff-Radford J, Grinberg LT, Irwin DJ, Josephs KA, Mendez MF, Mendez PC, Migliaccio R, Miller ZA, Montembeault M, Murray ME, Nemes S, Pelak V, Perani D, Phillips J, Pijnenburg Y, Rogalski E, Schott JM, Seeley W, Sullivan AC, Spina S, Tanner J, Walker J, Whitwell JL, Wolk DA, Ossenkoppele R, Rabinovici GD. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis. Lancet Neurol 2024; 23:168-177. [PMID: 38267189 DOI: 10.1016/s1474-4422(23)00414-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/22/2023] [Accepted: 10/18/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING None.
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Affiliation(s)
- Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Keir Yong
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Federica Agosta
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - John Best
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Baayla D C Boon
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Sebastian Crutch
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Massimo Filippi
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | | | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | | | - Lea T Grinberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Mario F Mendez
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Patricio Chrem Mendez
- Memory Center, Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia, Buenos Aires Argentina
| | - Raffaella Migliaccio
- Paris Brain Institute (ICM), FrontLab, Institut de la mémoire et de la maladie d'Alzheimer (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, Paris, France
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maxime Montembeault
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Sára Nemes
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Victoria Pelak
- Departments of Neurology and Ophthalmology, Divisions of Neuro-Ophthalmology and Behavioral Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Daniela Perani
- Vita-Salute, San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele, San Raffaele University, Milan, Italy
| | - Jeffrey Phillips
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology & Alzheimer's Disease, Northwestern University, Evanston, IL, USA
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands
| | - William Seeley
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - A Campbell Sullivan
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Jeremy Tanner
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jamie Walker
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | | | - David A Wolk
- Alzheimer's Disease Research Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands; Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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12
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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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14
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Coenen M, Biessels GJ, DeCarli C, Fletcher EF, Maillard PM, Barkhof F, Barnes J, Benke T, Boomsma JMF, P L H Chen C, Dal-Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Groeneveld O, Hilal S, Hofer E, Koek HL, Maier AB, McCreary CR, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Sudre CH, Steketee RME, van den Berg E, van der Flier WM, Venketasubramanian N, Vernooij MW, Wolters FJ, Xin X, Biesbroek JM, Kuijf HJ. Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts. Neuroimage Clin 2023; 40:103547. [PMID: 38035457 PMCID: PMC10698002 DOI: 10.1016/j.nicl.2023.103547] [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: 08/27/2023] [Revised: 11/03/2023] [Accepted: 11/21/2023] [Indexed: 12/02/2023]
Abstract
INTRODUCTION The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.
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Affiliation(s)
- Mirthe Coenen
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands.
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, USA
| | - Evan F Fletcher
- Department of Neurology, University of California at Davis, USA
| | | | - Frederik Barkhof
- Radiology & Nuclear Medicine, Amsterdam UMC, Location Vrije Universiteit, the Netherlands; UCL Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Thomas Benke
- Clinic of Neurology, Medical University Innsbruck, Austria
| | - Jooske M F Boomsma
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Christopher P L H Chen
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | | | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Christian Enzinger
- Division of General Neurology, Department of Neurology, Medical University Graz, Austria; Division of Neuroradiology, Interventional and Vascular Radiology, Department of Radiology, Medical University of Graz, Austria
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Lieza G Exalto
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Onno Groeneveld
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands; Department of Neurology, Isala, Meppel, the Netherlands
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Edith Hofer
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
| | - Huiberdina L Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Andrea B Maier
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore; Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Cheryl R McCreary
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Janne M Papma
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Anna Rubinski
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Reinhold Schmidt
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Eric E Smith
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Carole H Sudre
- 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 & Imaging Sciences, King's College London, London, UK
| | - Rebecca M E Steketee
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Esther van den Berg
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Narayanaswamy Venketasubramanian
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore; Raffles Neuroscience Center, Raffles Hospital, Singapore, Singapore
| | - Meike W Vernooij
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Frank J Wolters
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Xu Xin
- Department of Pharmacology, National University of Singapore, Singapore, Singapore; Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, Utrecht, the Netherlands; Department of Neurology, Diakonessenhuis Hospital, Utrecht, the Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
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15
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Liu Y, Patalay P, Stafford J, Schott JM, Richards M. Lifecourse investigation of the cumulative impact of adversity on cognitive function in old age and the mediating role of mental health: longitudinal birth cohort study. BMJ Open 2023; 13:e074105. [PMID: 37940163 PMCID: PMC10632868 DOI: 10.1136/bmjopen-2023-074105] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 10/23/2023] [Indexed: 11/10/2023] Open
Abstract
OBJECTIVE To investigate the accumulation of adversities (duration of exposure to any, economic, psychosocial) across the lifecourse (birth to 63 years) on cognitive function in older age, and the mediating role of mental health. DESIGN National birth cohort study. SETTING Great Britain. PARTICIPANTS 5362 singleton births within marriage in England, Wales and Scotland born within 1 week of March 1946, of which 2131 completed at least 1 cognitive assessment. MAIN OUTCOME MEASURES Cognitive assessments included the Addenbrooke's Cognitive Examination-III, as a measure of cognitive state, processing speed (timed-letter search task), and verbal memory (word learning task) at 69 years. Scores were standardised to the analytical sample. Mental health at 60-64 years was assessed using the 28-item General Health Questionnaire, with scores standardised to the analytical sample. RESULTS After adjusting for sex, increased duration of exposure to any adversity was associated with decreased performance on cognitive state (β=-0.39; 95% CI -0.59 to -0.20) and verbal memory (β=-0.45; 95% CI -0.63 to -0.27) at 69 years, although these effects were attenuated after adjusting for further covariates (childhood cognition and emotional problems, educational attainment). Analyses by type of adversity revealed stronger associations from economic adversity to verbal memory (β=-0.54; 95% CI -0.70 to -0.39), with a small effect remaining even after adjusting for all covariates (β=-0.18; 95% CI -0.32 to -0.03), and weaker associations from psychosocial adversity. Causal mediation analyses found that mental health mediated all associations between duration of exposure to adversity (any, economic, psychosocial) and cognitive function, with around 15% of the total effect of economic adversity on verbal memory attributable to mental health. CONCLUSIONS Improving mental health among older adults has the potential to reduce cognitive impairments, as well as mitigate against some of the effect of lifecourse accumulation of adversity on cognitive performance in older age.
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Affiliation(s)
- Yiwen Liu
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Jean Stafford
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
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16
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Liu Y, Hatch SL, Patalay P, Schott JM, Richards M. A lifecourse approach in examining the association between accumulation of adversity and mental health in older adulthood. J Affect Disord 2023; 339:211-218. [PMID: 37442442 DOI: 10.1016/j.jad.2023.07.001] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/01/2023] [Accepted: 07/08/2023] [Indexed: 07/15/2023]
Abstract
BACKGROUND There is evidence for a cumulative effect of adversities on mental health, however, less is known on the accumulating duration of exposure to adversity across the lifecourse on mental health in older adults. METHODS Using data from the 1946 British birth cohort study (N = 2745), we examined associations between the accumulation of adversity (birth-63 years) and mental health (emotional symptom, life satisfaction, affective wellbeing) in older adults (63-69 years). Accumulation of adversity was assessed as the number of adversities and duration of exposure (number of lifecourse stages exposed to any, economic, psychosocial, or physical adversity). Linear regression tested their association with mental health, adjusted for sex, childhood cognition and emotional problems, and educational attainment. RESULTS Increased number of adversities was associated with increased emotional symptoms (β = 0.08 [0.06, 0.10]), decreased life satisfaction (β = -0.14 [-0.16, -0.12]) and decreased affective wellbeing (β = -0.08 [-0.10, -0.06]). Each additional duration of exposure was associated with a 0.38 [0.12, 0.65] standard deviation (SD) increase in emotional symptoms, and a - 0.68 [-0.96, -0.39] and -0.43 SD [-0.68, -0.18] decrease in life satisfaction and affective wellbeing, respectively. Life satisfaction showed stronger associations with economic and psychosocial compared to physical adversity. LIMITATIONS Some limitations include selective drop-out and lack of ethnic diversity. CONCLUSIONS Efforts to improve mental health in older adults should focus on reducing the number of adversities, as well as considering previous exposure across different lifecourse stages, to prevent adversities from becoming chronic. Future research should also consider the clustering and co-occurrence of different adversities across the lifecourse.
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Affiliation(s)
- Yiwen Liu
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK.
| | - Stephani L Hatch
- Department of Psychological Medicine, King's College London, London, UK; ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK; Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
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17
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Bollack A, Markiewicz PJ, Wink AM, Prosser L, Lilja J, Bourgeat P, Schott JM, Coath W, Collij LE, Pemberton HG, Farrar G, Barkhof F, Cash DM. Evaluation of novel data-driven metrics of amyloid β deposition for longitudinal PET studies. Neuroimage 2023; 280:120313. [PMID: 37595816 DOI: 10.1016/j.neuroimage.2023.120313] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/29/2023] [Accepted: 08/04/2023] [Indexed: 08/20/2023] Open
Abstract
PURPOSE Positron emission tomography (PET) provides in vivo quantification of amyloid-β (Aβ) pathology. Established methods for assessing Aβ burden can be affected by physiological and technical factors. Novel, data-driven metrics have been developed to account for these sources of variability. We aimed to evaluate the performance of four of these amyloid PET metrics against conventional techniques, using a common set of criteria. METHODS Three cohorts were used for evaluation: Insight 46 (N=464, [18F]florbetapir), AIBL (N=277, [18F]flutemetamol), and an independent test-retest data (N=10, [18F]flutemetamol). Established metrics of amyloid tracer uptake included the Centiloid (CL) and where dynamic data was available, the non-displaceable binding potential (BPND). The four data-driven metrics computed were the amyloid load (Aβ load), the Aβ-PET pathology accumulation index (Aβ index), the Centiloid derived from non-negative matrix factorisation (CLNMF), and the amyloid pattern similarity score (AMPSS). These metrics were evaluated using reliability and repeatability in test-retest data, associations with BPND and CL, variability of the rate of change and sample size estimates to detect a 25% slowing in Aβ accumulation. RESULTS All metrics showed good reliability. Aβ load, Aβ index and CLNMF were strong associated with the BPND. The associations with CL suggest that cross-sectional measures of CLNMF, Aβ index and Aβ load are robust across studies. Sample size estimates for secondary prevention trial scenarios were the lowest for CLNMF and Aβ load compared to the CL. CONCLUSION Among the novel data-driven metrics evaluated, the Aβ load, the Aβ index and the CLNMF can provide comparable performance to more established quantification methods of Aβ PET tracer uptake. The CLNMF and Aβ load could offer a more precise alternative to CL, although further studies in larger cohorts should be conducted.
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Affiliation(s)
- Ariane Bollack
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK.
| | - Pawel J Markiewicz
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Alle Meije Wink
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
| | - Lloyd Prosser
- 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
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Lyduine E Collij
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Hugh G Pemberton
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; GE HealthCare, Amersham, UK; Queen Square Institute of Neurology, University College London, UK
| | | | - Frederik Barkhof
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK; Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands; Queen Square Institute of Neurology, University College London, UK
| | - David M Cash
- Queen Square Institute of Neurology, University College London, UK; UK Dementia Research Institute at University College London, London, UK
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18
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Banerjee G, Collinge J, Fox NC, Lashley T, Mead S, Schott JM, Werring DJ, Ryan NS. Clinical considerations in early-onset cerebral amyloid angiopathy. Brain 2023; 146:3991-4014. [PMID: 37280119 PMCID: PMC10545523 DOI: 10.1093/brain/awad193] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 04/16/2023] [Accepted: 05/01/2023] [Indexed: 06/08/2023] Open
Abstract
Cerebral amyloid angiopathy (CAA) is an important cerebral small vessel disease associated with brain haemorrhage and cognitive change. The commonest form, sporadic amyloid-β CAA, usually affects people in mid- to later life. However, early-onset forms, though uncommon, are increasingly recognized and may result from genetic or iatrogenic causes that warrant specific and focused investigation and management. In this review, we firstly describe the causes of early-onset CAA, including monogenic causes of amyloid-β CAA (APP missense mutations and copy number variants; mutations of PSEN1 and PSEN2) and non-amyloid-β CAA (associated with ITM2B, CST3, GSN, PRNP and TTR mutations), and other unusual sporadic and acquired causes including the newly-recognized iatrogenic subtype. We then provide a structured approach for investigating early-onset CAA, and highlight important management considerations. Improving awareness of these unusual forms of CAA amongst healthcare professionals is essential for facilitating their prompt diagnosis, and an understanding of their underlying pathophysiology may have implications for more common, late-onset, forms of the disease.
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Affiliation(s)
- Gargi Banerjee
- MRC Prion Unit at University College London (UCL), Institute of Prion Diseases, UCL, London, W1W 7FF, UK
| | - John Collinge
- MRC Prion Unit at University College London (UCL), Institute of Prion Diseases, UCL, London, W1W 7FF, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
| | - Tammaryn Lashley
- The Queen Square Brain Bank for Neurological Disorders, Department of Clinical and Movement Disorders, UCL Queen Square Institute of Neurology, London, W1 1PJ, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Simon Mead
- MRC Prion Unit at University College London (UCL), Institute of Prion Diseases, UCL, London, W1W 7FF, UK
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
| | - David J Werring
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Natalie S Ryan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
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Hällqvist J, Pinto RC, Heywood WE, Cordey J, Foulkes AJM, Slattery CF, Leckey CA, Murphy EC, Zetterberg H, Schott JM, Mills K, Paterson RW. A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning. Int J Mol Sci 2023; 24:13758. [PMID: 37762058 PMCID: PMC10531486 DOI: 10.3390/ijms241813758] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
As disease-modifying therapies are now available for Alzheimer's disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD.
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Affiliation(s)
- Jenny Hällqvist
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Rui C. Pinto
- Faculty of Medicine, School of Public Health, Imperial College London, London SW7 2BX, UK
| | - Wendy E. Heywood
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Jonjo Cordey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | | | | | - Claire A. Leckey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Eimear C. Murphy
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- UK Dementia Research Institute, UCL, London WC1E 6BT, UK
| | - Jonathan M. Schott
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Kevin Mills
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Ross W. Paterson
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Darent Valley Hospital, Dartford DA2 8DA, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
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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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Graham NS, Cole JH, Bourke NJ, Schott JM, Sharp DJ. Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease. Alzheimers Dement 2023; 19:3065-3077. [PMID: 36696255 PMCID: PMC10955776 DOI: 10.1002/alz.12934] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Traumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI. METHODS A total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared. RESULTS AD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD. DISCUSSION Post-traumatic neurodegeneration 1.9-4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger. HIGHLIGHTS We compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging. Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging. This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration.
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Affiliation(s)
- Neil S.N. Graham
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
| | - James H. Cole
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Centre for Medical Image ComputingUCLLondonUK
| | - Niall J. Bourke
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
| | | | - David J. Sharp
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
- Centre for Injury StudiesImperial College LondonLondonUK
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Arber C, Casey JM, Crawford S, Rambarack N, Yaman U, Wiethoff S, Augustin E, Piers TM, Rostagno A, Ghiso J, Lewis PA, Revesz T, Hardy J, Pocock JM, Houlden H, Schott JM, Salih DA, Lashley T, Wray S. Microglia produce the amyloidogenic ABri peptide in familial British dementia. bioRxiv 2023:2023.06.27.546552. [PMID: 37425748 PMCID: PMC10327149 DOI: 10.1101/2023.06.27.546552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Mutations in ITM2B cause familial British, Danish, Chinese and Korean dementias. In familial British dementia (FBD) a mutation in the stop codon of the ITM2B gene (also known as BRI2 ) causes a C-terminal cleavage fragment of the ITM2B/BRI2 protein to be extended by 11 amino acids. This fragment, termed amyloid-Bri (ABri), is highly insoluble and forms extracellular plaques in the brain. ABri plaques are accompanied by tau pathology, neuronal cell death and progressive dementia, with striking parallels to the aetiology and pathogenesis of Alzheimer's disease. The molecular mechanisms underpinning FBD are ill-defined. Using patient-derived induced pluripotent stem cells, we show that expression of ITM2B/BRI2 is 34-fold higher in microglia than neurons, and 15-fold higher in microglia compared with astrocytes. This cell-specific enrichment is supported by expression data from both mouse and human brain tissue. ITM2B/BRI2 protein levels are higher in iPSC-microglia compared with neurons and astrocytes. Consequently, the ABri peptide was detected in patient iPSC-derived microglial lysates and conditioned media but was undetectable in patient-derived neurons and control microglia. Pathological examination of post-mortem tissue support ABri expression in microglia that are in proximity to pre-amyloid deposits. Finally, gene co-expression analysis supports a role for ITM2B/BRI2 in disease-associated microglial responses. These data demonstrate that microglia are the major contributors to the production of amyloid forming peptides in FBD, potentially acting as instigators of neurodegeneration. Additionally, these data also suggest ITM2B/BRI2 may be part of a microglial response to disease, motivating further investigations of its role in microglial activation. This has implications for our understanding of the role of microglia and the innate immune response in the pathogenesis of FBD and other neurodegenerative dementias including Alzheimer's disease.
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Verdi S, Rutherford S, Fraza C, Tosun D, Altmann A, Raket LL, Schott JM, Marquand AF, Cole JH. Personalising Alzheimer's Disease progression using brain atrophy markers. medRxiv 2023:2023.06.15.23291418. [PMID: 37398392 PMCID: PMC10312850 DOI: 10.1101/2023.06.15.23291418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
INTRODUCTION Neuroanatomical normative modelling can capture individual variability in Alzheimer's Disease (AD). We used neuroanatomical normative modelling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS Cortical thickness and subcortical volume neuroanatomical normative models were generated using healthy controls (n~58k). These models were used to calculate regional Z-scores in 4361 T1-weighted MRI time-series scans. Regions with Z-scores <-1.96 were classified as outliers and mapped on the brain, and also summarised by total outlier count (tOC). RESULTS Rate of change in tOC increased in AD and in people with MCI who converted to AD and correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of MCI progression to AD. Brain Z-score maps showed that the hippocampus had the highest rate of atrophy change. CONCLUSIONS Individual-level atrophy rates can be tracked by using regional outlier maps and tOC.
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Affiliation(s)
- Serena Verdi
- Centre for Medical Image Computing, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Saige Rutherford
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Charlotte Fraza
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London, UK
| | - Lars Lau Raket
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - James H Cole
- Centre for Medical Image Computing, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
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Verdi S, Kia SM, Yong KXX, Tosun D, Schott JM, Marquand AF, Cole JH. Revealing Individual Neuroanatomical Heterogeneity in Alzheimer Disease Using Neuroanatomical Normative Modeling. Neurology 2023; 100:e2442-e2453. [PMID: 37127353 PMCID: PMC10264044 DOI: 10.1212/wnl.0000000000207298] [Citation(s) in RCA: 6] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 03/02/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Alzheimer disease (AD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology. To explore this, we used neuroanatomical normative modeling to index regional patterns of variability in cortical thickness. We aimed to characterize individual differences and outliers in cortical thickness in patients with AD, people with mild cognitive impairment (MCI), and controls. Furthermore, we assessed the relationships between cortical thickness heterogeneity and cognitive function, β-amyloid, phosphorylated-tau, and ApoE genotype. Finally, we examined whether cortical thickness heterogeneity was predictive of conversion from MCI to AD. METHODS Cortical thickness measurements across 148 brain regions were obtained from T1-weighted MRI scans from 62 sites of the Alzheimer's Disease Neuroimaging Initiative. AD was determined by clinical and neuropsychological examination with no comorbidities present. Participants with MCI had reported memory complaints, and controls were cognitively normal. A neuroanatomical normative model indexed cortical thickness distributions using a separate healthy reference data set (n = 33,072), which used hierarchical Bayesian regression to predict cortical thickness per region using age and sex, while adjusting for site noise. Z-scores per region were calculated, resulting in a Z-score brain map per participant. Regions with Z-scores <-1.96 were classified as outliers. RESULTS Patients with AD (n = 206) had a median of 12 outlier regions (out of a possible 148), with the highest proportion of outliers (47%) in the parahippocampal gyrus. For 62 regions, over 90% of these patients had cortical thicknesses within the normal range. Patients with AD had more outlier regions than people with MCI (n = 662) or controls (n = 159) (F(2, 1,022) = 95.39, p = 2.0 × 10-16). They were also more dissimilar to each other than people with MCI or controls (F(2, 1,024) = 209.42, p = 2.2 × 10-16). A greater number of outlier regions were associated with worse cognitive function, CSF protein concentrations, and an increased risk of converting from MCI to AD within 3 years (hazard ratio 1.028, 95% CI 1.016-1.039, p = 1.8 × 10-16). DISCUSSION Individualized normative maps of cortical thickness highlight the heterogeneous effect of AD on the brain. Regional outlier estimates have the potential to be a marker of disease and could be used to track an individual's disease progression or treatment response in clinical trials.
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Affiliation(s)
- Serena Verdi
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Seyed Mostafa Kia
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Keir X X Yong
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Duygu Tosun
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Jonathan M Schott
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Andre F Marquand
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands
| | - James H Cole
- From the Centre for Medical Image Computing (S.V., J.H.C.), Medical Physics and Biomedical Engineering, University College London; Dementia Research Centre (S.V., K.X.X.Y., J.M.S., J.H.C.), UCL Queen Square Institute of Neurology, London, United Kingdom; Donders Centre for Cognitive Neuroimaging (S.M.K., A.F.M.), Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen; Department of Psychiatry (S.M.K.), University Medical Centre Utrecht, the Netherlands; Department of Radiology and Biomedical Imaging (D.T.), University of California, San Francisco; and Department of Cognitive Neuroscience (A.F.M.), Radboud University Medical Centre, Nijmegen, the Netherlands.
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Mok TH, Nihat A, Majbour N, Sequeira D, Holm-Mercer L, Coysh T, Darwent L, Batchelor M, Groveman BR, Orr CD, Hughson AG, Heslegrave A, Laban R, Veleva E, Paterson RW, Keshavan A, Schott JM, Swift IJ, Heller C, Rohrer JD, Gerhard A, Butler C, Rowe JB, Masellis M, Chapman M, Lunn MP, Bieschke J, Jackson GS, Zetterberg H, Caughey B, Rudge P, Collinge J, Mead S. Seed amplification and neurodegeneration marker trajectories in individuals at risk of prion disease. Brain 2023; 146:2570-2583. [PMID: 36975162 PMCID: PMC10232278 DOI: 10.1093/brain/awad101] [Citation(s) in RCA: 6] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/17/2023] [Accepted: 03/13/2023] [Indexed: 03/29/2023] Open
Abstract
Human prion diseases are remarkable for long incubation times followed typically by rapid clinical decline. Seed amplification assays and neurodegeneration biofluid biomarkers are remarkably useful in the clinical phase, but their potential to predict clinical onset in healthy people remains unclear. This is relevant not only to the design of preventive strategies in those at-risk of prion diseases, but more broadly, because prion-like mechanisms are thought to underpin many neurodegenerative disorders. Here, we report the accrual of a longitudinal biofluid resource in patients, controls and healthy people at risk of prion diseases, to which ultrasensitive techniques such as real-time quaking-induced conversion (RT-QuIC) and single molecule array (Simoa) digital immunoassays were applied for preclinical biomarker discovery. We studied 648 CSF and plasma samples, including 16 people who had samples taken when healthy but later developed inherited prion disease (IPD) ('converters'; range from 9.9 prior to, and 7.4 years after onset). Symptomatic IPD CSF samples were screened by RT-QuIC assay variations, before testing the entire collection of at-risk samples using the most sensitive assay. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), tau and UCH-L1 levels were measured in plasma and CSF. Second generation (IQ-CSF) RT-QuIC proved 100% sensitive and specific for sporadic Creutzfeldt-Jakob disease (CJD), iatrogenic and familial CJD phenotypes, and subsequently detected seeding activity in four presymptomatic CSF samples from three E200K carriers; one converted in under 2 months while two remain asymptomatic after at least 3 years' follow-up. A bespoke HuPrP P102L RT-QuIC showed partial sensitivity for P102L disease. No compatible RT-QuIC assay was discovered for classical 6-OPRI, A117V and D178N, and these at-risk samples tested negative with bank vole RT-QuIC. Plasma GFAP and NfL, and CSF NfL levels emerged as proximity markers of neurodegeneration in the typically slow IPDs (e.g. P102L), with significant differences in mean values segregating healthy control from IPD carriers (within 2 years to onset) and symptomatic IPD cohorts; plasma GFAP appears to change before NfL, and before clinical conversion. In conclusion, we show distinct biomarker trajectories in fast and slow IPDs. Specifically, we identify several years of presymptomatic seeding positivity in E200K, a new proximity marker (plasma GFAP) and sequential neurodegenerative marker evolution (plasma GFAP followed by NfL) in slow IPDs. We suggest a new preclinical staging system featuring clinical, seeding and neurodegeneration aspects, for validation with larger prion at-risk cohorts, and with potential application to other neurodegenerative proteopathies.
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Affiliation(s)
- Tze How Mok
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Akin Nihat
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Nour Majbour
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Danielle Sequeira
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Leah Holm-Mercer
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Thomas Coysh
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Lee Darwent
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Mark Batchelor
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Bradley R Groveman
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Christina D Orr
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Andrew G Hughson
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Amanda Heslegrave
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Rhiannon Laban
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Elena Veleva
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
| | - Ross W Paterson
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Ashvini Keshavan
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Jonathan M Schott
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Imogen J Swift
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Carolin Heller
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Jonathan D Rohrer
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester M13 9PL, UK
- Department of Geriatric Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, 45147 Essen, Germany
- Department of Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, 45147 Essen, Germany
| | - Christopher Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Miles Chapman
- Neuroimmunology and CSF Laboratory, University College London Hospitals NHS Trust National Hospital of Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Michael P Lunn
- Neuroimmunology and CSF Laboratory, University College London Hospitals NHS Trust National Hospital of Neurology and Neurosurgery, London WC1N 3BG, UK
| | - Jan Bieschke
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Graham S Jackson
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- United Kingdom Dementia Research Institute at University College London, London WC1E 6BT, UK
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, S-43180 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792-2420, USA
| | - Byron Caughey
- Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT 59840, USA
| | - Peter Rudge
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - John Collinge
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
| | - Simon Mead
- Medical Research Council Prion Unit at University College London, UCL Institute of Prion Diseases, London W1W 7FF, UK
- NHS National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
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Coenen M, Kuijf HJ, Huenges Wajer IMC, Duering M, Wolters FJ, Fletcher EF, Maillard PM, Barkhof F, Barnes J, Benke T, Boomsma JMF, Chen CPLH, Dal-Bianco P, Dewenter A, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Groeneveld O, Hilal S, Hofer E, Koek DL, Maier AB, McCreary CR, Padilla CS, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Steketee RME, Sudre CH, van den Berg E, van der Flier WM, Venketasubramanian N, Vernooij MW, Xin X, DeCarli C, Biessels GJ, Biesbroek JM. Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients. Alzheimers Dement 2023; 19:2420-2432. [PMID: 36504357 DOI: 10.1002/alz.12827] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [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: 04/19/2022] [Revised: 09/07/2022] [Accepted: 09/13/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study. METHODS Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses. RESULTS WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains. DISCUSSION The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment. HIGHLIGHTS We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.
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Affiliation(s)
- Mirthe Coenen
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Irene M C Huenges Wajer
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Medical Image Analysis Center (MIAC) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frank J Wolters
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Evan F Fletcher
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Pauline M Maillard
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Frederik Barkhof
- Radiology & Nuclear Medicine, Amsterdam UMC, location Vrije Universiteit, Amsterdam, The Netherlands
- UCL Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Thomas Benke
- Clinic of Neurology, Medical University Innsbruck, Innsbruck, Austria
| | - Jooske M F Boomsma
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Christopher P L H Chen
- Department of Pharmacology, National University of Singapore, Singapore, Singapore
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | - Peter Dal-Bianco
- Department of Neurology, Medical University Vienna, Vienna, Austria
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Christian Enzinger
- Division of General Neurology, Department of Neurology, Medical University Graz, Graz, Austria
- Division of Neuroradiology, Interventional and Vascular Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Lieza G Exalto
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Onno Groeneveld
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Department of Neurology, Isala MS Centre, Isala Hospital, Meppel, The Netherlands
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore, Singapore
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Edith Hofer
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Dineke L Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Andrea B Maier
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
- Department of Medicine, National University of Singapore, Singapore, Singapore
| | - Cheryl R McCreary
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Catarina S Padilla
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - Janne M Papma
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Anna Rubinski
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Reinhold Schmidt
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Eric E Smith
- Department of Clinical Neurosciences and Radiology and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Rebecca M E Steketee
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Carole H Sudre
- MRC Unit for Lifelong Health and Ageing, the Centre for Medical Image Computing, UCL, London, UK
| | - Esther van den Berg
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Narayanaswamy Venketasubramanian
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
- Raffles Neuroscience Center, Raffles Hospital, Singapore, Singapore
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Xu Xin
- Department of Pharmacology, National University of Singapore, Singapore, Singapore
- Memory, Aging and Cognition Center, National University Health System, Singapore, Singapore
| | - Charles DeCarli
- Department of Neurology, University of California at Davis, Davis, California, USA
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
| | - J Matthijs Biesbroek
- Department of Neurology and Neurosurgery, UMC Utrecht, Brain Center, Utrecht, The Netherlands
- Department of Neurology, Diakonessenhuis Hospital, Utrecht, The Netherlands
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Weston PSJ, Coath W, Harris MJ, Malone IB, Dickson J, Aigbirhio FI, Cash DM, Zhang H, Schott JM. Cortical tau is associated with microstructural imaging biomarkers of neurite density and dendritic complexity in Alzheimer's disease. Alzheimers Dement 2023; 19:2750-2754. [PMID: 36932979 PMCID: PMC10614698 DOI: 10.1002/alz.13011] [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: 11/14/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 03/19/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD), hyperphosphorylated tau is closely associated with focal neurodegeneration, but the mechanism remains uncertain. METHODS We quantified cortical microstructure using neurite orientation dispersion and density imaging in 14 individuals with young onset AD. Diffusion tensor imaging measured mean diffusivity (MD). Amyloid beta and tau positron emission tomography were acquired and associations with microstructural measures were assessed. RESULTS When regional volume was adjusted for, in the medial temporal lobe there was a significant negative association between neurite density and tau (partial R2 = 0.56, p = 0.008) and between orientation dispersion and tau (partial R2 = 0.66, p = 0.002), but not between MD and tau. In a wider cortical composite, there was an association between orientation dispersion and tau (partial R2 = 0.43, p = 0.030), but not between other measures and tau. DISCUSSION Our findings are consistent with tau causing first dendritic pruning (reducing dispersion/complexity) followed by neuronal loss. Advanced magnetic resonance imaging (MRI) microstructural measures have the potential to provide information relating to underlying tau deposition.
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Affiliation(s)
- Philip S. J. Weston
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLUniversity College LondonLondonUK
| | - William Coath
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Matthew J. Harris
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Ian B. Malone
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - John Dickson
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - Franklin I. Aigbirhio
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - David M. Cash
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Jonathan M. Schott
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
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James SN, Chiou YJ, Fatih N, Needham LP, Schott JM, Richards M. Timing of physical activity across adulthood on later-life cognition: 30 years follow-up in the 1946 British birth cohort. J Neurol Neurosurg Psychiatry 2023; 94:349-356. [PMID: 36810321 PMCID: PMC10176405 DOI: 10.1136/jnnp-2022-329955] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 12/16/2022] [Indexed: 02/23/2023]
Abstract
BACKGROUND To assess how timing, frequency and maintenance of being physically active, spanning over 30 years in adulthood, is associated with later-life cognitive function. METHODS Participants (n=1417, 53% female) were from the prospective longitudinal cohort study, 1946 British birth cohort. Participation in leisure time physical activity was reported five times between ages 36 and 69, categorised into: not active (no participation in physical activity/month); moderately active (participated 1-4 times/month); most active (participated 5 or more times/month). Cognition at age 69 was assessed by tests of cognitive state (Addenbrooke's Cognitive Examination-III), verbal memory (word learning test) and processing speed (visual search speed). RESULTS Being physically active, at all assessments in adulthood, was associated with higher cognition at age 69. For cognitive state and verbal memory, the effect sizes were similar across all adult ages, and between those who were moderately and most physically active. The strongest association was between sustained cumulative physical activity and later-life cognitive state, in a dose-response manner. Adjusting for childhood cognition, childhood socioeconomic position and education largely attenuated these associations but results mainly remained significant at the 5% level. CONCLUSIONS Being physically active at any time in adulthood, and to any extent, is linked with higher later-life cognitive state, but lifelong maintenance of physical activity was most optimal. These relationships were partly explained by childhood cognition and education, but independent of cardiovascular and mental health and APOE-E4, suggestive of the importance of education on the lifelong impacts of physical activity.
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Affiliation(s)
- Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Yu-Jie Chiou
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Psychiatry, Chang Gung Memorial Hospital Kaohsiung Branch, Kaohsiung, Taiwan
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Nasri Fatih
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Louisa P Needham
- MRC Unit for Lifelong Health and Ageing 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, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
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30
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Needham LP, Lu K, Nicholas JM, Schott JM, Richards M, James SN. A comprehensive assessment of age at menopause with well-characterized cognition at 70 years: A population-based British birth cohort. Maturitas 2023; 170:31-38. [PMID: 36753872 DOI: 10.1016/j.maturitas.2023.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/23/2022] [Accepted: 01/10/2023] [Indexed: 01/29/2023]
Abstract
OBJECTIVES Associations between age at menopause and cognition post-menopause are examined to determine whether relationships are stronger for certain cognitive domains. STUDY DESIGN Women from the Medical Research Council National Survey of Health and Development and its neuroscience sub-study, Insight 46, were included if they had known age at menopause (self-reported via questionnaire) and complete cognitive outcome data at age 69 (n = 746) or at Insight 46 wave I (n = 197). Multivariable linear regression analyses adjusting for life course confounders were run; interactions with menopause type (natural/surgical) and APOE-ε4 status were examined; and the potential contribution of hormone therapy was assessed. MAIN OUTCOME MEASURES Cognitive measures were standardized Addenbrooke's Cognitive Examination - third edition total and sub-domain scores at age 69 (whole cohort) and Preclinical Alzheimer's Cognitive Composite total and sub-test scores at age ~70 (Insight 46). RESULTS Older age at menopause was associated with better performance across all outcomes, most strongly for the Addenbrooke's Cognitive Examination memory and visuospatial function sub-domains, and the Preclinical Alzheimer's Cognitive Composite digit-symbol substitution test and face-name associative memory examination sub-tests. Adjusting for early-life factors attenuated all effect estimates, driven by childhood cognition, and accounting for menopause type revealed negative confounding for some outcomes. No significant interactions with menopause type or APOE-ε4 status were detected. Further adjustment for hormone therapy did not meaningfully alter the estimated effects. CONCLUSIONS Older age at menopause is associated with better later-life cognitive performance, particularly for visual processing and associative learning and memory domains. Childhood cognition was an important contributor.
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Affiliation(s)
- Louisa P Needham
- MRC Unit for Lifelong Health and Ageing at UCL, 5th Floor, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom of Great Britain and Northern Ireland.
| | - Kirsty Lu
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom of Great Britain and Northern Ireland.
| | - Jennifer M Nicholas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom of Great Britain and Northern Ireland; Department of Medical Statistics, London School of Hygiene and Tropical Medicine, University of London, Keppel Street, London, WC1E 7HT, United Kingdom of Great Britain and Northern Ireland.
| | - Jonathan M Schott
- MRC Unit for Lifelong Health and Ageing at UCL, 5th Floor, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom of Great Britain and Northern Ireland; Dementia Research Centre, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom of Great Britain and Northern Ireland.
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, 5th Floor, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom of Great Britain and Northern Ireland.
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL, 5th Floor, 1-19 Torrington Pl, London WC1E 7HB, United Kingdom of Great Britain and Northern Ireland.
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31
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Coath W, Modat M, Cardoso MJ, Markiewicz PJ, Lane CA, Parker TD, Keshavan A, Buchanan SM, Keuss SE, Harris MJ, Burgos N, Dickson J, Barnes A, Thomas DL, Beasley D, Malone IB, Wong A, Erlandsson K, Thomas BA, Schöll M, Ourselin S, Richards M, Fox NC, Schott JM, Cash DM. Operationalizing the centiloid scale for [ 18F]florbetapir PET studies on PET/MRI. Alzheimers Dement (Amst) 2023; 15:e12434. [PMID: 37201176 PMCID: PMC10186069 DOI: 10.1002/dad2.12434] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/03/2023] [Accepted: 02/19/2023] [Indexed: 05/20/2023]
Abstract
INTRODUCTION The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI). METHODS We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian-mixture-modelling-derived cutpoints for Aβ PET positivity were converted. RESULTS The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM-based Centiloids. Linear adjustment produced a WM-based cutpoint of 18.1. DISCUSSION Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed. HIGHLIGHTS Centiloid conversion of amyloid beta positron emission tomography (PET) data aims to standardize results.Centiloid values can be influenced by differences in acquisition.We converted florbetapir PET/magnetic resonance imaging data from a large birth cohort.Whole cerebellum referenced values could be reliably transformed to Centiloids.White matter referenced values may be less generalizable between datasets.
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Affiliation(s)
- William Coath
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Marc Modat
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - M. Jorge Cardoso
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Pawel J. Markiewicz
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUCLLondonUK
| | | | - Thomas D. Parker
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Ashvini Keshavan
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Sarah M. Buchanan
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Sarah E. Keuss
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Matthew J. Harris
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Ninon Burgos
- Sorbonne Université, Institut du Cerveau ‐ Paris Brain Institute ‐ ICM, Inserm, CNRS, AP‐HP, Hôpital Pitié Salpêtrière, InriaAramis project‐teamParisFrance
| | - John Dickson
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - Anna Barnes
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - David L. Thomas
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Department of Brain Repair and RehabilitationUCL Queen Square Institute of NeurologyLondonUK
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Daniel Beasley
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Ian B. Malone
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCLLondonUK
| | - Kjell Erlandsson
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - Benjamin A. Thomas
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - Michael Schöll
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska AcademyUniversity of GothenburgMölndalSweden
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgMölndalSweden
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | | | - Nick C. Fox
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Dementia Research InstituteUCL Queen Square Institute of NeurologyLondonUK
| | | | - David M. Cash
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUCLLondonUK
- Dementia Research InstituteUCL Queen Square Institute of NeurologyLondonUK
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32
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Frisoni GB, Altomare D, Ribaldi F, Villain N, Brayne C, Mukadam N, Abramowicz M, Barkhof F, Berthier M, Bieler-Aeschlimann M, Blennow K, Brioschi Guevara A, Carrera E, Chételat G, Csajka C, Demonet JF, Dodich A, Garibotto V, Georges J, Hurst S, Jessen F, Kivipelto M, Llewellyn DJ, McWhirter L, Milne R, Minguillón C, Miniussi C, Molinuevo JL, Nilsson PM, Noyce A, Ranson JM, Grau-Rivera O, Schott JM, Solomon A, Stephen R, van der Flier W, van Duijn C, Vellas B, Visser LN, Cummings JL, Scheltens P, Ritchie C, Dubois B. Dementia prevention in memory clinics: recommendations from the European task force for brain health services. Lancet Reg Health Eur 2023; 26:100576. [PMID: 36895446 PMCID: PMC9989648 DOI: 10.1016/j.lanepe.2022.100576] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/09/2022] [Accepted: 12/15/2022] [Indexed: 02/04/2023]
Abstract
Observational population studies indicate that prevention of dementia and cognitive decline is being accomplished, possibly as an unintended result of better vascular prevention and healthier lifestyles. Population aging in the coming decades requires deliberate efforts to further decrease its prevalence and societal burden. Increasing evidence supports the efficacy of preventive interventions on persons with intact cognition and high dementia risk. We report recommendations for the deployment of second-generation memory clinics (Brain Health Services) whose mission is evidence-based and ethical dementia prevention in at-risk individuals. The cornerstone interventions consist of (i) assessment of genetic and potentially modifiable risk factors including brain pathology, and risk stratification, (ii) risk communication with ad-hoc protocols, (iii) risk reduction with multi-domain interventions, and (iv) cognitive enhancement with cognitive and physical training. A roadmap is proposed for concept validation and ensuing clinical deployment.
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Affiliation(s)
- Giovanni B. Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva Geneva, Switzerland
| | - Daniele Altomare
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva Geneva, Switzerland
| | - Federica Ribaldi
- Memory Center, Department of Rehabilitation and Geriatrics, University Hospitals and University of Geneva Geneva, Switzerland
| | - Nicolas Villain
- Institut de la Mémoire et de la Maladie d’Alzheimer, IM2A, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France
- Institut du Cerveau et de la Moelle Épinière, UMR-S975, INSERM, Paris, France
| | - Carol Brayne
- Cambridge Public Health, University of Cambridge, Cambridge, UK
| | - Naaheed Mukadam
- Division of Psychiatry, University College London, London, UK
| | - Marc Abramowicz
- Genetic Medicine, Diagnostics Dept, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Radiology & Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, the Netherlands
- Queen Square Institute of Neurology, University College London, London, UK
| | - Marcelo Berthier
- Unit of Cognitive Neurology and Aphasia, Centro de Investigaciones Médico-Sanitarias (CIMES), University of Malaga, Malaga, Spain
| | - Melanie Bieler-Aeschlimann
- Leenaards Memory Centre, Department of Clinical Neurosciences, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
- Infections Disease Service, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrea Brioschi Guevara
- Leenaards Memory Centre, Department of Clinical Neurosciences, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Emmanuel Carrera
- Stroke Center, Department of Clinical Neurosciences, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Gaël Chételat
- Normandie University, UNICAEN, INSERM, U1237, PhIND Physiopathology and Imaging of Neurological Disorders, Cyceron, Caen, France
| | - Chantal Csajka
- Center of Research and Innovation in Clinical Pharmaceutical Sciences, University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-François Demonet
- Leenaards Memory Centre, Department of Clinical Neurosciences, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
- French Clinical Research Infrastructure Network, INSERM, University Hospital of Toulouse, France
| | - Alessandra Dodich
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva and NIMTLab, University of Geneva, Geneva, Switzerland
| | | | - Samia Hurst
- Institute for Ethics, History, and the Humanities, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frank Jessen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Excellence Cluster Cellular Stress Responses in Aging-Related Diseases (CECAD), Medical Faculty, University of Cologne, Germany
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
- The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - David J. Llewellyn
- College of Medicine and Health, University of Exeter, UK
- Alan Turing Institute, Exeter, UK
| | - Laura McWhirter
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK
| | - Richard Milne
- Cambridge Public Health, University of Cambridge, Cambridge, UK
- Engagement and Society, Wellcome Connecting Science, Hinxton, UK
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Carlo Miniussi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
- Centre for Medical Sciences (CISMed), University of Trento, Rovereto, Italy
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck A/S, Denmark
| | - Peter M. Nilsson
- Department of Clinical Science, Lund University, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | - Alastair Noyce
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | | | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Alina Solomon
- The Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden
| | - Ruth Stephen
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Wiesje van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Bruno Vellas
- Gerontopole and Alzheimer's Disease Research and Clinical Center, Toulouse University Hospital, Toulouse, France
| | - Leonie N.C. Visser
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Jeffrey L. Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada, Las Vegas, NV, USA
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
- EQT Life Sciences, Amsterdam, the Netherlands
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d’Alzheimer, IM2A, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France
- Institut du Cerveau et de la Moelle Épinière, UMR-S975, INSERM, Paris, France
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33
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Green RE, Lord J, Scelsi MA, Xu J, Wong A, Naomi-James S, Handy A, Gilchrist L, Williams DM, Parker TD, Lane CA, Malone IB, Cash DM, Sudre CH, Coath W, Thomas DL, Keuss S, Dobson R, Legido-Quigley C, Fox NC, Schott JM, Richards M, Proitsi P. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease. Alzheimers Res Ther 2023; 15:38. [PMID: 36814324 PMCID: PMC9945600 DOI: 10.1186/s13195-023-01184-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 02/08/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß = - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß = - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.
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Affiliation(s)
- Rebecca E Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Marzia A Scelsi
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,Institute of Pharmaceutical Science, King's College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK
| | - Sarah Naomi-James
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Alex Handy
- University College London, Institute of Health Informatics, London, UK
| | - Lachlan Gilchrist
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Department of Brain Sciences, Imperial College London, London, W12 0NN, UK.,UK DRI Centre for Care Research and Technology, Imperial College London, London, W12 0BZ, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Carole H Sudre
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK.,MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK.,University College London, Institute of Health Informatics, London, UK.,Health Data Research UK London, University College London, London, UK.,NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK.,Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, 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, 8-11 Queen Square, London, WC1N 3BG, UK.
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.
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Yong KXX, Graff-Radford J, Ahmed S, Chapleau M, Ossenkoppele R, Putcha D, Rabinovici GD, Suarez-Gonzalez A, Schott JM, Crutch S, Harding E. Diagnosis and Management of Posterior Cortical Atrophy. Curr Treat Options Neurol 2023; 25:23-43. [PMID: 36820004 PMCID: PMC9935654 DOI: 10.1007/s11940-022-00745-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/10/2023]
Abstract
Purpose of review The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps. Recent findings Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer's disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies. Summary PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic - pharmacological and non-pharmacological - and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile - visual-spatial - rather than memory-led, predominantly young onset - and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.
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Affiliation(s)
- Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | | | - Samrah Ahmed
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire UK
| | - Marianne Chapleau
- Memory and Aging Center, University of California San Francisco, San Francisco, CA USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
| | - Gil D. Rabinovici
- Department of Neurology, Radiology, and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Sebastian Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Emma Harding
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
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35
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Schott JM. Not just neurological stamp collecting: when rare diagnoses lead to fundamental advances. Pract Neurol 2023; 23:98-99. [PMID: 36192134 DOI: 10.1136/pn-2022-003573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2022] [Indexed: 02/03/2023]
Affiliation(s)
- Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
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36
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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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Verdi S, Loreto F, Kia SM, Duvnjak A, Hakeem H, Perry RJ, Win Z, Patel N, Schott JM, Marquand AF, Malhotra PA, Cole JH. The heterogeneous amyloid‐positive brain: mapping individualised patterns of atrophy in amyloid‐positive Alzheimer’s disease patients using neuroanatomical normative models. Alzheimers Dement 2022. [DOI: 10.1002/alz.065489] [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: 12/24/2022]
Affiliation(s)
- Serena Verdi
- UCL London United Kingdom
- UCL Queen Square Institute of Neurology London United Kingdom
| | | | - Seyed Mostafa Kia
- Radboud University Nijmegen Netherlands
- University Medical Centre Utrecht Utrecht Netherlands
| | | | | | - Richard J Perry
- Imperial College London London United Kingdom
- Imperial College Healthcare NHS Trust London United Kingdom
| | - Zarni Win
- Imperial College Healthcare NHS Trust London United Kingdom
| | - Neva Patel
- Imperial College Healthcare NHS Trust London United Kingdom
| | - Jonathan M Schott
- UCL London United Kingdom
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Andre F Marquand
- Radboud University Nijmegen Netherlands
- Radboud University Medical Centre Nijmegen Netherlands
| | - Paresh A Malhotra
- Imperial College London London United Kingdom
- Imperial College Healthcare NHS Trust London United Kingdom
| | - James H Cole
- UCL London United Kingdom
- UCL Queen Square Institute of Neurology London United Kingdom
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Sweeney A, Passmore AP, Beverland D, McGuinness B, McAuley DF, Mawhinney T, Schott JM, Heslegrave A, Zetterberg H, Cunningham EL. Cerebrospinal Fluid Markers of Neurodegeneration Associated with Postoperative Delirium in an Older Elective Arthroplasty Population. Alzheimers Dement 2022. [DOI: 10.1002/alz.068131] [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: 12/24/2022]
Affiliation(s)
| | | | | | - Bernadette McGuinness
- Ageing Research Group, Centre for Public Health, Queen's University Belfast Belfast United Kingdom
| | | | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease and UK Dementia Research Institute, UCL Institute of Neurology, Queen Square London United Kingdom
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Holstege H, Hulsman M, Charbonnier C, Grenier-Boley B, Quenez O, Grozeva D, van Rooij JGJ, Sims R, Ahmad S, Amin N, Norsworthy PJ, Dols-Icardo O, Hummerich H, Kawalia A, Amouyel P, Beecham GW, Berr C, Bis JC, Boland A, Bossù P, Bouwman F, Bras J, Campion D, Cochran JN, Daniele A, Dartigues JF, Debette S, Deleuze JF, Denning N, DeStefano AL, Farrer LA, Fernández MV, Fox NC, Galimberti D, Genin E, Gille JJP, Le Guen Y, Guerreiro R, Haines JL, Holmes C, Ikram MA, Ikram MK, Jansen IE, Kraaij R, Lathrop M, Lemstra AW, Lleó A, Luckcuck L, Mannens MMAM, Marshall R, Martin ER, Masullo C, Mayeux R, Mecocci P, Meggy A, Mol MO, Morgan K, Myers RM, Nacmias B, Naj AC, Napolioni V, Pasquier F, Pastor P, Pericak-Vance MA, Raybould R, Redon R, Reinders MJT, Richard AC, Riedel-Heller SG, Rivadeneira F, Rousseau S, Ryan NS, Saad S, Sanchez-Juan P, Schellenberg GD, Scheltens P, Schott JM, Seripa D, Seshadri S, Sie D, Sistermans EA, Sorbi S, van Spaendonk R, Spalletta G, Tesi N, Tijms B, Uitterlinden AG, van der Lee SJ, Visser PJ, Wagner M, Wallon D, Wang LS, Zarea A, Clarimon J, van Swieten JC, Greicius MD, Yokoyama JS, Cruchaga C, Hardy J, Ramirez A, Mead S, van der Flier WM, van Duijn CM, Williams J, Nicolas G, Bellenguez C, Lambert JC. Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer's disease. Nat Genet 2022; 54:1786-1794. [PMID: 36411364 PMCID: PMC9729101 DOI: 10.1038/s41588-022-01208-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 09/19/2022] [Indexed: 11/22/2022]
Abstract
Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.
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Affiliation(s)
- Henne Holstege
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands.
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands.
| | - Marc Hulsman
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands.
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands.
| | - Camille Charbonnier
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France
| | - Benjamin Grenier-Boley
- Université Lille, INSERM, Centre Hospitalier Universitaire Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
| | - Olivier Quenez
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France
| | - Detelina Grozeva
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Jeroen G J van Rooij
- Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Rebecca Sims
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
- Leiden Academic Centre for Drug Research, Leiden, the Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
- Nuffield Department of Population Health Oxford University, Oxford, UK
| | - Penny J Norsworthy
- Medical Research Council Prion Unit at University College London, University College London Institute of Prion Diseases, London, UK
| | - Oriol Dols-Icardo
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Biomedical Research Networking Center on Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Holger Hummerich
- Medical Research Council Prion Unit at University College London, University College London Institute of Prion Diseases, London, UK
| | - Amit Kawalia
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philippe Amouyel
- Université Lille, INSERM, Centre Hospitalier Universitaire Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Claudine Berr
- Université Montpellier, INSERM, Institute for Neurosciences of Montpellier, Montpellier, France
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Anne Boland
- Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Centre National de Recherche en Génomique Humaine Evry, Gif-sur-Yvette, France
| | - Paola Bossù
- Experimental Neuro-psychobiology Laboratory, Department of Clinical and Behavioral Neurology, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Femke Bouwman
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Jose Bras
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
| | - Dominique Campion
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France
| | | | - Antonio Daniele
- Department of Neuroscience, Catholic University of Sacred Heart, Fondazione Policlinico Universitario A. Gemelli Istituto di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | | | - Stéphanie Debette
- Université Bordeaux, INSERM, Bordeaux Population Health Research Center, Bordeaux, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| | - Jean-François Deleuze
- Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Centre National de Recherche en Génomique Humaine Evry, Gif-sur-Yvette, France
| | - Nicola Denning
- UKDRI Cardiff, School of Medicine, Cardiff University, Cardiff, UK
| | - Anita L DeStefano
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Lindsay A Farrer
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University, Boston, MA, USA
| | - Maria Victoria Fernández
- Neurogenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Psychiatry Department, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Nick C Fox
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Daniela Galimberti
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Ca' Granda, Ospedale Policlinico, Milan, Italy
- University of Milan, Milan, Italy
| | - Emmanuelle Genin
- Université Brest, INSERM, Etablissement Français du Sang, Centre Hospitalier Universitaire Brest, Unité Mixte de Recherche 1078, GGB, Brest, France
| | - Johan J P Gille
- Genome Diagnostics, Department of Human Genetics, VU University, AmsterdamUMC (location VUmc), Amsterdam, the Netherlands
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Rita Guerreiro
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI, USA
| | - Jonathan L Haines
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Clive Holmes
- Clinical and Experimental Science, Faculty of Medicine, University of Southampton, Southampton, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Iris E Jansen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije University, Amsterdam, the Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Marc Lathrop
- McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Alberto Lleó
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Biomedical Research Networking Center on Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Lauren Luckcuck
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Marcel M A M Mannens
- Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands
| | - Rachel Marshall
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Eden R Martin
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Carlo Masullo
- Institute of Neurology, Catholic University of the Sacred Heart, Rome, Italy
| | - Richard Mayeux
- Taub Institute on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University, New York, NY, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
| | - Patrizia Mecocci
- Institute of Gerontology and Geriatrics, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Alun Meggy
- UKDRI Cardiff, School of Medicine, Cardiff University, Cardiff, UK
| | - Merel O Mol
- Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Kevin Morgan
- Human Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Adam C Naj
- Penn Neurodegeneration Genomics Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Valerio Napolioni
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
- Genomic and Molecular Epidemiology Laboratory, School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Florence Pasquier
- Université Lille, INSERM, Centre Hospitalier Universitaire Lille, UMR1172, Resources and Research Memory Center (MRRC) of Distalz, Licend, Lille, France
| | - Pau Pastor
- Fundació Docència i Recerca MútuaTerrassa and Movement Disorders Unit, Department of Neurology, University Hospital MútuaTerrassa, Barcelona, Spain
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Barcelona, Spain
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, USA
| | - Rachel Raybould
- UKDRI Cardiff, School of Medicine, Cardiff University, Cardiff, UK
| | - Richard Redon
- Université de Nantes, Centre Hospitalier Universitaire Nantes, Centre National de la Recherche Scientifique, INSERM, l'institut du Thorax, Nantes, France
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Anne-Claire Richard
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Stéphane Rousseau
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France
| | - Natalie S Ryan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Salha Saad
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Pascual Sanchez-Juan
- Biomedical Research Networking Center on Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander, Spain
| | - Gerard D Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Jonathan M Schott
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Davide Seripa
- Laboratory for Advanced Hematological Diagnostics, Department of Hematology and Stem Cell Transplant, Lecce, Italy
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Daoud Sie
- Genome Diagnostics, Department of Human Genetics, VU University, AmsterdamUMC (location VUmc), Amsterdam, the Netherlands
| | - Erik A Sistermans
- Genome Diagnostics, Department of Human Genetics, VU University, AmsterdamUMC (location VUmc), Amsterdam, the Netherlands
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Resie van Spaendonk
- Genome Diagnostics, Department of Human Genetics, VU University, AmsterdamUMC (location VUmc), Amsterdam, the Netherlands
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Niccolo' Tesi
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Betty Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Sven J van der Lee
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Michael Wagner
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - David Wallon
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Neurology and CNRMAJ, Rouen, France
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Aline Zarea
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Neurology and CNRMAJ, Rouen, France
| | - Jordi Clarimon
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Biomedical Research Networking Center on Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - John C van Swieten
- Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Carlos Cruchaga
- Neurogenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Psychiatry Department, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - John Hardy
- Reta Lila Weston Research Laboratories, Department of Molecular Neuroscience, University College London Institute of Neurology, London, UK
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany
| | - Simon Mead
- Medical Research Council Prion Unit at University College London, University College London Institute of Prion Diseases, London, UK
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, the Netherlands
- Nuffield Department of Population Health Oxford University, Oxford, UK
| | - Julie Williams
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics,, Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | - Gaël Nicolas
- Université Rouen Normandie, INSERM U1245 and CHU Rouen, Department of Genetics and CNRMAJ, Rouen, France.
| | - Céline Bellenguez
- Université Lille, INSERM, Centre Hospitalier Universitaire Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
| | - Jean-Charles Lambert
- Université Lille, INSERM, Centre Hospitalier Universitaire Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.
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Keuss SE, Cash DM, Nicholas JM, Parker TD, Lane CA, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris MJ, Lu K, James S, Street RE, Barnes J, Malone IB, Sudre CH, Thomas DL, Dickson J, Murray‐Smith H, Freiberger T, Wong A, Crutch SJ, Richards M, Fox NC, Schott JM, Coath W. Rates of cortical thinning in Alzheimer’s disease signature regions: pathological influences and cognitive consequences in members of the 1946 British birth cohort. Alzheimers Dement 2022. [DOI: 10.1002/alz.067336] [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: 12/24/2022]
Affiliation(s)
- Sarah E Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - David M Cash
- Institute of Neurology, University 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
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
- UK DRI Centre for Care Research and Technology, Imperial College London London United Kingdom
| | - Christopher A Lane
- 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
| | - Aaron Z Wagen
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Mathew Storey
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Matthew J Harris
- 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
| | - Sarah‐Naomi James
- MRC Unit for Lifelong Health and Ageing at UCL London United Kingdom
| | - Rebecca E Street
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Jo Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Carole H Sudre
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
- School of Biomedical Engineering and Imaging Sciences, King’s College London London United Kingdom
- Centre for Medical Image Computing, University College London London United Kingdom
- MRC Unit for Lifelong Health and Ageing at UCL, University College London London United Kingdom
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
- Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology London United Kingdom
| | - John Dickson
- UCL Institute of Nuclear Medicine London United Kingdom
| | - Heidi Murray‐Smith
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Tamar Freiberger
- 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
| | - Sebastian J Crutch
- 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
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
- UK Dementia Research Institute, UCL London United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
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Sweeney A, Passmore AP, Beverland D, McGuinness B, McAuley DF, Mawhinney T, O'Brien S, Schott JM, Heslegrave A, Zetterberg H, Cunningham EL. Plasma Markers of Neurodegeneration Associated with Postoperative Delirium in an Older Elective Arthroplasty Population. Alzheimers Dement 2022. [DOI: 10.1002/alz.068193] [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: 12/24/2022]
Affiliation(s)
| | | | | | - Bernadette McGuinness
- Ageing Research Group, Centre for Public Health, Queen's University Belfast Belfast United Kingdom
| | | | | | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Amanda Heslegrave
- UCL Queen Square Institute of Neurology London United Kingdom
- UK Dementia Research Institute at UCL London United Kingdom
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease and UK Dementia Research Institute, UCL Institute of Neurology, Queen Square London United Kingdom
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg Gothenburg Sweden
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Abdi Z, Yong KXX, Crutch SJ, Schott JM, Lashley T. Neuroinflammation in posterior cortical atrophy and typical Alzheimer’s disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.063826] [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: 12/24/2022]
Affiliation(s)
- Zeinab Abdi
- Queen Square Institute of Neurology, University College London London United Kingdom
| | - Keir X X Yong
- UCL Institute of Neurology London United Kingdom
- University College London London United Kingdom
| | - Sebastian J Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | | | - Tammaryn Lashley
- University College London, Queen Square Institute of Neurology London United Kingdom
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Chiou Y, Schott JM, Richards M, James S. How timings of being physically active in adulthood relate to later‐life cognition: over 30 years of follow up in the 1946 British Birth Cohort. Alzheimers Dement 2022. [DOI: 10.1002/alz.065712] [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: 12/24/2022]
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44
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Sweeney A, Passmore AP, Beverland D, McGuinness B, McAuley DF, Mawhinney T, O'Brien S, Schott JM, Heslegrave A, Zetterberg H, Cunningham EL. Preoperative Cerebrospinal Fluid and Plasma Markers of Inflammation and Neurodegeneration Predict Mortality Eight Years Later in an Observational Cohort Study of Postoperative delirium in an Older Elective Arthroplasty Populatio. Alzheimers Dement 2022. [DOI: 10.1002/alz.068179] [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: 12/24/2022]
Affiliation(s)
| | | | | | - Bernadette McGuinness
- Ageing Research Group, Centre for Public Health, Queen's University Belfast Belfast United Kingdom
| | | | | | | | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease and UK Dementia Research Institute, UCL Institute of Neurology, Queen Square London United Kingdom
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg Gothenburg Sweden
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Graham NSN, Cole JH, Schott JM, Sharp DJ. Distinct patterns of neurodegeneration after TBI and in Alzheimer’s disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.064274] [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: 12/24/2022]
Affiliation(s)
- Neil SN Graham
- Imperial College London London United Kingdom
- UK Dementia Research Institute Centre for Care Research and Technology London United Kingdom
| | - James H Cole
- Centre of Medical Image Computing, UCL Department of Medical Physics London United Kingdom
- UCL Queen Square Institute of Neurology London United Kingdom
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - David J Sharp
- Imperial College London London United Kingdom
- UK Dementia Research Institute Centre for Care Research and Technology London United Kingdom
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46
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Verdi S, Kia SM, Schott JM, Marquand AF, Cole JH. Mapping individualised patterns of atrophy in Alzheimer’s disease using neuroanatomical normative models. Alzheimers Dement 2022. [DOI: 10.1002/alz.060306] [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: 12/24/2022]
Affiliation(s)
- Serena Verdi
- UCL Queen Square Institute of Neurology London United Kingdom
- UCL London United Kingdom
| | - Seyed Mostafa Kia
- Radboud University Nijmegen Netherlands
- University Medical Centre Utrecht Utrecht Netherlands
| | - Jonathan M Schott
- UCL London United Kingdom
- Dementia Research Centre, UCL Queen Square Institute of Neurology London United Kingdom
| | - Andre F Marquand
- Radboud University Nijmegen Netherlands
- Radboud University Medical Centre Nijmegen Netherlands
| | - James H Cole
- UCL Queen Square Institute of Neurology London United Kingdom
- UCL London United Kingdom
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Hansson K, Dahlén R, Hansson O, Pernevik E, Paterson R, Schott JM, Magdalinou N, Zetterberg H, Blennow K, Gobom J. Corrigendum to “Use of the tau protein-to-peptide ratio in CSF to improve diagnostic classification of Alzheimer’s disease” [Clin. Mass Spectrom. 14 (Part B) (2019) 74–82]. J Mass Spectrom Adv Clin Lab 2022; 26:35. [PMID: 36187744 PMCID: PMC9523399 DOI: 10.1016/j.jmsacl.2022.08.002] [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] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Affiliation(s)
- Karl Hansson
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Rahil Dahlén
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Elin Pernevik
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Ross Paterson
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | | | - Nadia Magdalinou
- Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, Queen Square, London, UK
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Johan Gobom
- Institute of Neuroscience and Physiology, Department of Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Corresponding author at: Institute of Neuroscience and Physiology, Department of Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, 431 80 Mölndal, Sweden.
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Zetterberg H, Schott JM. Objectifying Subjective Cognitive Decline: The Prognostic Role of Alzheimer Biomarkers. Neurology 2022; 99:735-736. [PMID: 36240103 DOI: 10.1212/wnl.0000000000201172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 07/13/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- Henrik Zetterberg
- From the Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z., J.M.S.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z., J.M.S.), London; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, China; and Dementia Research Centre (J.M.S.), Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom.
| | - Jonathan M Schott
- From the Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease (H.Z., J.M.S.), UCL Institute of Neurology, Queen Square; UK Dementia Research Institute at UCL (H.Z., J.M.S.), London; Hong Kong Center for Neurodegenerative Diseases (H.Z.), Clear Water Bay, China; and Dementia Research Centre (J.M.S.), Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
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49
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Delaby C, Teunissen CE, Blennow K, Alcolea D, Arisi I, Amar EB, Beaume A, Bedel A, Bellomo G, Bigot‐Corbel E, Bjerke M, Blanc‐Quintin M, Boada M, Bousiges O, Chapman MD, DeMarco ML, D'Onofrio M, Dumurgier J, Dufour‐Rainfray D, Engelborghs S, Esselmann H, Fogli A, Gabelle A, Galloni E, Gondolf C, Grandhomme F, Grau‐Rivera O, Hart M, Ikeuchi T, Jeromin A, Kasuga K, Keshavan A, Khalil M, Körtvelyessy P, Kulczynska‐Przybik A, Laplanche J, Lewczuk P, Li Q, Lleó A, Malaplate C, Marquié M, Masters CL, Mroczko B, Nogueira L, Orellana A, Otto M, Oudart J, Paquet C, Paoletti FP, Parnetti L, Perret‐Liaudet A, Peoc'h K, Poesen K, Puig‐Pijoan A, Quadrio I, Quillard‐Muraine M, Rucheton B, Schraen S, Schott JM, Shaw LM, Suárez‐Calvet M, Tsolaki M, Tumani H, Udeh‐Momoh CT, Vaudran L, Verbeek MM, Verde F, Vermunt L, Vogelgsang J, Wiltfang J, Zetterberg H, Lehmann S. Clinical reporting following the quantification of cerebrospinal fluid biomarkers in Alzheimer's disease: An international overview. Alzheimers Dement 2022; 18:1868-1879. [PMID: 34936194 PMCID: PMC9787404 DOI: 10.1002/alz.12545] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 10/11/2021] [Accepted: 10/25/2021] [Indexed: 01/28/2023]
Abstract
INTRODUCTION The current practice of quantifying cerebrospinal fluid (CSF) biomarkers as an aid in the diagnosis of Alzheimer's disease (AD) varies from center to center. For a same biochemical profile, interpretation and reporting of results may differ, which can lead to misunderstandings and raises questions about the commutability of tests. METHODS We obtained a description of (pre-)analytical protocols and sample reports from 40 centers worldwide. A consensus approach allowed us to propose harmonized comments corresponding to the different CSF biomarker profiles observed in patients. RESULTS The (pre-)analytical procedures were similar between centers. There was considerable heterogeneity in cutoff definitions and report comments. We therefore identified and selected by consensus the most accurate and informative comments regarding the interpretation of CSF biomarkers in the context of AD diagnosis. DISCUSSION This is the first time that harmonized reports are proposed across worldwide specialized laboratories involved in the biochemical diagnosis of AD.
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Affiliation(s)
- Constance Delaby
- LBPC‐PPCUniv MontpellierCHU MontpellierINSERMMontpellierFrance,Hospital de la Santa Creu i Sant Pau ‐ Biomedical Research Institute Sant Pau ‐ Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Charlotte E. Teunissen
- Neurochemistry LabDepartment of Clinical ChemistryAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Kaj Blennow
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
| | - Daniel Alcolea
- Hospital de la Santa Creu i Sant Pau ‐ Biomedical Research Institute Sant Pau ‐ Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Ivan Arisi
- European Brain Research Institute (EBRI) “Rita Levi‐Montalcini”RomaItaly
| | - Elodie Bouaziz Amar
- Université de ParisCognitive Neurology CenterGHU APHP Nord Lariboisière Fernand‐Widal HospitalParisFrance
| | | | | | - Giovanni Bellomo
- Lab of Clinical NeurochemistrySection of NeurologyDept. of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | | | - Maria Bjerke
- Vrije Universiteit BrusselCenter for Neurosciences and Department of Clinical BiologyClinical Neurochemistry LaboratoryUniversitair Ziekenhuis BrusselBrusselsBelgium,Department of Biomedical Sciences, Institute Born‐BungeUniversity of AntwerpAntwerpBelgium
| | | | - Mercè Boada
- Research Center and Memory ClinicFundació ACEInstitut Català de Neurociències Aplicades and Universitat Internacional de Catalunya (UIC)BarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Olivier Bousiges
- Laboratoire de Biochimie et Biologie Moléculaire, et CNRSICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg)Team IMISHôpitaux Universitaires de StrasbourgStrasbourgFrance
| | - Miles D Chapman
- Department of NeuroimmunologyNational Hospital for Neurology and Neurosurgery, UCL Queen SquareLondonUK
| | - Mari L. DeMarco
- Department of Pathology and Laboratory MedicineSt. Paul's Hospital, Providence Health Care, Vancouver, Canada & Department of Pathology & Laboratory MedicineUniversity of British ColumbiaVancouverCanada
| | - Mara D'Onofrio
- European Brain Research Institute (EBRI) “Rita Levi‐Montalcini”RomaItaly
| | - Julien Dumurgier
- Université de ParisCognitive Neurology CenterGHU APHP Nord Lariboisière Fernand‐Widal HospitalParisFrance
| | | | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, Institute Born‐BungeUniversity of AntwerpAntwerpBelgium,Vrije Universiteit BrusselUniversitair Ziekenhuis BrusselCenter for Neurosciences and Department of NeurologyBrusselsBelgium
| | - Hermann Esselmann
- Department of Psychiatry and PsychotherapyUniversity Medical Center Goettingen (UMGGoettingenGermany
| | - Anne Fogli
- CHU Clermont‐FerrandClermont‐FerrandFrance
| | - Audrey Gabelle
- LBPC‐PPCUniv MontpellierCHU MontpellierINSERMMontpellierFrance
| | | | | | | | - Oriol Grau‐Rivera
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain,Servei de NeurologiaHospital del MarUnitat de deteriorament cognitiu i transtorns del movimentBarcelonaSpain,IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Melanie Hart
- Department of NeuroimmunologyNational Hospital for Neurology and Neurosurgery, UCL Queen SquareLondonUK
| | - Takeshi Ikeuchi
- Dept. of Molecular GeneticsCenter for BioresourcesBrain Research InstituteNiigata UniversityNiigataJapan
| | | | - Kensaku Kasuga
- Dept. of Molecular GeneticsCenter for BioresourcesBrain Research InstituteNiigata UniversityNiigataJapan
| | - Ashvini Keshavan
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | | | - Peter Körtvelyessy
- Freie Universität Berlin and Humboldt‐Universität zu BerlinDepartment of NeurologyGerman Center for Neurodegenerative Diseases, Magdeburg, Germany and Charité‐Universitäts medizin BerlinBerlinGermany
| | | | - Jean‐Louis Laplanche
- Université de ParisCognitive Neurology CenterGHU APHP Nord Lariboisière Fernand‐Widal HospitalParisFrance
| | - Piotr Lewczuk
- Department of Neurodegeneration DiagnosticsMedical University of BialystokBialystokPoland,Lab for Clinical Neurochemistry and Neurochemical Dementia DiagnosticsUniversitätsklinikum Erlangen and Friedrich‐Alexander Universität Erlangen‐NürnbergErlangenGermany
| | - Qiao‐Xin Li
- Florey Institute and The University of MelbourneMelbourneVictoriaAustralia
| | - Alberto Lleó
- Hospital de la Santa Creu i Sant Pau ‐ Biomedical Research Institute Sant Pau ‐ Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Catherine Malaplate
- CHRU de NancyLaboratoire de BiochimieBiologie Moléculaire et Nutrition/ Université de LorraineNancyFrance
| | - Marta Marquié
- Research Center and Memory ClinicFundació ACEInstitut Català de Neurociències Aplicades and Universitat Internacional de Catalunya (UIC)BarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Colin L. Masters
- Florey Institute and The University of MelbourneMelbourneVictoriaAustralia
| | - Barbara Mroczko
- Department of Neurodegeneration DiagnosticsMedical University of BialystokBialystokPoland
| | - Léonor Nogueira
- Laboratoire de Biologie Cellulaire et CytologieCHU PURPANToulouseFrance
| | - Adelina Orellana
- Research Center and Memory ClinicFundació ACEInstitut Català de Neurociències Aplicades and Universitat Internacional de Catalunya (UIC)BarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Markus Otto
- Department of Neurology and CSF LaboratoryUniversity of UlmUlmGermany
| | | | - Claire Paquet
- Université de ParisCognitive Neurology CenterGHU APHP Nord Lariboisière Fernand‐Widal HospitalParisFrance
| | - Federico Paolini Paoletti
- Lab of Clinical NeurochemistrySection of NeurologyDept. of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | - Lucilla Parnetti
- Lab of Clinical NeurochemistrySection of NeurologyDept. of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | - Armand Perret‐Liaudet
- Lyon Neuroscience Research Center BIORAN Team ‐ CNRS UMR 5292INSERM U1028Lyon University HospitalLyonFrance
| | - Katell Peoc'h
- Université de Paris GHU APHP Nord Beaujon HospitalParisFrance
| | - Koen Poesen
- Laboratory for Molecular Neurobiomarker Research (LaMoN)Department of NeurosciencesKU LeuvenLeuven Brain InstituteLeuvenBelgium
| | - Albert Puig‐Pijoan
- Servei de NeurologiaHospital del MarUnitat de deteriorament cognitiu i transtorns del movimentBarcelonaSpain,IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Isabelle Quadrio
- Lyon Neuroscience Research Center BIORAN Team ‐ CNRS UMR 5292INSERM U1028Lyon University HospitalLyonFrance
| | - Muriel Quillard‐Muraine
- UNIROUENRouen University HospitalDepartment of Clinical biologyBiochemistry laboratoryNormandie UnivRouenFrance
| | | | - Susanna Schraen
- InsermCHU LilleU1172‐LilNCogLICENDLabEx DISTALZUniversité de LilleLilleFrance
| | | | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine HospitalUniversity of PennsylvaniaPennsylvaniaUSA
| | - Marc Suárez‐Calvet
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain,Servei de NeurologiaHospital del MarUnitat de deteriorament cognitiu i transtorns del movimentBarcelonaSpain,IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Magda Tsolaki
- 1st Department of NeurologySchool of MedicineFaculty of Health of SciencesAristotle University of ThessalonikiThessalonikiGreece
| | - Hayrettin Tumani
- Department of Neurology and CSF LaboratoryUniversity of UlmUlmGermany
| | | | | | - Marcel M Verbeek
- Donders Institute for Brain, Cognition and BehaviourRadboud Alzheimer CentreDepartments of Neurology and Laboratory MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Federico Verde
- Department of Neurology ‐ Stroke Unit and Laboratory of NeuroscienceIRCCS Istituto Auxologico ItalianoMilanItaly,Department of Pathophysiology and Transplantation“Dino Ferrari” Center, Università degli Studi di MilanoMilanItaly
| | - Lisa Vermunt
- Neurochemistry LabDepartment of Clinical ChemistryAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Jonathan Vogelgsang
- Department of Psychiatry and PsychotherapyUniversity Medical Center Goettingen (UMGGoettingenGermany,McLean HospitalTranslational Neuroscience LaboratoryHarvard Medical SchoolBelmontMassachusettsUSA
| | - Jens Wiltfang
- Department of Psychiatry and PsychotherapyUniversity Medical Center Goettingen (UMGGoettingenGermany,German Center for Neurodegenerative Diseases (DZNE)GoettingenGermany,Neurosciences and Signaling GroupInstitute of Biomedicine (iBiMED)Department of Medical SciencesUniversity of AveiroAveiroPortugal
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden,Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden,UK Dementia Research Institute at UCLLondonUK,Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
| | - Sylvain Lehmann
- LBPC‐PPCUniv MontpellierCHU MontpellierINSERMMontpellierFrance
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50
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Bowman EML, Cardwell C, McAuley DF, McGuinness B, Passmore AP, Beverland D, Zetterberg H, Schott JM, Cunningham EL. Factors influencing resilience to postoperative delirium in adults undergoing elective orthopaedic surgery. Br J Surg 2022; 109:908-911. [PMID: 35707934 PMCID: PMC10364747 DOI: 10.1093/bjs/znac197] [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] [Received: 02/23/2022] [Revised: 04/15/2022] [Accepted: 05/13/2022] [Indexed: 01/18/2023]
Affiliation(s)
- Emily M L Bowman
- Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences, Belfast, UK
| | - Christopher Cardwell
- Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences, Belfast, UK
| | - Daniel F McAuley
- Centre for Experimental Medicine, Queen's University Belfast, Wellcome-Wolfson Institute for Experimental Medicine, Belfast, UK
| | - Bernadette McGuinness
- Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences, Belfast, UK
| | - Anthony P Passmore
- Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences, Belfast, UK
| | - David Beverland
- Outcomes Assessment Unit, Musgrave Park Hospital, Belfast Trust, Belfast, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, London, UK.,Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, London, UK.,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
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, London, UK
| | - Emma L Cunningham
- Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences, Belfast, UK
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