251
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Mattsson N, Groot C, Jansen WJ, Landau SM, Villemagne VL, Engelborghs S, Mintun MM, Lleo A, Molinuevo JL, Jagust WJ, Frisoni GB, Ivanoiu A, Chételat G, Resende de Oliveira C, Rodrigue KM, Kornhuber J, Wallin A, Klimkowicz-Mrowiec A, Kandimalla R, Popp J, Aalten PP, Aarsland D, Alcolea D, Almdahl IS, Baldeiras I, van Buchem MA, Cavedo E, Chen K, Cohen AD, Förster S, Fortea J, Frederiksen KS, Freund-Levi Y, Gill KD, Gkatzima O, Grimmer T, Hampel H, Herukka SK, Johannsen P, van Laere K, de Leon MJ, Maier W, Marcusson J, Meulenbroek O, Møllergård HM, Morris JC, Mroczko B, Nordlund A, Prabhakar S, Peters O, Rami L, Rodríguez-Rodríguez E, Roe CM, Rüther E, Santana I, Schröder J, Seo SW, Soininen H, Spiru L, Stomrud E, Struyfs H, Teunissen CE, Verhey FRJ, Vos SJB, van Waalwijk van Doorn LJC, Waldemar G, Wallin ÅK, Wiltfang J, Vandenberghe R, Brooks DJ, Fladby T, Rowe CC, Drzezga A, Verbeek MM, Sarazin M, Wolk DA, Fleisher AS, Klunk WE, Na DL, Sánchez-Juan P, Lee DY, Nordberg A, Tsolaki M, Camus V, Rinne JO, Fagan AM, Zetterberg H, Blennow K, Rabinovici GD, Hansson O, van Berckel BNM, van der Flier WM, Scheltens P, Visser PJ, Ossenkoppele R. Prevalence of the apolipoprotein E ε4 allele in amyloid β positive subjects across the spectrum of Alzheimer's disease. Alzheimers Dement 2018; 14:913-924. [PMID: 29601787 DOI: 10.1016/j.jalz.2018.02.009] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 12/28/2017] [Accepted: 02/07/2018] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid β (Aβ) pathology. METHODS We included 3451 Aβ+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location. RESULTS The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aβ+ cognitively normal and Aβ+ mild cognitive impairment (P < .05) but not in Aβ+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education. DISCUSSION The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aβ pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.
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Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden.
| | - Colin Groot
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Willemijn J Jansen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Victor L Villemagne
- Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | | | - Alberto Lleo
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - José Luis Molinuevo
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE- Laboratory of Neuroimaging of Aging, University Hospitals, and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Adrian Ivanoiu
- Memory Clinic and Neurochemistry Laboratory, Saint Luc University Hospital, Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Gaël Chételat
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | - Catarina Resende de Oliveira
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Karen M Rodrigue
- Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University of Erlangen- Nuremberg, Erlangen, Germany
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | | | - Ramesh Kandimalla
- Department of Biochemistry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Julius Popp
- Department of Psychiatry, Service of Old Age Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pauline P Aalten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Dag Aarsland
- Center for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Daniel Alcolea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - Ina S Almdahl
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Inês Baldeiras
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Mark A van Buchem
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Enrica Cavedo
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Paris, France
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Ann D Cohen
- University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA
| | - Stefan Förster
- Department of Nuclear Medicine, Technische Universitaet München, Munich, Germany
| | - Juan Fortea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - Kristian S Frederiksen
- Danish Dementia Research Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Department of Geriatrics, Karolinska University Hospital Huddinge, Section of Clinical Geriatrics, Institution of NVS, Karolinska Institutet, Stockholm, Sweden
| | - Kiran Dip Gill
- Department of Biochemistry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Olymbia Gkatzima
- Third Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar der Technischen Universitaet München, Munich, Germany
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Paris, France; Department of Psychiatry, Alzheimer Memorial Center and Geriatric Psychiatry Branch, Ludwig-Maximilian University, Munich, Germany
| | - Sanna-Kaisa Herukka
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Peter Johannsen
- Memory Clinic, Danish Dementia Research Center, Rigshospitalet, Copenhagen, Denmark
| | - Koen van Laere
- Department of Imaging and Pathology, Catholic University Leuven, Leuven, Belgium
| | - Mony J de Leon
- School of Medicine, Center for Brain Health, New York University, New York, NY, USA
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Jan Marcusson
- Geriatric Medicine, Department of Clinical and Experimental Medicine, University of Linköping, Linköping, Sweden
| | - Olga Meulenbroek
- Department of Geriatric Medicine, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Hanne M Møllergård
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Barbara Mroczko
- Department of Neurodegeneration Diagnostics, Leading National Research Centre in Białystok (KNOW), Medical University of Białystok, Białystok, Poland
| | - Arto Nordlund
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - Sudesh Prabhakar
- Department of Neurology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Oliver Peters
- Department of Psychiatry and Psychotherapy, Charité Berlin, German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Lorena Rami
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | - Eloy Rodríguez-Rodríguez
- Neurology Service, Universitary Hospital Marqués de Valdecilla, CIBERNED, IDIVAL, Santander, Spain
| | - Catherine M Roe
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Eckart Rüther
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Isabel Santana
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Johannes Schröder
- Sektion Gerontopsychiatrie, Universität Heidelberg, Heidelberg, Germany
| | - Sang W Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hilkka Soininen
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Luiza Spiru
- Department of Geriatrics-Gerontology-Gerontopsychiatry, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Erik Stomrud
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Charlotte E Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Frans R J Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Linda J C van Waalwijk van Doorn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Gunhild Waldemar
- Danish Dementia Research Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Åsa K Wallin
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology and Alzheimer Research Centre KU Leuven, Catholic University Leuven, Leuven, Belgium
| | - David J Brooks
- Division of Neuroscience, Medical Research Council Clinical Sciences Centre, Imperial College London, London, UK
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Christopher C Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
| | - Alexander Drzezga
- Department of Nuclear Medicine, University of Cologne, Cologne, Germany
| | - Marcel M Verbeek
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Marie Sarazin
- Neurologie de la Mémoire et du Langage, Centre Hospitalier Sainte-Anne, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam S Fleisher
- Banner Alzheimer's Institute, Phoenix, AZ, USA; Eli Lilly, Indianapolis, IN, USA; Department of Neurosciences, University of California, San Diego, CA, USA
| | - William E Klunk
- University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Pascual Sánchez-Juan
- Neurology Service, Universitary Hospital Marqués de Valdecilla, CIBERNED, IDIVAL, Santander, Spain
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University, College of Medicine, Seoul, South Korea
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Geriatric Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Magda Tsolaki
- Third Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vincent Camus
- CHRU de Tours, CIC INSERM 1415, INSERM U930, Université François Rabelais de Tours, Tours, France
| | - Juha O Rinne
- Turku PET Centre and Division of Clinical Neurosciences Turku, University of Turku and Turku University Hospital, Turku, Finland
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute, London, UK; Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Sweden and Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Sweden and Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Pieter Jelle Visser
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden; Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.
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252
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Chung JK, Plitman E, Nakajima S, Caravaggio F, Iwata Y, Gerretsen P, Kim J, Takeuchi H, Shinagawa S, Patel R, Chakravarty MM, Graff-Guerrero A. Hippocampal and Clinical Trajectories of Mild Cognitive Impairment with Suspected Non-Alzheimer's Disease Pathology. J Alzheimers Dis 2018; 58:747-762. [PMID: 28505977 DOI: 10.3233/jad-170201] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Suspected non-Alzheimer's disease pathology (SNAP) characterizes individuals showing neurodegeneration (e.g., hypometabolism) without amyloid-β (Aβ). Findings from previous studies regarding clinical and structural trajectories of SNAP are inconsistent. Using data from the Alzheimer's Disease Neuroimaging Initiative, patients with amnestic mild cognitive impairment (MCI) were categorized into four groups: amyloid positive with hypometabolism (Aβ+ND+), amyloid only (Aβ+ND-), neither amyloid nor hypometabolism (Aβ-ND-), and SNAP (Aβ-ND+). Aβ+ND+(n = 33), Aβ+ND-(n = 32), and Aβ-ND-(n = 36) were matched to SNAP for age, gender, apolipoprotein E4 (apoE4) genotype, and scores on the Montreal Cognitive Assessment. Elderly controls (n = 40) were also matched to SNAP for age, gender, and apoE4 genotype. Longitudinal changes were compared across groups in terms of hippocampal volume, clinical symptoms, daily functioning, and cognitive functioning over a 2-year period. At baseline, no difference in cognition and functioning was observed between SNAP and Aβ+groups. SNAP showed worse clinical symptoms and impaired functioning at baseline compared to Aβ-ND-and controls. Two years of follow-up showed no differences in hippocampal volume changes between SNAP and any of the comparison groups. SNAP showed worse functional deterioration in comparison to Aβ-ND-and controls. However, Aβ+ND+ showed more severe changes in clinical symptoms in comparison to SNAP. Thus, patients with MCI and SNAP showed 1) more severe functional deterioration compared to Aβ-ND-and controls, 2) no differences with Aβ+ND-, and 3) less cognitive deterioration than Aβ+ND+. Future studies should investigate what causes SNAP, which is different from typical AD pathology and biomarker cascades.
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Affiliation(s)
- Jun Ku Chung
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Eric Plitman
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Shinichiro Nakajima
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Yusuke Iwata
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Philip Gerretsen
- Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
| | - Julia Kim
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Hiroyoshi Takeuchi
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | | | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Ariel Graff-Guerrero
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,Multimodal Imaging Group - Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Canada
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Wolfsgruber S, Polcher A, Koppara A, Kleineidam L, Frölich L, Peters O, Hüll M, Rüther E, Wiltfang J, Maier W, Kornhuber J, Lewczuk P, Jessen F, Wagner M. Cerebrospinal Fluid Biomarkers and Clinical Progression in Patients with Subjective Cognitive Decline and Mild Cognitive Impairment. J Alzheimers Dis 2018; 58:939-950. [PMID: 28527210 DOI: 10.3233/jad-161252] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND There is very limited data on the prevalence of abnormal cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and their predictive value for clinical progression in memory clinic patients with subjective cognitive decline (SCD). OBJECTIVE To assess the frequency of abnormal CSF biomarkers of AD and their predictive value for clinical progression in memory clinic patients with SCD in comparison to patients with mild cognitive impairment (MCI) from the same cohort. METHODS We analyzed prospective data from memory clinic patients of the German Competence Network Dementia cohort with a baseline diagnosis of SCD (n = 82) or MCI (n = 134), distinguished by actuarial neuropsychological MCI criteria ("Jak-Bondi criteria"). Risk of clinical progression during 3-year follow-up was evaluated with Cox-Proportional-Hazard models. RESULTS Prevalence of abnormal values in CSF markers of tau-mediated neurodegeneration (67.8% versus 46.3%) but not of amyloid deposition (40.3% versus 35.4%) was significantly higher in MCI compared to SCD. The rate of incident AD dementia (26.1% versus 12.2%) was also significantly higher in MCI. In SCD, additional 22% progressed to MCI during follow-up. Combined amyloid/tau abnormality was the strongest predictor of clinical progression in both groups. CONCLUSION High prevalence of biomarker abnormality and clinical progression, together with the predictive value of CSF biomarkers, in memory clinic patients with SCD support the validity and usefulness of this condition as a "pre-MCI" at risk stage of AD.
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Affiliation(s)
- Steffen Wolfsgruber
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Alexandra Polcher
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Alexander Koppara
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Luca Kleineidam
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Lutz Frölich
- Department of Gerontopsychiatry, Central Institute of Mental Health, Mannheim, Germany
| | - Oliver Peters
- Department of Psychiatry, Charité Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Michael Hüll
- Center for Geriatric Medicine and Gerontology, University of Freiburg, Germany
| | - Eckart Rüther
- Department ofPsychiatry and Psychotherapy, University of Göttingen, Germany
| | - Jens Wiltfang
- Department ofPsychiatry and Psychotherapy, University of Göttingen, Germany
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.,Department of Neurodegeneration Diagnostics, Medical University of Biasłystok, and Departmentof Biochemical Diagnostics, University Hospital of Bialystok, Bialystok, Poland
| | - Frank Jessen
- German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Psychiatry, University of Cologne, Germany
| | - Michael Wagner
- Department of Psychiatry and Psychotherapy, University of Bonn, Germany.,German Center for Neurodegenerative Diseases, Bonn, Germany
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Firouzian A, Whittington A, Searle GE, Koychev I, Zamboni G, Lovestone S, Gunn RN. Imaging Aβ and tau in early stage Alzheimer's disease with [ 18F]AV45 and [ 18F]AV1451. EJNMMI Res 2018; 8:19. [PMID: 29500717 PMCID: PMC5834417 DOI: 10.1186/s13550-018-0371-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Accepted: 02/19/2018] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND AD is a progressive neurodegenerative disorder that is associated with the accumulation of two different insoluble protein aggregates, Aβ plaques and hyperphosphorylated tau. This study aimed to investigate the optimal acquisition and quantification of [18F]AV45 and [18F]AV1451 to image Aβ and tau, respectively, in subjects with AD. Fifteen subjects with early stage AD underwent a T1-weighted structural MRI and two dynamic PET scans to image Aβ (60 min, [18F]AV45) and tau (120 min, [18F]AV1451). Both dynamic BPND and static SUVR outcome measures were calculated and compared for 12 out of 15 subjects who completed 60 min of the Aβ PET scan and at least 110 min of the tau PET scan. The SRTM and reference Logan graphical analysis were applied to the dynamic data to estimate regional BPND values and SUVR ratios from the static data. Optimal acquisition windows were explored for both the dynamic and static acquisitions. In addition, the spatial correlation between regional Aβ and tau signals was explored. RESULTS Both the SRTM and graphical analysis methods showed a good fit to the dynamic data for both Aβ and tau dynamic PET scans. Mean regional BPND estimates became stable 30 min p.i. for [18F]AV45 and 80 min p.i. for [18F]AV1451. Time stability analysis of static SUVR data showed that the outcome measure starts to become stable for scan windows of 30-50 min p.i. for [18F]AV45 and 80-100 min p.i. for [18F]AV1451. The results from these time windows correlated well with the results from the full dynamic analysis for both tracers (R2 = 0.74 for [18F]AV45 and R2 = 0.88 for [18F]AV1451). There was a high correlation between amyloid uptake estimate using both dynamic analysis methods in thalamus and tau uptake in thalamus, hippocampus and amygdala. CONCLUSIONS Short static PET scans at appropriate time windows provided SUVR values which were in reasonable agreement with BPND values calculated from dynamic scans using SRTM and reference Logan. These simplified methods may be appropriate for classification and intervention studies, although caution should be employed when considering interventional studies where blood flow and extraction could change.
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Affiliation(s)
- Azadeh Firouzian
- Imanova Ltd., Burlington Danes Building, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK
| | - Alex Whittington
- Department of Medicine, Faculty of Medicine, Imperial College London, South Kensington Campus, London, SW7 2AZ UK
| | - Graham E. Searle
- Imanova Ltd., Burlington Danes Building, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK
| | - Ivan Koychev
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX UK
| | - Giovanna Zamboni
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU UK
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX UK
| | - Roger N. Gunn
- Imanova Ltd., Burlington Danes Building, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK
- Department of Medicine, Faculty of Medicine, Imperial College London, South Kensington Campus, London, SW7 2AZ UK
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - on behalf of the Deep and Frequent Phenotyping study team
- Imanova Ltd., Burlington Danes Building, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK
- Department of Medicine, Faculty of Medicine, Imperial College London, South Kensington Campus, London, SW7 2AZ UK
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU UK
- Department of Engineering Science, University of Oxford, Oxford, UK
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Bachurin SO, Gavrilova SI, Samsonova A, Barreto GE, Aliev G. Mild cognitive impairment due to Alzheimer disease: Contemporary approaches to diagnostics and pharmacological intervention. Pharmacol Res 2018; 129:216-226. [DOI: 10.1016/j.phrs.2017.11.021] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 11/15/2017] [Accepted: 11/17/2017] [Indexed: 01/16/2023]
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256
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Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study. Lancet Neurol 2018; 17:335-346. [PMID: 29500152 DOI: 10.1016/s1474-4422(18)30029-2] [Citation(s) in RCA: 145] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 11/16/2017] [Accepted: 12/21/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimer's disease. We assessed associations between brain β-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimer's disease. METHODS The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70-85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid β deposition on 18F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on 18F-fluorodeoxyglucose (18F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and 18F-FDG and 18F-florbetapir PET every 24 months. We assessed associations of amyloid β deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimer's disease was defined as an amnestic syndrome of the hippocampal type. FINDINGS From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1-8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid β deposition and the remainder did not. The amyloid β subgroups did not differ for any psychobehavioural, cognitive, actigraphy, and structural and functional neuroimaging results after adjustment for age, sex, and level of education More participants positive for amyloid β deposition had the APOE ε4 allele (33 [38%] vs 29 [13%], p<0·0001). Amyloid β1-42 concentration in CSF significantly correlated with mean 18F-florbetapir uptake at baseline (r=-0·62, p<0·0001) and the ratio of amyloid β1-42 to amyloid β1-40 (r=-0·61, p<0·0001), and identified amyloid β deposition status with high accuracy (mean area under the curve values 0·89, 95% CI 0·80-0·98 and 0·84, 0·72-0·96, respectively). No difference was seen in MMSE (28·3 [SD 2·0] vs 28·9 [1·2], p=0·16) and Clinical Dementia Rating scores (0·06 [0·2] vs 0·05 [0·3]; p=0·79) at 30 months (n=274) between participants positive or negative for amyloid β. Four participants (all positive for amyloid β deposition at baseline) progressed to prodromal Alzheimer's disease. They were older than other participants positive for amyloid β deposition at baseline (mean 80·2 years [SD 4·1] vs 76·8 years [SD 3·4]) and had greater 18F-florbetapir uptake at baseline (mean standard uptake value ratio 1·46 [SD 0·16] vs 1·02 [SD 0·20]), and more were carriers of the APOE ε4 allele (three [75%] of four vs 33 [39%] of 83). They also had mild executive dysfunction at baseline (mean FCSRT free recall score 21·25 [SD 2·75] vs 29·08 [5·44] and Frontal Assessment Battery total score 13·25 [1·50] vs 16·05 [1·68]). INTERPRETATION Brain β-amyloidosis alone did not predict progression to prodromal Alzheimer's disease within 30 months. Longer follow-up is needed to establish whether this finding remains consistent. FUNDING Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epinière (IHU-A-ICM), Ministry of Research, Fondation Plan Alzheimer, Pfizer, and Avid.
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257
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Hollands S, Lim YY, Laws SM, Villemagne VL, Pietrzak RH, Harrington K, Porter T, Snyder P, Ames D, Fowler C, Rainey-Smith SR, Martins RN, Salvado O, Robertson J, Rowe CC, Masters CL, Maruff P. APOEɛ4 Genotype, Amyloid, and Clinical Disease Progression in Cognitively Normal Older Adults. J Alzheimers Dis 2018; 57:411-422. [PMID: 28234254 DOI: 10.3233/jad-161019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND In cognitively normal (CN) older adults, carriage of the apolipoprotein E (APOE) ɛ4 allele is associated with increased risk for dementia of the Alzheimer type (AD-dementia). It is unclear whether this occurs solely through APOEɛ4 increasing amyloid-β (Aβ) accumulation or through processes independent of Aβ. OBJECTIVE To determine the extent and nature to which APOEɛ4 increases risk for clinical disease progression in CN older adults. METHODS Data from the total (n = 765) and Aβ-imaged (n = 423) CN cohort in the Australian Imaging, Biomarker and Lifestyle (AIBL) Study of Ageing was analyzed using Cox proportional hazard models to estimate ɛ4 risk for clinical disease progression over a 72-month follow-up. RESULTS With Aβ status unknown and risk from demographic characteristics controlled, ɛ4 carriage increased risk for clinical disease progression over 72 months by 2.66 times compared to risk of non-ɛ4 carriage. Re-analysis with Aβ status included showed that abnormally high Aβ increased risk for clinical disease progression over 72 months by 2.11 times compared to risk of low Aβ. However, with Aβ level known, ɛ4 carriage was no longer predictive of clinical disease progression. CONCLUSION In CN older adults, the risk of ɛ4 for clinical disease progression occurs through the effect of ɛ4 increasing Aβ levels.
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Affiliation(s)
| | - Yen Ying Lim
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - Simon M Laws
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia.,Co-operative Research Centre for Mental Health, http://www.mentalhealthcrc.com
| | - Victor L Villemagne
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia.,Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Robert H Pietrzak
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Karra Harrington
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - Tenielle Porter
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia.,Co-operative Research Centre for Mental Health, http://www.mentalhealthcrc.com
| | - Peter Snyder
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - David Ames
- Academic Unit for Psychiatry of Old Age, St. Vincent's Health, The University of Melbourne, Kew, VIC, Australia.,National Ageing Research Institute, Parkville, VIC, Australia
| | - Christopher Fowler
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - Stephanie R Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia
| | - Ralph N Martins
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australia
| | - Olivier Salvado
- Commonwealth Scientific Industrial Research Organization (CSIRO) Preventative Health National Research Flagship, Australian e-Health Research Centre-BiaMedIA, Brisbane, QLD, Australia
| | - Joanne Robertson
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - Christopher C Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - Paul Maruff
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia.,Cogstate Ltd., Melbourne, VIC, Australia
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258
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Villemagne VL, Doré V, Burnham SC, Masters CL, Rowe CC. Imaging tau and amyloid-β proteinopathies in Alzheimer disease and other conditions. Nat Rev Neurol 2018; 14:225-236. [DOI: 10.1038/nrneurol.2018.9] [Citation(s) in RCA: 230] [Impact Index Per Article: 32.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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259
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Muñoz-Moreno E, Tudela R, López-Gil X, Soria G. Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease. Alzheimers Res Ther 2018; 10:16. [PMID: 29415770 PMCID: PMC5803915 DOI: 10.1186/s13195-018-0346-2] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 01/22/2018] [Indexed: 02/05/2023]
Abstract
BACKGROUND Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present. METHODS Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats. RESULTS The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes. CONCLUSIONS In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks have not yet been detected. Structural and functional network metrics of regions related to reward, memory, and sensory performance were strongly correlated with the cognitive outcome. The use of animal models is essential for the early identification of these alterations and can contribute to the development of early biomarkers of the disease based on MRI connectomics.
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Affiliation(s)
- Emma Muñoz-Moreno
- Experimental 7T MRI Unit, Institut d’Investigacions Biòmediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Raúl Tudela
- Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Group of Biomedical Imaging, University of Barcelona, Barcelona, Spain
| | - Xavier López-Gil
- Experimental 7T MRI Unit, Institut d’Investigacions Biòmediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Guadalupe Soria
- Experimental 7T MRI Unit, Institut d’Investigacions Biòmediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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260
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Ienca M, Vayena E, Blasimme A. Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy. Front Med (Lausanne) 2018; 5:13. [PMID: 29468161 PMCID: PMC5808247 DOI: 10.3389/fmed.2018.00013] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 01/16/2018] [Indexed: 11/13/2022] Open
Abstract
Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy.
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Affiliation(s)
- Marcello Ienca
- Health Ethics and Policy Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Effy Vayena
- Health Ethics and Policy Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Alessandro Blasimme
- Health Ethics and Policy Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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261
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Hsu DC, Mormino EC, Schultz AP, Amariglio RE, Donovan NJ, Rentz DM, Johnson KA, Sperling RA, Marshall GA. Lower Late-Life Body-Mass Index is Associated with Higher Cortical Amyloid Burden in Clinically Normal Elderly. J Alzheimers Dis 2018; 53:1097-105. [PMID: 27340843 DOI: 10.3233/jad-150987] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Lower body-mass index (BMI) in late life has been associated with an increased risk of dementia, and weight loss has been associated with more rapid decline in Alzheimer's disease (AD) dementia. OBJECTIVE To explore the association between BMI and cortical amyloid burden in clinically normal (CN) elderly at risk for AD dementia. METHODS Cross-sectional analyses were completed using baseline data from the Harvard Aging Brain Study, consisting of 280 community-dwelling CN older adults aged 62-90. Assessments included medical histories and physical exam, Pittsburgh compound B (PiB) positron emission tomography (PET) amyloid imaging, and apolipoprotein E ɛ4 (APOE4) genotyping. For the primary analysis, a general linear regression model was used to evaluate the association of BMI with PiB retention. Covariates included age, sex, years of education, and APOE4 carrier status. Secondary analyses were performed for BMI subdivisions (normal, overweight, obese), APOE4 carriers, and BMI×APOE4 interaction. RESULTS In the primary analysis, greater PiB retention was associated with lower BMI (β = -0.14, p = 0.02). In the secondary analyses, APOE4 carrier status (β= -0.27, p = 0.02) and normal BMI (β= -0.25, p = 0.01), as opposed to overweight or obese BMI, were associated with greater PiB retention. The BMI×APOE4 interaction was also significant (β= -0.14, p = 0.04). CONCLUSIONS This finding offers new insight into the role of BMI at the preclinical stage of AD, wherein lower BMI late in life is associated with greater cortical amyloid burden. Future studies are needed to elucidate the mechanism behind this association, especially in those with lower BMI who are APOE4 carriers.
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Affiliation(s)
- David C Hsu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Mercy Medical Group, Sacramento, CA, USA
| | - Elizabeth C Mormino
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nancy J Donovan
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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262
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Grober E, Veroff AE, Lipton RB. Temporal unfolding of declining episodic memory on the Free and Cued Selective Reminding Test in the predementia phase of Alzheimer's disease: Implications for clinical trials. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2018; 10:161-171. [PMID: 29552631 PMCID: PMC5852329 DOI: 10.1016/j.dadm.2017.12.004] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction Free and Cued Selective Reminding Test (FCSRT) performance identifies patients with preclinical disease at elevated risk for developing Alzheimer's dementia, predicting diagnosis better than other memory tests. Methods Based on literature mapping FCSRT performance to clinical outcomes and biological markers, and on longitudinal preclinical data from the Baltimore Longitudinal Study of Aging, we developed the Stages of Objective Memory Impairment (SOMI) model. Five sequential stages of episodic memory decline are defined by Free Recall (FR) and Total Recall (TR) score ranges and years prior to dementia diagnosis. We sought to replicate the SOMI model using longitudinal assessments of 142 Einstein Aging Study participants who developed AD over 10 years. Results Time to diagnosis was at least seven years if FR was intact, at least four years if TR was intact, and two years if TR was impaired, consistent with SOMI model predictions. The SOMI identified incipient dementia with excellent sensitivity and specificity. Discussion The SOMI model provides an efficient approach for clinical trial cognitive screening in advance of more costly biomarker studies and ultimately in clinical practice, and provides a vocabulary for understanding AD biomarker patterns and for re-analysis of existing clinical trial data.
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Affiliation(s)
- Ellen Grober
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
| | | | - Richard B Lipton
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
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263
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Babulal GM, Chen S, Williams MM, Trani JF, Bakhshi P, Chao GL, Stout SH, Fagan AM, Benzinger TL, Holtzman DM, Morris JC, Roe CM. Depression and Alzheimer's Disease Biomarkers Predict Driving Decline. J Alzheimers Dis 2018; 66:1213-1221. [PMID: 30400098 PMCID: PMC6330210 DOI: 10.3233/jad-180564] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND Symptomatic Alzheimer's disease (AD) and depression independently increase crash risk. Additionally, depression is both a risk factor for and a consequence of AD. OBJECTIVE To examine whether a depression diagnosis, antidepressant use, and preclinical AD are associated with driving decline among cognitively normal older adults. METHODS Cognitively normal participants, age ≥65, were enrolled. Cox proportional hazards models evaluated whether a depression diagnosis, depressive symptoms (Geriatric Depression Scale), antidepressant use, cerebrospinal fluid (amyloid-β42 [Aβ42], tau, phosphorylated tau181 [ptau181]), and amyloid imaging biomarkers (Pittsburgh Compound B and Florbetapir) were associated with time to receiving a rating of marginal/fail on a road test. Age was adjusted for in all models. RESULTS Data were available from 131 participants with age ranging from 65.4 to 88.2 years and mean follow up of 2.4 years (SD = 1.0). A depression diagnosis was associated with a faster time to receiving a marginal/fail rating on a road test and antidepressant use (p = 0.024, HR = 2.62). Depression diagnosis and CSF and amyloid PET imaging biomarkers were associated with driving performance on the road test (p≤0.05, HR = 2.51-3.15). In the CSF ptau181 model, depression diagnosis (p = 0.031, HR = 2.51) and antidepressant use (p = 0.037, HR = 2.50) were statistically significant predictors. There were no interaction effects between depression diagnosis, antidepressant use, and biomarker groups. Depressive symptomology was not a statistically significant predictor of driving performance. CONCLUSIONS While, as previously shown, preclinical AD alone predicts a faster time to receiving a marginal/fail rating, these results suggest that also having a diagnosis of depression accelerates the onset of driving problems in cognitively normal older adults.
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Affiliation(s)
- Ganesh M. Babulal
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzie Chen
- St. Louis College of Pharmacy, St. Louis, MO, USA
| | | | | | - Parul Bakhshi
- Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
- Brown School, Washington University, St. Louis, MO, USA
| | | | - Sarah H. Stout
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M. Fagan
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - David M. Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA
- Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine M. Roe
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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264
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Roe CM, Babulal GM, Mishra S, Gordon BA, Stout SH, Ott BR, Carr DB, Ances BM, Morris JC, Benzinger TL. Tau and Amyloid Positron Emission Tomography Imaging Predict Driving Performance Among Older Adults with and without Preclinical Alzheimer's Disease. J Alzheimers Dis 2018; 61:509-513. [PMID: 29171997 PMCID: PMC5784441 DOI: 10.3233/jad-170521] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Abnormal levels of Alzheimer's disease (AD) biomarkers, measured by positron emission tomography imaging using amyloid-based radiotracers and cerebrospinal fluid, are associated with impaired driving performance in older adults. We examined whether preclinical AD staging, defined using amyloid imaging and tau imaging using the radiotracer T807 (AKA flortaucipir or AV-1451), was associated with receiving a marginal/fail rating on a standardized road test (n = 42). Participants at Stage 2 (positive amyloid and tau scans) of preclinical AD were more likely to receive a marginal/fail rating compared to participants at Stage 0 or 1. Stage 2 preclinical AD may manifest in worse driving performance.
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Affiliation(s)
- Catherine M. Roe
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ganesh M. Babulal
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Shruti Mishra
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah H. Stout
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian R. Ott
- The Alzheimer’s Disease and Memory Disorders Center, Alpert Medical School of Brown University, Providence, RI, USA
| | - David B. Carr
- The Rehabilitation Institute of St. Louis, Washington University School of Medicine, St. Louis, MO, USA
| | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Immunology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Physical Therapy, Washington University School of Medicine, St. Louis, MO, USA
- Department of Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
- The Rehabilitation Institute of St. Louis, Washington University School of Medicine, St. Louis, MO, USA
- The Alzheimer’s Disease and Memory Disorders Center, Alpert Medical School of Brown University, Providence, RI, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
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265
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Thomas KR, Edmonds EC, Eppig J, Salmon DP, Bondi MW. Using Neuropsychological Process Scores to Identify Subtle Cognitive Decline and Predict Progression to Mild Cognitive Impairment. J Alzheimers Dis 2018; 64:195-204. [PMID: 29865077 PMCID: PMC7263028 DOI: 10.3233/jad-180229] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND We previously operationally-defined subtle cognitive decline (SCD) in preclinical Alzheimer's disease (AD) using total scores on neuropsychological (NP) tests. NP process scores (i.e., provide information about how a total NP score was achieved) may be a useful tool for identifying early cognitive inefficiencies prior to objective impairment seen in mild cognitive impairment (MCI) and dementia. OBJECTIVE We aimed to integrate process scores into the SCD definition to identify stages of SCD and improve early detection of those at risk for decline. METHODS Cognitively "normal" participants from the Alzheimer's Disease Neuroimaging Initiative were classified as "early" SCD (E-SCD; >1 SD below norm-adjusted mean on 2 process scores or on 1 process score plus 1 NP total score), "late" SCD (L-SCD; existing SCD criteria of >1 SD below norm-adjusted mean on 2 NP total scores in different domains), or "no SCD" (NC). Process scores considered in the SCD criteria were word-list intrusion errors, retroactive interference, and learning slope. Cerebrospinal fluid AD biomarkers were used to examine pathologic burden across groups. RESULTS E-SCD and L-SCD progressed to MCI 2.5-3.4 times faster than the NC group. Survival curves for E-SCD and L-SCD converged at 7-8 years after baseline. The combined (E-SCD+L-SCD) group had improved sensitivity to detect progression to MCI relative to L-SCD only. AD biomarker positivity increased across NC, SCD, and MCI groups. CONCLUSIONS Process scores can be integrated into the SCD criteria to allow for increased sensitivity and earlier identification of cognitively normal older adults at risk for decline prior to frank impairment on NP total scores.
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Affiliation(s)
- Kelsey R. Thomas
- Veteran Affairs San Diego Healthcare System, San Diego, CA
- Dept. of Psychiatry, University of California, San Diego, School of Medicine, La Jolla, CA
| | - Emily C. Edmonds
- Veteran Affairs San Diego Healthcare System, San Diego, CA
- Dept. of Psychiatry, University of California, San Diego, School of Medicine, La Jolla, CA
| | - Joel Eppig
- San Diego State University/University of California, San Diego (SDSU/UCSD) Joint Doctoral Program in Clinical Psychology, San Diego, CA
| | - David P. Salmon
- Dept. of Neurosciences, University of California San Diego, School of Medicine, La Jolla, CA
| | - Mark W. Bondi
- Veteran Affairs San Diego Healthcare System, San Diego, CA
- Dept. of Psychiatry, University of California, San Diego, School of Medicine, La Jolla, CA
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266
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Ganguli M, Albanese E, Seshadri S, Bennett DA, Lyketsos C, Kukull WA, Skoog I, Hendrie HC. Population Neuroscience: Dementia Epidemiology Serving Precision Medicine and Population Health. Alzheimer Dis Assoc Disord 2018; 32:1-9. [PMID: 29319603 PMCID: PMC5821530 DOI: 10.1097/wad.0000000000000237] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Over recent decades, epidemiology has made significant contributions to our understanding of dementia, translating scientific discoveries into population health. Here, we propose reframing dementia epidemiology as "population neuroscience," blending techniques and models from contemporary neuroscience with those of epidemiology and biostatistics. On the basis of emerging evidence and newer paradigms and methods, population neuroscience will minimize the bias typical of traditional clinical research, identify the relatively homogenous subgroups that comprise the general population, and investigate broader and denser phenotypes of dementia and cognitive impairment. Long-term follow-up of sufficiently large study cohorts will allow the identification of cohort effects and critical windows of exposure. Molecular epidemiology and omics will allow us to unravel the key distinctions within and among subgroups and better understand individuals' risk profiles. Interventional epidemiology will allow us to identify the different subgroups that respond to different treatment/prevention strategies. These strategies will inform precision medicine. In addition, insights into interactions between disease biology, personal and environmental factors, and social determinants of health will allow us to measure and track disease in communities and improve population health. By placing neuroscience within a real-world context, population neuroscience can fulfill its potential to serve both precision medicine and population health.
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Affiliation(s)
- Mary Ganguli
- Departments of Psychiatry and Neurology, School of Medicine and Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | | | | | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL
| | - Constantine Lyketsos
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Ingmar Skoog
- Institute of Neuroscience and Physiology, Gothenburg University, Gothenburg, Sweden
| | - Hugh C Hendrie
- Regenstrief Institute Inc., Indiana University Center for Aging Research, Indianapolis, IN
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267
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Jansen WJ, Ossenkoppele R, Tijms BM, Fagan AM, Hansson O, Klunk WE, van der Flier WM, Villemagne VL, Frisoni GB, Fleisher AS, Lleó A, Mintun MA, Wallin A, Engelborghs S, Na DL, Chételat G, Molinuevo JL, Landau SM, Mattsson N, Kornhuber J, Sabri O, Rowe CC, Parnetti L, Popp J, Fladby T, Jagust WJ, Aalten P, Lee DY, Vandenberghe R, Resende de Oliveira C, Kapaki E, Froelich L, Ivanoiu A, Gabryelewicz T, Verbeek MM, Sanchez-Juan P, Hildebrandt H, Camus V, Zboch M, Brooks DJ, Drzezga A, Rinne JO, Newberg A, de Mendonça A, Sarazin M, Rabinovici GD, Madsen K, Kramberger MG, Nordberg A, Mok V, Mroczko B, Wolk DA, Meyer PT, Tsolaki M, Scheltens P, Verhey FRJ, Visser PJ, Aarsland D, Alcolea D, Alexander M, Almdahl IS, Arnold SE, Baldeiras I, Barthel H, van Berckel BNM, Blennow K, van Buchem MA, Cavedo E, Chen K, Chipi E, Cohen AD, Förster S, Fortea J, Frederiksen KS, Freund-Levi Y, Gkatzima O, Gordon MF, Grimmer T, Hampel H, Hausner L, Hellwig S, Herukka SK, Johannsen P, Klimkowicz-Mrowiec A, Köhler S, Koglin N, van Laere K, de Leon M, Lisetti V, Maier W, Marcusson J, Meulenbroek O, Møllergård HM, Morris JC, Nordlund A, Novak GP, Paraskevas GP, Perera G, Peters O, Ramakers IHGB, et alJansen WJ, Ossenkoppele R, Tijms BM, Fagan AM, Hansson O, Klunk WE, van der Flier WM, Villemagne VL, Frisoni GB, Fleisher AS, Lleó A, Mintun MA, Wallin A, Engelborghs S, Na DL, Chételat G, Molinuevo JL, Landau SM, Mattsson N, Kornhuber J, Sabri O, Rowe CC, Parnetti L, Popp J, Fladby T, Jagust WJ, Aalten P, Lee DY, Vandenberghe R, Resende de Oliveira C, Kapaki E, Froelich L, Ivanoiu A, Gabryelewicz T, Verbeek MM, Sanchez-Juan P, Hildebrandt H, Camus V, Zboch M, Brooks DJ, Drzezga A, Rinne JO, Newberg A, de Mendonça A, Sarazin M, Rabinovici GD, Madsen K, Kramberger MG, Nordberg A, Mok V, Mroczko B, Wolk DA, Meyer PT, Tsolaki M, Scheltens P, Verhey FRJ, Visser PJ, Aarsland D, Alcolea D, Alexander M, Almdahl IS, Arnold SE, Baldeiras I, Barthel H, van Berckel BNM, Blennow K, van Buchem MA, Cavedo E, Chen K, Chipi E, Cohen AD, Förster S, Fortea J, Frederiksen KS, Freund-Levi Y, Gkatzima O, Gordon MF, Grimmer T, Hampel H, Hausner L, Hellwig S, Herukka SK, Johannsen P, Klimkowicz-Mrowiec A, Köhler S, Koglin N, van Laere K, de Leon M, Lisetti V, Maier W, Marcusson J, Meulenbroek O, Møllergård HM, Morris JC, Nordlund A, Novak GP, Paraskevas GP, Perera G, Peters O, Ramakers IHGB, Rami L, Rodríguez-Rodríguez E, Roe CM, Rot U, Rüther E, Santana I, Schröder J, Seo SW, Soininen H, Spiru L, Stomrud E, Struyfs H, Teunissen CE, Vos SJB, van Waalwijk van Doorn LJC, Waldemar G, Wallin ÅK, Wiltfang J, Zetterberg H. Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia. JAMA Psychiatry 2018; 75:84-95. [PMID: 29188296 PMCID: PMC5786156 DOI: 10.1001/jamapsychiatry.2017.3391] [Show More Authors] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Cerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials. OBJECTIVE To investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017. MAIN OUTCOMES AND MEASURES Global cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype. RESULTS Among 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, -1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P < .001) and low MMSE (mean difference, 14% [95% CI, 12%-17%], P < .001) scores, and this association decreased with age. Low cognitive scores had limited utility for screening of amyloid positivity in persons with normal cognition and those with MCI. In persons with normal cognition, the age-related increase in low memory score paralleled the age-related increase in amyloid positivity with an intervening period of 10 to 15 years. CONCLUSIONS AND RELEVANCE Although low memory scores are an early marker of amyloid positivity, their value as a screening measure for early AD among persons without dementia is limited.
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Affiliation(s)
- Willemijn J. Jansen
- Department of Psychiatry and Neuropsychology, School
for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University,
Maastricht, the Netherlands
| | - Rik Ossenkoppele
- Department of Neurology and Alzheimer Center, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands,Department of Radiology and Nuclear Medicine, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands,Department of Neurology, Memory and Aging Center,
University of California, San Francisco,Helen Wills Neuroscience Institute, University of
California, Berkeley
| | - Betty M. Tijms
- Department of Neurology and Alzheimer Center, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Anne M. Fagan
- Knight Alzheimer’s Disease Research Center,
Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Oskar Hansson
- Clinical Memory Research Unit, Clinical Sciences
Malmö, Lund University, Lund, Sweden
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh
School of Medicine, Pittsburgh, Pennsylvania
| | - Wiesje M. van der Flier
- Department of Neurology and Alzheimer Center, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands,Department of Epidemiology and Biostatistics, VU
University Medical Center, Amsterdam, the Netherlands
| | - Victor L. Villemagne
- Department of Nuclear Medicine and Centre for PET,
Austin Health, Melbourne, Australia
| | - Giovanni B. Frisoni
- Laboratory of Alzheimer's Neuroimaging and
Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy,Memory Clinic and LANVIE–Laboratory of
Neuroimaging of Aging, University Hospitals, and University of Geneva, Geneva, Switzerland
| | - Adam S. Fleisher
- Banner Alzheimer’s Institute, Phoenix,
Arizona,Eli Lilly and Company, Indianapolis, Indiana,Department of Neurosciences, University of
California, San Diego
| | - Alberto Lleó
- Neurology Department, Hospital de Sant Pau,
Barcelona, Spain
| | | | - Anders Wallin
- Institute of Neuroscience and Physiology,
Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia
(BIODEM), University of Antwerp, Antwerp, Belgium
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center,
Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Gäel Chételat
- Institut National de la Santé et de la
Recherche Médicale (INSERM), CHU de Caen, Caen, France
| | - José Luis Molinuevo
- Alzheimer’s Disease and Other Cognitive
Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | - Susan M. Landau
- Helen Wills Neuroscience Institute, University of
California, Berkeley
| | - Niklas Mattsson
- Clinical Memory Research Unit, Clinical Sciences
Malmö, Lund University, Lund, Sweden
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy,
Friedrich-Alexander University of Erlangen–Nuremberg, Erlangen, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of
Leipzig, Leipzig, Germany
| | - Christopher C. Rowe
- Knight Alzheimer’s Disease Research Center,
Department of Neurology, Washington University School of Medicine, St Louis, Missouri,Department of Nuclear Medicine and Centre for PET,
Austin Health, Melbourne, Australia
| | - Lucilla Parnetti
- Section of Neurology, Center for Memory
Disturbances, University of Perugia, Perugia, Italy
| | - Julius Popp
- Department of Psychiatry, Service of Old Age
Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Tormod Fladby
- Department of Neurology, Akershus University
Hospital, Lørenskog, Norway
| | - William J. Jagust
- Helen Wills Neuroscience Institute, University of
California, Berkeley
| | - Pauline Aalten
- Department of Psychiatry and Neuropsychology, School
for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University,
Maastricht, the Netherlands
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National
University, College of Medicine, Seoul, South Korea
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology and Alzheimer
Research Centre KU Leuven, Catholic University Leuven, Leuven, Belgium
| | - Catarina Resende de Oliveira
- Center for Neuroscience and Cell Biology, Faculty of
Medicine, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Elisabeth Kapaki
- First Department of Neurology, Eginition Hospital,
Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Lutz Froelich
- Department of Geriatric Psychiatry, Central
Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim,
Germany
| | - Adrian Ivanoiu
- Memory Clinic and Neurochemistry Laboratory, Saint
Luc University Hospital, Institute of Neuroscience, Université catholique de Louvain,
Brussels, Belgium
| | - Tomasz Gabryelewicz
- Department of Neurodegenerative Disorders,
Mossakowski Medical Research Centre Polish Academy of Sciences, Warsaw, Poland
| | - Marcel M. Verbeek
- Departments of Neurology and Laboratory Medicine,
Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud
University Medical Center, Nijmegen, the Netherlands
| | - Páscual Sanchez-Juan
- Neurology Service, Universitary Hospital
Marqués de Valdecilla, IDIVAL, Santander, Spain
| | | | - Vincent Camus
- CHRU de Tours, CIC INSERM 1415, INSERM U930, and
Université François Rabelais de Tours, Tours, France
| | - Marzena Zboch
- Alzheimer Center, Wroclaw Medical University,
Scinawa, Poland
| | - David J. Brooks
- Division of Neuroscience, Medical Research Council
Clinical Sciences Centre, Imperial College London, London, England
| | - Alexander Drzezga
- Department of Nuclear Medicine, University of
Cologne, Cologne, Germany
| | - Juha O. Rinne
- Turku PET Centre and Division of Clinical
Neurosciences Turku, University of Turku and Turku University Hospital, Turku, Finland
| | - Andrew Newberg
- Myrna Brind Center of Integrative Medicine, Thomas
Jefferson University and Hospital, Philadelphia, Pennsylvania
| | - Alexandre de Mendonça
- Institute of Molecular Medicine and Faculty of
Medicine, University of Lisbon, Lisbon, Portugal
| | - Marie Sarazin
- Neurologie de la Mémoire et du Langage, Centre
Hospitalier Sainte-Anne, Université Paris 5, Paris, France
| | - Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center,
University of California, San Francisco
| | - Karine Madsen
- Neurobiology Research Unit, Copenhagen University
Hospital, Copenhagen, Denmark
| | - Milica G. Kramberger
- Center for Cognitive Impairments, University Medical
Centre Ljubljana, Ljubljana, Slovenia
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research,
Translational Alzheimer Neurobiology, Karolinska Institutet, and Geriatric Medicine,
Karolinska University Hospital, Stockholm, Sweden
| | - Vincent Mok
- Lui Che Woo Institute of Innovative Medicine,
Department of Medicine and Therapeutics, Therese Pei Fong Chow Research Centre for
Prevention of Dementia, Hong Kong
| | - Barbara Mroczko
- Department of Neurodegeneration Diagnostics, Leading
National Research Centre in Białystok (KNOW), Medical University of Białystok,
Białystok, Poland
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania,
Philadelphia
| | - Philipp T. Meyer
- Department of Nuclear Medicine, University Hospital
Freiburg, Freiburg, Germany
| | - Magda Tsolaki
- Third Department of Neurology, Aristotle University
of Thessaloniki, Thessaloniki, Greece
| | | | - Philip Scheltens
- Department of Neurology and Alzheimer Center, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Frans R. J. Verhey
- Department of Psychiatry and Neuropsychology, School
for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University,
Maastricht, the Netherlands
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School
for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University,
Maastricht, the Netherlands,Department of Neurology and Alzheimer Center, VU
University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Dag Aarsland
- Center for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Daniel Alcolea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | | | - Ina S Almdahl
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Steven E Arnold
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - Inês Baldeiras
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Mark A van Buchem
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Enrica Cavedo
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Stijmsalpêtrière, Boulevard de l'hôpital, F-75013, Paris, France.,AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière, Paris, France
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, Arizona
| | - Elena Chipi
- Section of Neurology, Center for Memory Disturbances, University of Perugia, Perugia, Italy
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Stefan Förster
- Department of Nuclear Medicine, Technische Universitaet München, Munich, Germany
| | - Juan Fortea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - Kristian S Frederiksen
- Danish Dementia Research Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Department of Geriatrics, Karolinska University Hospital Huddinge, Section of Clinical Geriatrics, Institution of NVS, Karolinska Institutet, Stockholm, Sweden
| | - Olymbia Gkatzima
- Third Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar der Technischen Universitaet München, Munich, Germany
| | - Harald Hampel
- Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Stijmsalpêtrière, Boulevard de l'hôpital, F-75013, Paris, France.,AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière, Paris, France.,Department of Psychiatry, Alzheimer Memorial Center and Geriatric Psychiatry Branch, Ludwig-Maximilian University, Munich, Germany
| | - Lucrezia Hausner
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Sabine Hellwig
- Center of Geriatrics and Gerontology, University Hospital Freiburg, Freiburg, Germany
| | - Sanna-Kaisa Herukka
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Peter Johannsen
- Memory Clinic, Danish Dementia Research Center, Rigshospitalet, Copenhagen, Denmark
| | | | - Sebastian Köhler
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | | | - Koen van Laere
- Department of Imaging and Pathology, Catholic University Leuven, Leuven, Belgium
| | - Mony de Leon
- School of Medicine, Center for Brain Health, New York University, New York
| | - Viviana Lisetti
- Section of Neurology, Center for Memory Disturbances, University of Perugia, Perugia, Italy
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Jan Marcusson
- Geriatric Medicine, Department of Clinical and Experimental Medicine, University of Linköping, Linköping, Sweden
| | - Olga Meulenbroek
- Department of Geriatric Medicine, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Hanne M Møllergård
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Arto Nordlund
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - Gerald P Novak
- Janssen Research and Development, Titusville, New Jersey
| | - George P Paraskevas
- First Department of Neurology, Eginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Gayan Perera
- Roche Products, Welwyn Garden City, United Kingdom.,Department of Psychological Medicine, Institute of Psychiatry, Kings College London, London, United Kingdom
| | - Oliver Peters
- Department of Psychiatry and Psychotherapy, Charité Berlin, German Center for Neurodegenrative Diseases (DZNE), Berlin, Germany
| | - Inez H G B Ramakers
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Lorena Rami
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | | | - Catherine M Roe
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Uros Rot
- Center for Cognitive Impairments, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Eckart Rüther
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Isabel Santana
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Johannes Schröder
- Sektion Gerontopsychiatrie, Universität Heidelberg, Heidelberg, Germany
| | - Sang W Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hilkka Soininen
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Luiza Spiru
- Department of Geriatrics-Gerontology-Gerontopsychiatry, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Erik Stomrud
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Charlotte E Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Linda J C van Waalwijk van Doorn
- Departments of Neurology and Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Gunhild Waldemar
- Department of Nuclear Medicine, Technische Universitaet München, Munich, Germany
| | - Åsa K Wallin
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,UCL Institute of Neurology, Queen Square, London, United Kingdom
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268
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Voevodskaya O, Pereira JB, Volpe G, Lindberg O, Stomrud E, van Westen D, Westman E, Hansson O. Altered structural network organization in cognitively normal individuals with amyloid pathology. Neurobiol Aging 2017; 64:15-24. [PMID: 29316528 DOI: 10.1016/j.neurobiolaging.2017.11.014] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Revised: 11/10/2017] [Accepted: 11/30/2017] [Indexed: 01/04/2023]
Abstract
Recent findings show that structural network topology is disrupted in Alzheimer's disease (AD), with changes occurring already at the prodromal disease stages. Amyloid accumulation, a hallmark of AD, begins several decades before symptom onset, and its effects on brain connectivity at the earliest disease stages are not fully known. We studied global and local network changes in a large cohort of cognitively healthy individuals (N = 299, Swedish BioFINDER study) with and without amyloid-β (Aβ) pathology (based on cerebrospinal fluid Aβ42/Aβ40 levels). Structural correlation matrices were constructed based on magnetic resonance imaging cortical thickness data. Despite the fact that no significant regional cortical atrophy was found in the Aβ-positive group, this group exhibited an altered global network organization, including decreased global efficiency and modularity. At the local level, Aβ-positive individuals displayed fewer and more disorganized modules as well as a loss of hubs. Our findings suggest that changes in network topology occur already at the presymptomatic (preclinical) stage of AD and may precede detectable cortical thinning.
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Affiliation(s)
- Olga Voevodskaya
- Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden.
| | - Joana B Pereira
- Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Olof Lindberg
- Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Erik Stomrud
- Memory Clinic, Skåne University Hospital, Malmö, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Danielle van Westen
- Department of Clinical Sciences, Diagnostic radiology, Lund University, Lund, Sweden; Imaging and Function, Skåne University Health Care, Lund, Sweden
| | - Eric Westman
- Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
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269
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Ruan Q, D'Onofrio G, Sancarlo D, Greco A, Lozupone M, Seripa D, Panza F, Yu Z. Emerging biomarkers and screening for cognitive frailty. Aging Clin Exp Res 2017; 29:1075-1086. [PMID: 28260159 DOI: 10.1007/s40520-017-0741-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Accepted: 02/16/2017] [Indexed: 11/24/2022]
Abstract
Physical frailty and cognitive frailty are two important targets of secondary intervention in aging research to narrow the gap between life and health span. The objective of the present narrative review was to examine clinical and epidemiological studies investigating the recently proposed construct of cognitive frailty and its subtypes, with a focus on operational definitions, clinical criteria, and emerging biomarkers potentially useful for the screening of this novel entity. Both physical frailty and frailty indexes with a multidimensional nature were associated with late-life cognitive impairment/decline, incident dementia, Alzheimer's disease (AD), mild cognitive impairment, vascular dementia, non-AD dementias, and AD pathology proposing cognitive frailty as a clinical entity with cognitive impairment related to physical causes with a potential reversibility. The new clinical and research AD criteria established by the National Institute on Aging-Alzheimer's Association and the American Psychiatric Association could improve the differential diagnosis of cognitive impairment within the cognitive frailty construct. The emerging biomarkers of sarcopenia, physical frailty, and cognitive impairment will provide the basis to establish more reliable clinical and research criteria for cognitive frailty, using different operational definitions for frailty and cognitive impairment and useful clinical, biological, and imaging markers for this novel clinical construct.
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Affiliation(s)
- Qingwei Ruan
- Shanghai Key Laboratory of Clinical Geriatrics, Department of Geriatrics, Huadong Hospital, and Research Center of Aging and Medicine, Shanghai Institute of Geriatrics and Gerontology, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Grazia D'Onofrio
- Geriatric Unit and Laboratory of Gerontology and Geriatrics, Department of Medical Sciences, IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Foggia, Italy
| | - Daniele Sancarlo
- Geriatric Unit and Laboratory of Gerontology and Geriatrics, Department of Medical Sciences, IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Foggia, Italy
| | - Antonio Greco
- Geriatric Unit and Laboratory of Gerontology and Geriatrics, Department of Medical Sciences, IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Foggia, Italy
| | - Madia Lozupone
- Neurodegenerative Disease Unit, Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Davide Seripa
- Geriatric Unit and Laboratory of Gerontology and Geriatrics, Department of Medical Sciences, IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Foggia, Italy
| | - Francesco Panza
- Geriatric Unit and Laboratory of Gerontology and Geriatrics, Department of Medical Sciences, IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Foggia, Italy.
- Neurodegenerative Disease Unit, Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy.
- Department of Clinical Research in Neurology, University of Bari Aldo Moro, "Pia Fondazione Cardinale G. Panico", Tricase, Lecce, Italy.
| | - Zhuowei Yu
- Shanghai Key Laboratory of Clinical Geriatrics, Department of Geriatrics, Huadong Hospital, and Research Center of Aging and Medicine, Shanghai Institute of Geriatrics and Gerontology, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
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270
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Hohman TJ, Dumitrescu L, Oksol A, Wagener M, Gifford KA, Jefferson AL. APOE allele frequencies in suspected non-amyloid pathophysiology (SNAP) and the prodromal stages of Alzheimer's Disease. PLoS One 2017; 12:e0188501. [PMID: 29190651 PMCID: PMC5708777 DOI: 10.1371/journal.pone.0188501] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 11/08/2017] [Indexed: 01/14/2023] Open
Abstract
Biomarker definitions for preclinical Alzheimer’s disease (AD) have identified individuals with neurodegeneration (ND+) without β-amyloidosis (Aβ-) and labeled them with suspected non-AD pathophysiology (SNAP). We evaluated Apolipoprotein E (APOE) ε2 and ε4 allele frequencies across biomarker definitions—Aβ-/ND- (n = 268), Aβ+/ND- (n = 236), Aβ-/ND+ or SNAP (n = 78), Aβ+/ND+ (n = 204)—hypothesizing that SNAP would have an APOE profile comparable to Aβ-/ND-. Using AD Neuroimaging Initiative data (n = 786, 72±7 years, 48% female), amyloid status (Aβ+ or Aβ-) was defined by cerebrospinal fluid (CSF) Aβ-42 levels, and neurodegeneration status (ND+ or ND-) was defined by hippocampal volume from MRI. Binary logistic regression related biomarker status to APOE ε2 and ε4 allele carrier status, adjusting for age, sex, education, and cognitive diagnosis. Compared to the biomarker negative (Aβ-/ND-) participants, higher proportions of ε4 and lower proportions of ε2 carriers were observed among Aβ+/ND- (ε4: OR = 6.23, p<0.001; ε2: OR = 0.53, p = 0.03) and Aβ+/ND+ participants (ε4: OR = 12.07, p<0.001; ε2: OR = 0.29, p = 0.004). SNAP participants were statistically comparable to biomarker negative participants (p-values>0.30). In supplemental analyses, comparable results were observed when coding SNAP using amyloid imaging and when using CSF tau levels. In contrast to APOE, a polygenic risk score for AD that excluded APOE did not show an association with amyloidosis or neurodegeneration (p-values>0.15), but did show an association with SNAP defined using CSF tau (β = 0.004, p = 0.02). Thus, in a population with low levels of cerebrovascular disease and a lower prevalence of SNAP than the general population, APOE and known genetic drivers of AD do not appear to contribute to the neurodegeneration observed in SNAP. Additional work in population based samples is needed to better elucidate the genetic contributors to various etiological drivers of SNAP.
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Affiliation(s)
- Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
- * E-mail:
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Amy Oksol
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Madison Wagener
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States of America
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271
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Kreisl WC, Henter ID, Innis RB. Imaging Translocator Protein as a Biomarker of Neuroinflammation in Dementia. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2017; 82:163-185. [PMID: 29413519 PMCID: PMC6190574 DOI: 10.1016/bs.apha.2017.08.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Neuroinflammation has long been considered a potential contributor to neurodegenerative disorders that result in dementia. Accumulation of abnormal protein aggregates in Alzheimer's disease, frontotemporal dementia, and dementia with Lewy bodies is associated with the activation of microglia and astrocytes into proinflammatory states, and chronic low-level activation of glial cells likely contributes to the pathological changes observed in these and other neurodegenerative diseases. The 18kDa translocator protein (TSPO) is a key biomarker for measuring inflammation in the brain via positron emission tomography (PET). Increased TSPO density has been observed in brain tissue from patients with neurodegenerative diseases and colocalizes to activated microglia and reactive astrocytes. Several radioligands have been developed to measure TSPO density in vivo with PET, and these have been used in clinical studies of different dementia syndromes. However, TSPO radioligands have limitations, including low specific-to-nonspecific signal and differential affinity to a polymorphism on the TSPO gene, which must be taken into consideration in designing and interpreting human PET studies. Nonetheless, most PET studies have shown that increased TSPO binding is associated with various dementias, suggesting that TSPO has potential as a biomarker to further explore the role of neuroinflammation in dementia pathogenesis and may prove useful in monitoring disease progression.
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Affiliation(s)
- William C Kreisl
- Taub Institute, Columbia University Medical Center, New York, NY, United States.
| | - Ioline D Henter
- Molecular Imaging Branch, National Institute of Mental Health, Bethesda, MD, United States
| | - Robert B Innis
- Molecular Imaging Branch, National Institute of Mental Health, Bethesda, MD, United States
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272
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Wirth M, Bejanin A, La Joie R, Arenaza-Urquijo EM, Gonneaud J, Landeau B, Perrotin A, Mézenge F, de La Sayette V, Desgranges B, Chételat G. Regional patterns of gray matter volume, hypometabolism, and beta-amyloid in groups at risk of Alzheimer's disease. Neurobiol Aging 2017; 63:140-151. [PMID: 29203090 DOI: 10.1016/j.neurobiolaging.2017.10.023] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 10/26/2017] [Accepted: 10/30/2017] [Indexed: 12/12/2022]
Abstract
Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) deposition and neurodegeneration. To seek for signs of such pathologies, we compared regional biomarker degrees and patterns of Aβ deposition, glucose hypometabolism, and gray matter volume (GMV) reduction in 3 groups at risk of AD. In elderly carriers of the apolipoprotein E ε4 (APOE4, n = 17), patients with subjective cognitive decline (n = 16), and patients with mild cognitive impairment (n = 30), head-to-head intermodality comparisons were performed on cross-sectional structural magnetic resonance images as well as 18F-fluorodeoxyglucose and 18F-florbetapir positron emission tomography scans. In mild cognitive impairment patients, 3 distinct biomarker patterns were recovered, similarly seen in AD patients: (1) in medial temporal regions, local GMV reduction exceeded hypometabolism, (2) in temporoparietal regions, hypometabolism predominated over GMV reduction, and (3) in frontal regions, Aβ deposition exceeded GMV reduction and hypometabolism. In subjective cognitive decline patients, only pattern 1 was detected, while APOE4 carriers demonstrated only pattern 3. Our findings highlight that regional AD-like biomarker patterns may vary across different at-risk populations, potentially reflecting differential mediators of these risks.
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Affiliation(s)
- Miranka Wirth
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, NeuroCure Clinical Research Center, Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Center for Stroke Research Berlin, Berlin, Germany
| | - Alexandre Bejanin
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Renaud La Joie
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Eider M Arenaza-Urquijo
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Julie Gonneaud
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Brigitte Landeau
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Audrey Perrotin
- Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Florence Mézenge
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Vincent de La Sayette
- Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Béatrice Desgranges
- Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Gaël Chételat
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Boulevard H. Becquerel, Caen, France; Normandie Université, UNICAEN, PSL Research University, EPHE, Inserm, U1077, CHU de Caen, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France.
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273
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Roberts RO, Knopman DS, Syrjanen JA, Aakre JA, Vassilaki M, Kremers WK, Mielke MM, Machulda MM, Graff-Radford J, Geda YE, Vemuri P, Lowe V, Jack CR, Petersen RC. Weighting and standardization of frequencies to determine prevalence of AD imaging biomarkers. Neurology 2017; 89:2039-2048. [PMID: 29030451 DOI: 10.1212/wnl.0000000000004652] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 08/24/2017] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE To estimate the prevalence of elevated brain amyloid and reduced cortical thickness (as a marker for neurodegeneration) in a defined population. METHODS Mayo Clinic Study of Aging participants underwent MRI to assess a composite Alzheimer disease (AD) signature cortical thickness measure and PET to assess brain amyloid accumulation. Participants were characterized as having elevated amyloid (A+/A-), reduced cortical thickness (N+/N-), and A+N+, A+N-, A-N+, or A-N-. The prevalence of AD biomarkers was derived by adjusting for nonparticipation and standardizing to the Olmsted County, Minnesota, population. RESULTS Among 1,646 participants without dementia (mean age 70.8 years; 53.2% men), the prevalence (95% confidence interval) of amyloidosis was 21.1% (19.1%-23.2%): women, 24.3%; men, 17.5%. The prevalence of reduced cortical thickness was 28.9% (26.4%-31.5%): women, 27.9%; men, 30.2%. The prevalence estimates of biomarker categories were as follows: A-N-: 61.4%; A+N-: 9.7%; A-N+: 17.4%; and A+N+: 11.5%, and varied by sex and by APOE ε4 carrier status. In men, prevalence estimates were as follows: A-N-: 62.6%; A+N-: 7.3%; A-N+: 19.9%; and A+N+: 10.2%. In women, prevalence estimates were as follows: A-N-: 60.4%; A+N-: 11.7%; A-N+: 15.3%; and A+N+: 12.6%. In ε4 carriers, prevalence estimates were as follows: A-N-: 54.6%; A+N-: 16.6%; A-N+: 12.4%; and A+N+: 16.4%. In non-ε4 carriers, prevalence estimates were as follows: A-N-: 63.3%; A+N-: 6.9%; A-N+: 19.9%; and A+N+: 10.0%. CONCLUSIONS These prevalence estimates are important for understanding age-related trends in amyloid positivity and AD signature cortical thickness in the population, and for potentially projecting the future burden of biomarkers in elderly persons.
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Affiliation(s)
- Rosebud O Roberts
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ.
| | - David S Knopman
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Jeremy A Syrjanen
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Jeremiah A Aakre
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Maria Vassilaki
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Walter K Kremers
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Michelle M Mielke
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Mary M Machulda
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Jonathan Graff-Radford
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Yonas E Geda
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Prashanthi Vemuri
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Val Lowe
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Clifford R Jack
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
| | - Ronald C Petersen
- From the Divisions of Epidemiology (R.O.R., M.V., M.M. Mielke, R.C.P.) and Biomedical Statistics and Informatics (J.A.S., J.A.A., W.K.K.), Department of Health Sciences Research, Department of Neurology (R.O.R., D.S.K., M.M. Mielke, J.G.-R., R.C.P.), Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (P.V., V.L., C.R.J.), Mayo Clinic, Rochester, MN; and Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ
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Tatebe H, Kasai T, Ohmichi T, Kishi Y, Kakeya T, Waragai M, Kondo M, Allsop D, Tokuda T. Quantification of plasma phosphorylated tau to use as a biomarker for brain Alzheimer pathology: pilot case-control studies including patients with Alzheimer's disease and down syndrome. Mol Neurodegener 2017; 12:63. [PMID: 28866979 PMCID: PMC5582385 DOI: 10.1186/s13024-017-0206-8] [Citation(s) in RCA: 173] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 08/18/2017] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND There is still a substantial unmet need for less invasive and lower-cost blood-based biomarkers to detect brain Alzheimer's disease (AD) pathology. This study is aimed to determine whether quantification of plasma tau phosphorylated at threonine 181 (p-tau181) is informative in the diagnosis of AD. METHODS We have developed a novel ultrasensitive immunoassay to quantify plasma p-tau181, and measured the levels of plasma p-tau181 in three cohorts. RESULTS In the first cohort composed of 20 AD patients and 15 age-matched controls, the plasma levels of p-tau181 were significantly higher in the AD patients than those in the controls (0.171 ± 0.166 pg/ml in AD versus 0.0405 ± 0.0756 pg/ml in controls, p = 0.0039). The percentage of the subjects whose levels of plasma p-tau181 exceeded the cut-off value (0.0921 pg/ml) was significantly higher in the AD group compared with the control group (60% in AD versus 16.7% in controls, p = 0.0090). In the second cohort composed of 20 patients with Down syndrome (DS) and 22 age-matched controls, the plasma concentrations of p-tau181 were significantly higher in the DS group (0.767 ± 1.26 pg/ml in DS versus 0.0415 ± 0.0710 pg/ml in controls, p = 0.0313). There was a significant correlation between the plasma levels of p-tau181 and age in the DS group (R2 = 0.4451, p = 0.0013). All of the DS individuals showing an extremely high concentration of plasma p-tau181 (> 1.0 pg/ml) were older than the age of 40. In the third cohort composed of 8 AD patients and 3 patients with other neurological diseases, the levels of plasma p-tau181 significantly correlated with those of CSF p-tau181 (R2 = 0.4525, p = 0.023). CONCLUSIONS We report for the first time quantitative data on the plasma levels of p-tau181 in controls and patients with AD and DS, and these data suggest that the plasma p-tau181 is a promising blood biomarker for brain AD pathology. This exploratory pilot study warrants further large-scale and well-controlled studies to validate the usefulness of plasma p-tau181 as an urgently needed surrogate marker for the diagnosis and disease progression of AD.
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Affiliation(s)
- Harutsugu Tatebe
- Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
- Department of Zaitaku (Homecare) Medicine, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
| | - Takashi Kasai
- Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
| | - Takuma Ohmichi
- Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
| | - Yusuke Kishi
- Strategic Marketing Division, SCRUM Inc, Tokyo, 130-0021 Japan
| | - Tomoshi Kakeya
- Strategic Marketing Division, SCRUM Inc, Tokyo, 130-0021 Japan
| | - Masaaki Waragai
- Department of Neurology, Higashi Matsudo Municipal Hospital, Matsudo, 270-2222 Japan
| | - Masaki Kondo
- Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
| | - David Allsop
- Division of Biomedical and Life Sciences, Faculty of Health and Medicine, Lancaster University, Lancaster, LA1 4YQ UK
| | - Takahiko Tokuda
- Department of Neurology, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
- Department of Molecular Pathobiology of Brain Diseases, Kyoto Prefectural University of Medicine, Kyoto, 602-0841 Japan
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275
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Progressive medial temporal lobe atrophy during preclinical Alzheimer's disease. NEUROIMAGE-CLINICAL 2017; 16:439-446. [PMID: 28879085 PMCID: PMC5577409 DOI: 10.1016/j.nicl.2017.08.022] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 08/07/2017] [Accepted: 08/25/2017] [Indexed: 11/21/2022]
Abstract
This study examined whether longitudinal MRI trajectories in medial temporal lobe (MTL) brain regions differed among groups of cognitively normal individuals defined by their cerebrospinal fluid (CSF) levels when they were first enrolled (N = 207; mean clinical follow-up = 13.3 years (max = 20 years), mean MRI follow-up = 2.4 years (max = 8 years)). We first compared atrophy rates among groups defined by CSF amyloid and phosphorylated-tau (p-tau) vs. CSF amyloid and total tau (t-tau). We also examined whether, in the presence of amyloid or tau/p-tau, the atrophy rates differed based on whether the subjects ultimately progressed to a diagnosis of mild cognitive impairment (MCI), as well as whether apolipoprotein ε4 (Apoε4) status had an impact on the longitudinal MRI trajectories. The primary finding was that when the groups were defined using CSF amyloid and p-tau, individuals with low levels of CSF amyloid and high levels of CSF p-tau (referred to as Stage 2) showed a significantly greater rate of atrophy in a composite measure of MTL volumes compared to groups defined by evidence of abnormal CSF levels in only one of the brain proteins (but not both), or no evidence of CSF abnormality. In contrast, there were no differences in rate of MTL atrophy when the groups were defined by levels of CSF amyloid and t-tau (instead of p-tau). Additionally, the rate of MTL atrophy did not differ between subjects who progressed to MCI at follow-up vs. those who remained cognitively normal when CSF levels of amyloid, t-tau, or p-tau were covaried. Lastly, the presence of an APOE ε4 genotype did not modulate the degree of MTL atrophy once baseline levels of CSF amyloid, p-tau or t-tau were accounted for. These results suggest that abnormal levels of CSF amyloid and CSF p-tau (but not t-tau) maximize the likelihood of observing significant MTL atrophy over time among individuals with normal cognition at baseline, and emphasize the importance of differentiating biomarkers that primarily reflect neurofibrillary tangle pathology (CSF p-tau) compared with biomarkers of neuronal injury (CSF t-tau). Examined association between CSF AD biomarkers and medial temporal lobe atrophy Abnormal levels of both amyloid and p-tau were associated with greatest atrophy. No difference in rate of atrophy based on levels of amyloid and total tau Follow-up diagnosis was unrelated to atrophy rate when covarying amyloid and p-tau. Levels of CSF amyloid and p-tau were associated with atrophy in preclinical AD.
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276
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Aisen PS, Cummings J, Jack CR, Morris JC, Sperling R, Frölich L, Jones RW, Dowsett SA, Matthews BR, Raskin J, Scheltens P, Dubois B. On the path to 2025: understanding the Alzheimer's disease continuum. Alzheimers Res Ther 2017; 9:60. [PMID: 28793924 PMCID: PMC5549378 DOI: 10.1186/s13195-017-0283-5] [Citation(s) in RCA: 331] [Impact Index Per Article: 41.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 07/04/2017] [Indexed: 12/02/2022]
Abstract
Basic research advances in recent years have furthered our understanding of the natural history of Alzheimer's disease (AD). It is now recognized that pathophysiological changes begin many years prior to clinical manifestations of disease and the spectrum of AD spans from clinically asymptomatic to severely impaired. Defining AD purely by its clinical presentation is thus artificial and efforts have been made to recognize the disease based on both clinical and biomarker findings. Advances with biomarkers have also prompted a shift in how the disease is considered as a clinico-pathophysiological entity, with an increasing appreciation that AD should not only be viewed with discrete and defined clinical stages, but as a multifaceted process moving along a seamless continuum. Acknowledging this concept is critical to understanding the development process for disease-modifying therapies, and for initiating effective diagnostic and disease management options. In this article, we discuss the concept of a disease continuum from pathophysiological, biomarker, and clinical perspectives, and highlight the importance of considering AD as a continuum rather than discrete stages. While the pathophysiology of AD has still not been elucidated completely, there is ample evidence to support researchers and clinicians embracing the view of a disease continuum in their study, diagnosis, and management of the disease.
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Affiliation(s)
- Paul S. Aisen
- University of Southern California, San Diego, CA USA
| | - Jeffrey Cummings
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV USA
| | | | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO USA
| | - Reisa Sperling
- Center for Alzheimer’s Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Roy W. Jones
- The Research Institute for the Care of Older People (RICE), Royal United Hospital, Bath, UK
| | | | | | | | - Philip Scheltens
- Department of Neurology & Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Bruno Dubois
- Institute for Memory and Alzheimer’s Disease (IM2A) and ICM, Salpêtrière University Hospital, Paris University (UPMC), Paris, France
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277
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Schreiber S, Schreiber F, Lockhart SN, Horng A, Bejanin A, Landau SM, Jagust WJ. Alzheimer Disease Signature Neurodegeneration and APOE Genotype in Mild Cognitive Impairment With Suspected Non-Alzheimer Disease Pathophysiology. JAMA Neurol 2017; 74:650-659. [PMID: 28319241 DOI: 10.1001/jamaneurol.2016.5349] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Importance There are conflicting results claiming that Alzheimer disease signature neurodegeneration may be more, less, or similarly advanced in individuals with β-amyloid peptide (Aβ)-negative (Aβ-) suspected non-Alzheimer disease pathophysiology (SNAP) than in Aβ-positive (Aβ+) counterparts. Objective To examine patterns of neurodegeneration in individuals with SNAP compared with their Aβ+ counterparts. Design, Setting, and Participants A longitudinal cohort study was conducted among individuals with mild cognitive impairment (MCI) and cognitively normal individuals receiving care at Alzheimer's Disease Neuroimaging Initiative sites in the United States and Canada for a mean follow-up period of 30.5 months from August 1, 2005, to June 30, 2015. Several neurodegeneration biomarkers and longitudinal cognitive function were compared between patients with distinct SNAP (Aβ- and neurodegeneration-positive [Aβ-N+]) subtypes and their Aβ+N+ counterparts. Main Outcomes and Measures Participants were classified according to the results of their florbetapir F-18 (Aβ) positron emission tomography and their Alzheimer disease-associated neurodegeneration status (temporoparietal glucose metabolism determined by fluorodeoxyglucose F 18 [FDG]-labeled positron emission tomography and/or hippocampal volume [HV] determined by magnetic resonance imaging: participants with subthreshold HV values were regarded as exhibiting hippocampal volume atrophy [HV+], while subthreshold mean FDG values were considered as FDG hypometabolism [FDG+]). Results The study comprised 265 cognitively normal individuals (135 women and 130 men; mean [SD] age, 75.5 [6.7] years) and 522 patients with MCI (225 women and 297 men; mean [SD] age, 72.6 [7.8] years). A total of 469 individuals with MCI had data on neurodegeneration biomarkers; of these patients, 107 were Aβ-N+ (22.8%; 63 FDG+, 82 HV+, and 38 FDG+HV+) and 187 were Aβ+N+ (39.9%; 135 FDG+, 147 HV+, and 95 FDG+HV+ cases). A total of 209 cognitively normal participants had data on neurodegeneration biomarkers; of these, 52 were Aβ-N+ (24.9%; 30 FDG+, 33 HV+, and 11 FDG+HV+) and 37 were Aβ+N+ (17.7%; 22 FDG+, 26 HV+, and 11 FDG+HV+). Compared with their Aβ+ counterparts, all patients with MCI SNAP subtypes displayed better preservation of temporoparietal FDG metabolism (mean [SD] FDG: Aβ-N+, 1.25 [0.11] vs Aβ+N+, 1.19 [0.11]), less severe atrophy of the lateral temporal lobe, and lower mean (SD) cerebrospinal fluid levels of tau (59.2 [32.8] vs 111.3 [56.4]). In MCI with SNAP, sustained glucose metabolism and gray matter volume were associated with disproportionately low APOE ε4 (Aβ-N+, 18.7% vs Aβ+N+, 70.6%) and disproportionately high APOE ε2 (18.7% vs 4.8%) carrier prevalence. Slower cognitive decline and lower rates of progression to Alzheimer disease (Aβ-N+, 6.5% vs Aβ+N+, 32.6%) were also seen in patients with MCI with SNAP subtypes compared with their Aβ+ counterparts. In cognitively normal individuals, neurodegeneration biomarkers did not differ between Aβ-N+ and Aβ+N+ cases. Conclusions and Relevance In MCI with SNAP, low APOE ε4 and high APOE ε2 carrier prevalence may account for differences in neurodegeneration patterns between Aβ-N+ and Aβ+N+ cases independent from the neuroimaging biomarker modality used to define neurodegeneration associated with Alzheimer disease.
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Affiliation(s)
- Stefanie Schreiber
- Helen Wills Neuroscience Institute, University of California, Berkeley2Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany3German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Frank Schreiber
- Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany3German Center for Neurodegenerative Diseases, Magdeburg, Germany4Institute of Control Engineering, Technische Universität Braunschweig, Braunschweig, Germany
| | - Samuel N Lockhart
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Andy Horng
- Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Alexandre Bejanin
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley6Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley6Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
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278
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Jacquemont T, De Vico Fallani F, Bertrand A, Epelbaum S, Routier A, Dubois B, Hampel H, Durrleman S, Colliot O. Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment. Neurobiol Aging 2017; 55:177-189. [DOI: 10.1016/j.neurobiolaging.2017.03.023] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 03/17/2017] [Accepted: 03/19/2017] [Indexed: 01/01/2023]
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279
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Dani M, Brooks D, Edison P. Suspected non-Alzheimer's pathology - Is it non-Alzheimer's or non-amyloid? Ageing Res Rev 2017; 36:20-31. [PMID: 28235659 DOI: 10.1016/j.arr.2017.02.003] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 01/04/2017] [Accepted: 02/16/2017] [Indexed: 01/10/2023]
Abstract
Neurodegeneration, the progressive loss of neurons, is a major process involved in dementia and age-related cognitive impairment. It can be detected clinically using currently available biomarker tests. Suspected Non-Alzheimer Pathology (SNAP) is a biomarker-based concept that encompasses a group of individuals with neurodegeneration, but no evidence of amyloid deposition (thereby distinguishing it from Alzheimer's disease (AD)). These individuals may often have a clinical diagnosis of AD, but their clinical features, genetic susceptibility and progression can differ significantly, carrying crucial implications for precise diagnostics, clinical management, and efficacy of clinical drug trials. SNAP has caused wide interest in the dementia research community, because it is still unclear whether it represents distinct pathology separate from AD, or whether in some individuals, it could represent the earliest stage of AD. This debate has raised pertinent questions about the pathways to AD, the need for biomarkers, and the sensitivity of current biomarker tests. In this review, we discuss the biomarker and imaging trials that first recognized SNAP. We describe the pathological correlates of SNAP and comment on the different causes of neurodegeneration. Finally, we discuss the debate around the concept of SNAP, and further unanswered questions that are emerging.
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280
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Mattsson N, Andreasson U, Zetterberg H, Blennow K. Association of Plasma Neurofilament Light With Neurodegeneration in Patients With Alzheimer Disease. JAMA Neurol 2017; 74:557-566. [PMID: 28346578 PMCID: PMC5822204 DOI: 10.1001/jamaneurol.2016.6117] [Citation(s) in RCA: 700] [Impact Index Per Article: 87.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Question What is the importance of plasma neurofilament light in Alzheimer disease? Findings In this case-control study of 193 cognitively healthy controls, 197 patients with mild cognitive impairment, and 180 patients with Alzheimer disease dementia, plasma neurofilament light was associated with Alzheimer disease and correlated with future progression of cognitive decline, brain atrophy, and brain hypometabolism. Meaning Plasma neurofilament light may be a promising noninvasive biomarker for Alzheimer disease. Importance Existing cerebrospinal fluid (CSF) or imaging (tau positron emission tomography) biomarkers for Alzheimer disease (AD) are invasive or expensive. Biomarkers based on standard blood test results would be useful in research, drug development, and clinical practice. Plasma neurofilament light (NFL) has recently been proposed as a blood-based biomarker for neurodegeneration in dementias. Objective To test whether plasma NFL concentrations are increased in AD and associated with cognitive decline, other AD biomarkers, and imaging evidence of neurodegeneration. Design, Setting, and Participants In this prospective case-control study, an ultrasensitive assay was used to measure plasma NFL concentration in 193 cognitively healthy controls, 197 patients with mild cognitive impairment (MCI), and 180 patients with AD dementia from the Alzheimer’s Disease Neuroimaging Initiative. The study dates were September 7, 2005, to February 13, 2012. The plasma NFL analysis was performed in September 2016. Main Outcomes and Measures Associations were tested between plasma NFL and diagnosis, Aβ pathologic features, CSF biomarkers of neuronal injury, cognition, brain structure, and metabolism. Results Among 193 cognitively healthy controls, 197 patients with mild cognitive impairment, and 180 patients with AD with dementia, plasma NFL correlated with CSF NFL (Spearman ρ = 0.59, P < .001). Plasma NFL was increased in patients with MCI (mean, 42.8 ng/L) and patients with AD dementia (mean, 51.0 ng/L) compared with controls (mean, 34.7 ng/L) (P < .001) and had high diagnostic accuracy for patients with AD with dementia vs controls (area under the receiver operating characteristic curve, 0.87, which is comparable to established CSF biomarkers). Plasma NFL was particularly high in patients with MCI and patients with AD dementia with Aβ pathologic features. High plasma NFL correlated with poor cognition and AD-related atrophy (at baseline and longitudinally) and with brain hypometabolism (longitudinally). Conclusions and Relevance Plasma NFL is associated with AD diagnosis and with cognitive, biochemical, and imaging hallmarks of the disease. This finding implies a potential usefulness for plasma NFL as a noninvasive biomarker in AD.
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Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden2Memory Clinic, Skåne University Hospital, Scania, Sweden3Department of Neurology, Skåne University Hospital, Scania, Sweden
| | - Ulf Andreasson
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden5Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Möndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden5Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Möndal, Sweden6Department of Molecular Neuroscience, University College London Institute of Neurology, Queen Square, London, England
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden5Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Möndal, Sweden
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281
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Gold BT, Brown CA, Hakun JG, Shaw LM, Trojanowski JQ, Smith CD. Clinically silent Alzheimer's and vascular pathologies influence brain networks supporting executive function in healthy older adults. Neurobiol Aging 2017; 58:102-111. [PMID: 28719854 DOI: 10.1016/j.neurobiolaging.2017.06.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2017] [Revised: 05/15/2017] [Accepted: 06/18/2017] [Indexed: 12/18/2022]
Abstract
Aging is associated with declines in executive function. We examined how executive functional brain systems are influenced by clinically silent Alzheimer's disease (AD) pathology and cerebral white-matter hyperintensities (WMHs). Twenty-nine younger adults and 34 cognitively normal older adults completed a working memory paradigm while functional magnetic resonance imaging was performed. Older adults further underwent lumbar cerebrospinal fluid draw for the assessment of AD pathology and FLAIR imaging for the assessment of WMHs. Accurate working memory performance in both age groups was associated with high fronto-visual functional connectivity (fC). However, in older adults, higher expression of fronto-visual fC was linked with lower levels of clinically silent AD pathology. In addition, AD pathology and WMHs were each independently related to increased functional magnetic resonance imaging response in the left dorsolateral prefrontal cortex, a pattern associated with slower task performance. Our results suggest that clinically silent AD pathology is related to lower expression of a fronto-visual fC pattern supporting executive task performance. Further, our findings suggest that AD pathology and WMHs appear to be linked with ineffective increases in frontal response in CN older adults.
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Affiliation(s)
- Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA; Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA; Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY, USA.
| | | | - Jonathan G Hakun
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Charles D Smith
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA; Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, KY, USA; Department of Neurology, University of Kentucky, Lexington, KY, USA
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282
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Donohue MC, Sperling RA, Petersen R, Sun CK, Weiner MW, Aisen PS. Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons. JAMA 2017; 317:2305-2316. [PMID: 28609533 PMCID: PMC5736301 DOI: 10.1001/jama.2017.6669] [Citation(s) in RCA: 317] [Impact Index Per Article: 39.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
IMPORTANCE Among cognitively normal individuals, elevated brain amyloid (defined by cerebrospinal fluid assays or positron emission tomography regional summaries) can be related to risk for later Alzheimer-related cognitive decline. OBJECTIVE To characterize and quantify the risk for Alzheimer-related cognitive decline among cognitively normal individuals with elevated brain amyloid. DESIGN, SETTING, AND PARTICIPANTS Exploratory analyses were conducted with longitudinal cognitive and biomarker data from 445 cognitively normal individuals in the United States and Canada. Participants were observed from August 23, 2005, to June 7, 2016, for a median of 3.1 years (interquartile range, 2.0-4.2 years; maximum follow-up, 10.3 years) as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). EXPOSURES Individuals were classified at baseline as having normal (n = 243) or elevated (n = 202) brain amyloid using positron emission tomography amyloid imaging or a cerebrospinal fluid assay of amyloid β. MAIN OUTCOMES AND MEASURES Outcomes included scores on the Preclinical Alzheimer Cognitive Composite (PACC; a sum of 4 baseline standardized z scores, which decreases with worse performance), Mini-Mental State Examination (MMSE; 0 [worst] to 30 [best] points), Clinical Dementia Rating Sum of Boxes (CDR-Sum of Boxes; 0 [best] to 18 [worst] points), and Logical Memory Delayed Recall (0 [worst] to 25 [best] story units). RESULTS Among the 445 participants (243 with normal amyloid, 202 with elevated amyloid), mean (SD) age was 74.0 (5.9) years, mean education was 16.4 (2.7) years, and 52% were women. The mean score for PACC at baseline was 0.00 (2.60); for MMSE, 29.0 (1.2); for CDR-Sum of Boxes, 0.04 (0.14); and for Logical Memory Delayed Recall, 13.1 (3.3). Compared with the group with normal amyloid, those with elevated amyloid had worse mean scores at 4 years on the PACC (mean difference, 1.51 points [95% CI, 0.94-2.10]; P < .001), MMSE (mean difference, 0.56 points [95% CI, 0.32-0.80]; P < .001), and CDR-Sum of Boxes (mean difference, 0.23 points [95% CI, 0.08-0.38]; P = .002). For Logical Memory Delayed Recall, between-group score was not statistically significant at 4 years (mean difference, 0.73 story units [95% CI, -0.02 to 1.48]; P = .056). CONCLUSIONS AND RELEVANCE Exploratory analyses of a cognitively normal cohort followed up for a median of 3.1 years suggest that elevation in baseline brain amyloid level, compared with normal brain amyloid level, was associated with higher likelihood of cognitive decline, although the findings are of uncertain clinical significance. Further research is needed to assess the clinical importance of these differences and measure longer-term associations.
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Affiliation(s)
- Michael C Donohue
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
| | - Reisa A Sperling
- Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts3Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts4Massachusetts General Hospital, Boston
| | | | - Chung-Kai Sun
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California-San Francisco7San Francisco VA Medical Center, San Francisco, California
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
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283
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Harrington KD, Lim YY, Ames D, Hassenstab J, Laws SM, Martins RN, Rainey-Smith S, Robertson J, Rowe CC, Salvado O, Doré V, Villemagne VL, Snyder PJ, Masters CL, Maruff P. Amyloid β-associated cognitive decline in the absence of clinical disease progression and systemic illness. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 8:156-164. [PMID: 28761926 PMCID: PMC5520957 DOI: 10.1016/j.dadm.2017.05.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Introduction High levels of amyloid β (Aβ) are associated with cognitive decline in cognitively normal (CN) older adults. This study investigated the nature of cognitive decline in healthy individuals who did not progress to mild cognitive impairment or dementia. Method Cognition was measured over 72 months and compared between low (Aβ−) and high (Aβ+) CN older adults (n = 335) who did not progress to mild cognitive impairment or dementia and who remained free of severe or uncontrolled systemic illness. Results Compared to the Aβ− group, the Aβ+ group showed no cognitive impairment at baseline but showed substantial decline in verbal learning, episodic memory, and attention over 72 months. Discussion Moderate cognitive decline, particularly for learning and memory, was associated with Aβ+ in CN older adults in the absence of clinical disease progression and uncontrolled or serious comorbid illness.
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Affiliation(s)
- Karra D Harrington
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,Cooperative Research Centre for Mental Health, Parkville, Victoria, Australia
| | - Yen Ying Lim
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,CogState Ltd., Melbourne, Victoria, Australia
| | - David Ames
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.,National Ageing Research Institute, Parkville, Victoria, Australia
| | - Jason Hassenstab
- Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - Simon M Laws
- Cooperative Research Centre for Mental Health, Parkville, Victoria, Australia.,Centre of Excellence for Alzheimer's Disease Research and Care, School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia.,School of Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia
| | - Ralph N Martins
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, Western Australia, Australia
| | - Stephanie Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia.,Sir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, Western Australia, Australia
| | - Joanne Robertson
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging, Austin Health, Melbourne, Victoria, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Olivier Salvado
- CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
| | - Vincent Doré
- Department of Molecular Imaging, Austin Health, Melbourne, Victoria, Australia.,CSIRO Health and Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, Australia
| | - Victor L Villemagne
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,Department of Molecular Imaging, Austin Health, Melbourne, Victoria, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Peter J Snyder
- Department of Neurology, Warren Alpert School of Medicine, Brown University, Providence, RI, USA.,Department of Neurology, Rhode Island Hospital, Alpert Medical School of Brown University, Providence, RI, USA
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Paul Maruff
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,CogState Ltd., Melbourne, Victoria, Australia
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284
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Jack CR, Wiste HJ, Weigand SD, Therneau TM, Knopman DS, Lowe V, Vemuri P, Mielke MM, Roberts RO, Machulda MM, Senjem ML, Gunter JL, Rocca WA, Petersen RC. Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50-95 years: a cross-sectional study. Lancet Neurol 2017; 16:435-444. [PMID: 28456479 PMCID: PMC5516534 DOI: 10.1016/s1474-4422(17)30077-7] [Citation(s) in RCA: 242] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 02/09/2017] [Accepted: 03/06/2017] [Indexed: 12/21/2022]
Abstract
BACKGROUND A new classification for biomarkers in Alzheimer's disease and cognitive ageing research is based on grouping the markers into three categories: amyloid deposition (A), tauopathy (T), and neurodegeneration or neuronal injury (N). Dichotomising these biomarkers as normal or abnormal results in eight possible profiles. We determined the clinical characteristics and prevalence of each ATN profile in cognitively unimpaired individuals aged 50 years and older. METHODS All participants were in the Mayo Clinic Study of Aging, a population-based study that uses a medical records linkage system to enumerate all individuals aged 50-89 years in Olmsted County, MN, USA. Potential participants are randomly selected, stratified by age and sex, and invited to participate in cognitive assessments; individuals without medical contraindications are invited to participate in brain imaging studies. Participants who were judged clinically as having no cognitive impairment and underwent multimodality imaging between Oct 11, 2006, and Oct 5, 2016, were included in the current study. Participants were classified as having normal (A-) or abnormal (A+) amyloid using amyloid PET, normal (T-) or abnormal (T+) tau using tau PET, and normal (N-) or abnormal (N+) neurodegeneration or neuronal injury using cortical thickness assessed by MRI. We used the cutoff points of standard uptake value ratio (SUVR) 1·42 (centiloid 19) for amyloid PET, 1·23 SUVR for tau PET, and 2·67 mm for MRI cortical thickness. Age-specific and sex-specific prevalences of the eight groups were determined using multinomial models combining data from 435 individuals with amyloid PET, tau PET, and MRI assessments, and 1113 individuals who underwent amyloid PET and MRI, but not tau PET imaging. FINDINGS The numbers of participants in each profile group were 165 A-T-N-, 35 A-T+N-, 63 A-T-N+, 19 A-T+N+, 44 A+T-N-, 25 A+T+N-, 35 A+T-N+, and 49 A+T+N+. Age differed by ATN group (p<0·0001), ranging from a median 58 years (IQR 55-64) in A-T-N- and 57 years (54-64) in A-T+N- to a median 80 years (75-84) in A+T-N+ and 79 years (73-87) in A+T+N+. The number of APOE ε4 carriers differed by ATN group (p=0·04), with carriers roughly twice as frequent in each A+ group versus the corresponding A- group. White matter hyperintensity volume (p<0·0001) and cognitive performance (p<0·0001) also differed by ATN group. Tau PET and neurodegeneration biomarkers were discordant in most individuals who would be categorised as stage 2 or 3 preclinical Alzheimer's disease (A+T+N-, A+T-N+, and A+T+N+; 86% at age 65 years and 51% at age 80 years) or with suspected non-Alzheimer's pathophysiology (A-T+N-, A-T-N+, and A-T+N+; 92% at age 65 years and 78% at age 80 years). From age 50 years, A-T-N- prevalence declined and A+T+N+ and A-T+N+ prevalence increased. In both men and women, A-T-N- was the most prevalent until age late 70s. After about age 80 years, A+T+N+ was most prevalent. By age 85 years, more than 90% of men and women had one or more biomarker abnormalities. INTERPRETATION Biomarkers of fibrillar tau deposition can be included with those of β-amyloidosis and neurodegeneration or neuronal injury to more fully characterise the heterogeneous pathological profiles in the population. Both amyloid- dependent and amyloid-independent pathological profiles can be identified in the cognitively unimpaired population. The prevalence of each ATN group changed substantially with age, with progression towards more biomarker abnormalities among individuals who remained cognitively unimpaired. FUNDING National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation.
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Affiliation(s)
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Val Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Rosebud O Roberts
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Jeffrey L Gunter
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Walter A Rocca
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
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285
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Abstract
PURPOSE OF THE REVIEW A wide array of sleep and circadian deficits have been observed in patients with Alzheimer's Disease (AD). However, the vast majority of these studies have focused on later-stage AD, and do not shed light on the possibility that circadian dysfunction contributes to AD pathogenesis. The goal of this review it to examine the evidence supporting or refuting the hypothesis that circadian dysfunction plays an important role in early AD pathogenesis or AD risk in humans. RECENT FINDINGS Few studies have addressed the role of the circadian system in very early AD, or prior to AD diagnosis. AD appears to have a long presymtomatic phase during which pathology is present but cognition remains normal. Studies evaluating circadian function in cognitively-normal elderly or early-stage AD have thus far not incorporated AD biomarkers. Thus, the cause-and-effect relationship between circadian dysfunction and early-stage AD remains unclear. SUMMARY Circadian dysfunction becomes apparent in AD as dementia progresses, but it is unknown at which point in the pathogenic process rhythms begin to deteriorate. Further, it is unknown if exposure to circadian disruption in middle age increases AD risk later in life. This review address gaps in current knowledge on this topic, and proposes several critical directions for future research which might help to clarify the potential pathogenic role of circadian clock dysfunction in AD.
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Affiliation(s)
- Erik S. Musiek
- Dept. of Neurology, Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis MO, USA
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286
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Gordon BA, Blazey T, Su Y, Fagan AM, Holtzman DM, Morris JC, Benzinger TLS. Longitudinal β-Amyloid Deposition and Hippocampal Volume in Preclinical Alzheimer Disease and Suspected Non-Alzheimer Disease Pathophysiology. JAMA Neurol 2017; 73:1192-1200. [PMID: 27548756 DOI: 10.1001/jamaneurol.2016.2642] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Preclinical Alzheimer disease (AD) can be staged using a 2-factor model denoting the presence or absence of β-amyloid (Aβ+/-) and neurodegeneration (ND+/-). The association of these stages with longitudinal biomarker outcomes is unknown. Objective To examine whether longitudinal Aβ accumulation and hippocampal atrophy differ based on initial preclinical staging. Design, Setting, and Participants This longitudinal population-based cohort study used data collected at the Knight Alzheimer Disease Research Center, Washington University, St Louis, Missouri, from December 1, 2006, to June 31, 2015. Cognitively normal older adults (n = 174) were recruited from the longitudinal Adult Children Study and Healthy Aging and Senile Dementia Study at the Knight Alzheimer Disease Research Center. At baseline, all participants had magnetic resonance imaging (MRI) scans, positron emission tomography (PET) scans with carbon 11-labeled Pittsburgh Compound B (PiB), and cerebrospinal fluid assays of tau and phosphorylated tau (ptau) acquired within 12 months. Using the baseline biomarkers, individuals were classified into preclinical stage 0 (Aβ-/ND-), 1 (Aβ+/ND-), or 2+ (Aβ+/ND+) or suspected non-AD pathophysiology (SNAP; Aβ-/ND+). Main Outcomes and Measures Subsequent longitudinal accumulation of Aβ assessed with PiB PET and loss of hippocampal volume assessed with MRI in each group. Results Among the 174 participants (81 men [46.6%]; 93 women [53.4%]; mean [SD] age, 65.7 [8.9] years), a proportion (14%-17%) of individuals with neurodegeneration alone (SNAP) later demonstrated Aβ+. The rates of Aβ accumulation and loss of hippocampal volume in individuals with SNAP were indistinguishable from those without any pathologic features at baseline (for Aβ accumulation: when hippocampal volume was used to define ND, t = 0.00 [P > .99]; when tau and ptau were used to define ND, t = -0.02 [P = .98]; for loss of hippocampal volume: when hippocampal volume was used to define ND, t = -1.34 [P = .18]; when tau and ptau were used to define ND, t = 0.84 [P = .40]). Later preclinical stages (stages 1 and 2+) had elevated Aβ accumulation. Using hippocampal volume to define ND, individuals with stage 1 had accelerated Aβ accumulation relative to stage 0 (t = 11.06; P < .001), stage 2+ (t = 2.10; P = .04), and SNAP (t = 9.32; P < .001), and those with stage 2+ had accelerated Aβ accumulation relative to stage 0 (t = 4.38; P < .001) and SNAP (t = 4.08; P < .001). When ND was defined using tau and ptau, individuals with stage 2+ had accelerated Aβ accumulation relative to stage 0 (t = 4.96) and SNAP (t = 4.06), and those with stage 1 had accelerated Aβ accumulation relative to stage 0 (t = 8.44) and SNAP (t = 6.61) (P < .001 for all comparisons). When ND was defined using cerebrospinal fluid biomarkers, individuals with stage 2+ had accelerated hippocampal atrophy relative to stage 0 (t = -3.41; P < .001), stage 1 (t = -2.48; P = .03), and SNAP (t = -2.26; P = .03). Conclusions and Relevance More advanced preclinical stages of AD have greater longitudinal Aβ accumulation. SNAP appears most likely to capture inherent individual variability in brain structure or to represent comorbid pathologic features rather than early emerging AD. Low hippocampal volumes or elevated levels of tau or ptau in isolation may not accurately represent ongoing neurodegenerative processes.
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Affiliation(s)
- Brian A Gordon
- Department of Radiology, Washington University, St Louis, Missouri2Knight Alzheimer's Disease Research Center, Washington University, St Louis, Missouri
| | - Tyler Blazey
- Division of Biology and Biomedical Sciences, Washington University, St Louis, Missouri
| | - Yi Su
- Department of Radiology, Washington University, St Louis, Missouri
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, Missouri4Department of Neurology, Washington University, St Louis, Missouri5Hope Center for Neurological Disorders, Washington University, St Louis, Missouri
| | - David M Holtzman
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, Missouri3Division of Biology and Biomedical Sciences, Washington University, St Louis, Missouri4Department of Neurology, Washington University, St Louis, Missouri5Hope Center for Neurological Disorders, Washington University, St Louis, Missouri
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, Missouri4Department of Neurology, Washington University, St Louis, Missouri
| | - Tammie L S Benzinger
- Department of Radiology, Washington University, St Louis, Missouri2Knight Alzheimer's Disease Research Center, Washington University, St Louis, Missouri6Department of Neurological Surgery, Washington University, St Louis, Missouri
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287
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Assessment of amyloid β in pathologically confirmed frontotemporal dementia syndromes. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 9:10-20. [PMID: 28653036 PMCID: PMC5473545 DOI: 10.1016/j.dadm.2017.05.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION The diagnostic utility of in vivo amyloid β (Aβ) imaging to aid in the clinical distinction between frontotemporal dementia (FTD) and Alzheimer's disease remains unclear without data on the prevalence and severity of Aβ in pathologically confirmed FTD syndromes. METHODS Aβ was assessed in 98 autopsy-confirmed FTD and 36 control cases, and the pathological accuracy of 11C-Pittsburgh compound B (PiB)-positron emission tomography imaging was assessed in a subset of FTD cases (n = 15). RESULTS Aβ was identified in a similar proportion of FTD syndromes and age-matched controls and increases with age. Alzheimer's disease pathology was identified in all cases with high PiB retention and in one case with low PiB retention. We further demonstrate a strong regional correlation between volume fraction of histological Aβ with PiB standard uptake value ratio scaled to the white matter. DISCUSSION The present study provides a pathologic reference to assist in the interpretation of in vivo assessments in FTD syndromes.
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288
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Soldan A, Pettigrew C, Cai Q, Wang MC, Moghekar AR, O'Brien RJ, Selnes OA, Albert MS. Hypothetical Preclinical Alzheimer Disease Groups and Longitudinal Cognitive Change. JAMA Neurol 2017; 73:698-705. [PMID: 27064267 DOI: 10.1001/jamaneurol.2016.0194] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
IMPORTANCE Clinical trials testing treatments for Alzheimer disease (AD) are increasingly focused on cognitively normal individuals in the preclinical phase of the disease. To optimize observing a treatment effect, such trials need to enroll cognitively normal individuals likely to show cognitive decline over the duration of the trial. OBJECTIVE To identify which group of cognitively normal individuals shows the greatest cognitive decline over time based on their cerebrospinal fluid biomarker profile. DESIGN, SETTING, AND PARTICIPANTS In this cohort study, cognitively normal participants were classified into 1 of the following 4 hypothetical preclinical AD groups using baseline cerebrospinal fluid levels of Aβ and tau or Aβ and phosphorylated tau (p-tau): stage 0 (high Aβ and low tau), stage 1 (low Aβ and low tau), stage 2 (low Aβ and high tau), and suspected non-AD pathology (SNAP) (high Aβ and high tau). The data presented herein were collected between August 1995 and August 2014. MAIN OUTCOMES AND MEASURES An a priori cognitive composite score based on the following 4 tests previously shown to predict progression from normal cognition to symptom onset of mild cognitive impairment or dementia: Paired Associates immediate recall, Logical Memory delayed recall, Boston Naming, and Digit-Symbol Substitution. Linear mixed-effects models were used to compare the cognitive composite scores across the 4 groups over time, adjusting for baseline age, sex, education, and their interactions with time. RESULTS Two hundred twenty-two cognitively normal participants were included in the analyses (mean follow-up, 11.0 years [range, 0-18.3 years] and mean baseline age, 56.9 years [range, 22.1-85.8 years]). Of these, 102 were stage 0, 46 were stage 1, 28 were stage 2, and 46 were SNAP. Individuals in stage 2 (low Aβ and high tau [or p-tau]) had lower baseline cognitive scores and a greater decline in the cognitive composite score relative to the other 3 groups (β ≤ -0.06 for all and P ≤ .001 for the rate of decline for all). Individuals in stage 0, stage 1, and SNAP did not differ from one another in cognitive performance at baseline or over time (11.0 years) and showed practice-related improvement in performance. The APOE ε4 genotype was not associated with baseline cognitive composite score or the rate of change in the cognitive composite score. CONCLUSIONS AND RELEVANCE These results suggest that, to optimize observing a treatment effect, clinical trials enrolling cognitively normal individuals should selectively recruit participants with abnormal levels of both amyloid and tau (ie, stage 2) because this group would be expected to show the greatest cognitive decline over time if untreated.
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Affiliation(s)
- Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Qing Cai
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mei-Cheng Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Abhay R Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Richard J O'Brien
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina
| | - Ola A Selnes
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
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289
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Insel PS, Ossenkoppele R, Gessert D, Jagust W, Landau S, Hansson O, Weiner MW, Mattsson N. Time to Amyloid Positivity and Preclinical Changes in Brain Metabolism, Atrophy, and Cognition: Evidence for Emerging Amyloid Pathology in Alzheimer's Disease. Front Neurosci 2017; 11:281. [PMID: 28567001 PMCID: PMC5434146 DOI: 10.3389/fnins.2017.00281] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 05/01/2017] [Indexed: 01/06/2023] Open
Abstract
Background: Aβ pathology is associated with longitudinal changes of brain metabolism, atrophy, and cognition, in cognitively healthy elders. However, Aβ information is usually measured cross-sectionally and dichotomized to classify subjects as Aβ-positive or Aβ-negative, making it difficult to evaluate when brain and cognitive changes occur with respect to emerging Aβ pathology. In this study, we use longitudinal Aβ information to combine the level and rate of change of Aβ to estimate the time to Aβ-positivity for each subject and test this temporal proximity to significant Aβ pathology for associations with brain structure, metabolism, and cognition. Methods: In 89 cognitively healthy elders with up to 10 years of follow-up, we estimated the points at which rates of fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to the time to Aβ-positivity. Points of initial acceleration in rates of decline were estimated using mixed-effects models with penalized regression splines. Results: Acceleration of rates of FDG PET were observed to occur 20+ years before the conventional threshold for Aβ-positivity. Subtle signs of cognitive dysfunction were observed 10+ years before Aβ-positivity. Conclusions: Aβ may have subtle associations with other hallmarks of Alzheimer's disease before Aβ biomarkers reach conventional thresholds for Aβ-positivity. Therefore, we propose that emerging Aβ pathology occurs many years before cognitively healthy elders reach the current threshold for Aβ positivity (preclinical AD). To allow prevention in the earliest disease stages, AD clinical trials may be designed to also include subjects with Aβ biomarkers in the sub-threshold range.
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Affiliation(s)
- Philip S. Insel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityMalmö, Sweden
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative DiseasesSan Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan Francisco, CA, United States
| | - Rik Ossenkoppele
- Department of Neurology and Alzheimercenter, Neuroscience Campus Amsterdam, VU University Medical CenterAmsterdam, Netherlands
| | - Devon Gessert
- Alzheimer's Therapeutic Research Institute, University of Southern California, San DiegoSan Diego, CA, United States
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California, BerkeleyBerkeley, CA, United States
- Life Sciences Division, Lawrence Berkeley National Laboratory, BerkeleyBerkeley, CA, United States
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, BerkeleyBerkeley, CA, United States
- Life Sciences Division, Lawrence Berkeley National Laboratory, BerkeleyBerkeley, CA, United States
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityMalmö, Sweden
- Memory Clinic, Skåne University HospitalMalmö, Sweden
| | - Michael W. Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative DiseasesSan Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan Francisco, CA, United States
| | - Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityMalmö, Sweden
- Memory Clinic, Skåne University HospitalMalmö, Sweden
- Department of Neurology, Skåne University HospitalLund, Sweden
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290
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Duke Han S, Nguyen CP, Stricker NH, Nation DA. Detectable Neuropsychological Differences in Early Preclinical Alzheimer's Disease: A Meta-Analysis. Neuropsychol Rev 2017; 27:305-325. [PMID: 28497179 DOI: 10.1007/s11065-017-9345-5] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 04/23/2017] [Indexed: 12/20/2022]
Abstract
The development of methods for in vivo detection of cerebral beta amyloid retention and tau accumulation have been increasingly useful in characterizing preclinical Alzheimer's disease (AD). While the association between these biomarkers and eventual AD has been demonstrated among cognitively intact older adults, the link between biomarkers and neurocognitive ability remains unclear. We conducted a meta-analysis to test the hypothesis that cognitively intact older adults would show statistically discernable differences in neuropsychological performance by amyloid status (amyloid negative = A-, amyloid positive = A+). We secondarily hypothesized a third group characterized by either CSF tau pathology or neurodegeneration, in addition to amyloidosis (A+/N+ or Stage 2), would show lower neuropsychology scores than the amyloid positive group (A+/N- or Stage 1) when compared to the amyloid negative group. Pubmed, PsychINFO, and other sources were searched for relevant articles, yielding 775 total sources. After review for inclusion/exclusion criteria, duplicates, and risk of bias, 61 studies were utilized in the final meta-analysis. Results showed A+ was associated with poorer performance in the domains of global cognitive function, memory, language, visuospatial ability, processing speed, and attention/working memory/executive functions when compared to A-. A+/N+ showed lower performances on memory measures when compared to A+/N- in secondary analyses based on a smaller subset of studies. Results support the notion that neuropsychological measures are sensitive to different stages of preclinical AD among cognitively intact older adults. Further research is needed to determine what constitutes meaningful differences in neuropsychological performance among cognitively intact older adults.
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Affiliation(s)
- S Duke Han
- Department of Family Medicine, USC Keck School of Medicine, 1000 S. Fremont Avenue, Unit 22, HSA Building A-6, 4th Floor, Room 6437A, Alhambra, CA, 91803, USA. .,Department of Neurology, USC Keck School of Medicine, Los Angeles, CA, USA. .,Department of Psychology, USC Dornsife College, Los Angeles, CA, USA. .,USC School of Gerontology, Los Angeles, CA, USA.
| | - Caroline P Nguyen
- Department of Family Medicine, USC Keck School of Medicine, 1000 S. Fremont Avenue, Unit 22, HSA Building A-6, 4th Floor, Room 6437A, Alhambra, CA, 91803, USA
| | - Nikki H Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Daniel A Nation
- Department of Psychology, USC Dornsife College, Los Angeles, CA, USA
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291
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Rhodius-Meester HFM, Benedictus MR, Wattjes MP, Barkhof F, Scheltens P, Muller M, van der Flier WM. MRI Visual Ratings of Brain Atrophy and White Matter Hyperintensities across the Spectrum of Cognitive Decline Are Differently Affected by Age and Diagnosis. Front Aging Neurosci 2017; 9:117. [PMID: 28536518 PMCID: PMC5422528 DOI: 10.3389/fnagi.2017.00117] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Accepted: 04/11/2017] [Indexed: 11/13/2022] Open
Abstract
Aim: To assess the associations of age and diagnosis with visual ratings of medial temporal lobe atrophy (MTA), parietal atrophy (PA), global cortical atrophy (GCA), and white matter hyperintensities (WMH) and to investigate their clinical value in a large memory clinic cohort. Methods: We included 2,934 patients (age 67 ± 9 years; 1,391 [47%] female; MMSE 24 ± 5) from the Amsterdam Dementia Cohort (1,347 dementia due to Alzheimer's disease [AD]; 681 mild cognitive impairment [MCI]; 906 controls with subjective cognitive decline). We analyzed the effect of age, APOE e4 and diagnosis on visual ratings using linear regression analyses. Subsequently, we compared diagnostic and predictive value in three age-groups (<65 years, 65-75 years, and >75 years). Results: Linear regression analyses showed main effects of age and diagnosis and an interaction age*diagnosis for MTA, PA, and GCA. For MTA the interaction effect indicated steeper age effects in MCI and AD than in controls. PA and GCA increased with age in MCI and controls, while AD patients have a high score, regardless of age. For WMH we found a main effect of age, but not of diagnosis. For MTA, GCA and PA, diagnostic value was best in patients <65 years (optimal cut-off: ≥1). PA and GCA only discriminated in patients <65 years and MTA in patients <75 years. WMH did not discriminate at all. Taking into account APOE did not affect the identified optimal cut-offs. When we used these scales to predict progression in MCI using Cox proportional hazard models, only MTA (cut-off ≥2) had any predictive value, restricted to patients >75 years. Conclusion: Visual ratings of atrophy and WMH were differently affected by age and diagnosis, requiring an age-specific approach in clinical practice. Their diagnostic value seems strongest in younger patients.
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Affiliation(s)
- Hanneke F M Rhodius-Meester
- Department of Neurology, Alzheimer Center, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands
| | - Marije R Benedictus
- Department of Neurology, Alzheimer Center, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands
| | - Mike P Wattjes
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands.,Institutes of Neurology and Healthcare Engineering, UCLLondon, UK
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands
| | - Majon Muller
- Department of Internal Medicine, Section Geriatrics, VU University Medical CentreAmsterdam, Netherlands
| | - Wiesje M van der Flier
- Department of Neurology, Alzheimer Center, VU University Medical Centre, Amsterdam NeuroscienceAmsterdam, Netherlands.,Department of Epidemiology and Biostatistics, VU University Medical CentreAmsterdam, Netherlands
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292
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Berman SE, Koscik RL, Clark LR, Mueller KD, Bluder L, Galvin JE, Johnson SC. Use of the Quick Dementia Rating System (QDRS) as an Initial Screening Measure in a Longitudinal Cohort at Risk for Alzheimer's Disease. J Alzheimers Dis Rep 2017; 1:9-13. [PMID: 28819654 PMCID: PMC5557032 DOI: 10.3233/adr-170004] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
The Quick Dementia Rating System (QDRS) and Clinical Dementia Rating Scale (CDR) assess global cognitive and functional decline. We evaluated whether the shorter QDRS was a valid screen for problems identified by the CDR in individuals with minimal clinical abnormalities. Agreement between QDRS-Global and CDR-Global was assessed for 54 participants from the Wisconsin Registry for Alzheimer’s Prevention. Resource-savings achieved by adopting an “administer CDR-only-if-QDRS-Global>0” approach were estimated based on 238 subsequent participants. Agreement statistics (concordance = 88.9%) supported use of the QDRS as an initial informant report and modifying center protocol to administer CDRs only when QDRS>0 reduced CDR assessments by 79.8%.
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Affiliation(s)
- Sara E Berman
- Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,Medical Scientist and Neuroscience Training Programs, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Lindsay R Clark
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Kimberly D Mueller
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Lisa Bluder
- Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - James E Galvin
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA
| | - Sterling C Johnson
- Geriatric Research Education and Clinical Center, William. S. Middleton Memorial Veterans Hospital, Madison, WI, USA.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.,Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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293
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Schindler SE, Jasielec MS, Weng H, Hassenstab JJ, Grober E, McCue LM, Morris JC, Holtzman DM, Xiong C, Fagan AM. Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease. Neurobiol Aging 2017; 56:25-32. [PMID: 28482211 DOI: 10.1016/j.neurobiolaging.2017.04.004] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 04/03/2017] [Accepted: 04/07/2017] [Indexed: 10/19/2022]
Abstract
Identifying which neuropsychological measures detect early cognitive changes associated with Alzheimer disease (AD), brain pathology would be helpful clinically for the diagnosis of early AD and for the design of clinical trials. We evaluated which neuropsychological measures in our cognitive battery are most strongly associated with cerebrospinal fluid (CSF) biomarkers of AD brain pathology. We studied a large cohort (n = 233) of middle-to older-aged community-dwelling individuals (mean age 61 years) who had no clinical symptoms of dementia and underwent baseline CSF collection at baseline. Participants completed a battery of 9 neuropsychological measures at baseline and then every 1 to 3 years. CSF tau/Aβ42 was associated with baseline performance on 5/9 neuropsychological measures, especially measures of episodic memory, and longitudinal performance on 7/9 neuropsychological measures, especially measures of global cognition. The free recall portion of the Free and Cued Selective Reminding Task (FCSRT-free) detected declining cognition in the high CSF tau/Aβ42 group the earliest, followed by another measure of episodic memory and a sequencing task.
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Affiliation(s)
- Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Mateusz S Jasielec
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Hua Weng
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jason J Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Ellen Grober
- Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
| | - Lena M McCue
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
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294
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Brugulat-Serrat A, Rojas S, Bargalló N, Conesa G, Minguillón C, Fauria K, Gramunt N, Molinuevo JL, Gispert JD. Incidental findings on brain MRI of cognitively normal first-degree descendants of patients with Alzheimer's disease: a cross-sectional analysis from the ALFA (Alzheimer and Families) project. BMJ Open 2017; 7:e013215. [PMID: 28341686 PMCID: PMC5372150 DOI: 10.1136/bmjopen-2016-013215] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
OBJECTIVES To describe the prevalence of brain MRI incidental findings (IF) in a cohort of cognitively normal first-degree descendants of patients with Alzheimer's disease (AD). DESIGN Cross-sectional observational study. SETTING All scans were obtained with a 3.0 T scanner. Scans were evaluated by a single neuroradiologist and IF recorded and categorised. The presence of white matter hyperintensities (WMH) was determined with the Fazekas scale and reported as relevant if ≥2. PARTICIPANTS 575 participants (45-75 years) underwent high-resolution structural brain MRI. Participants were cognitively normal and scored over the respective cut-off values in all the following neuropsychological tests: Mini-Mental State Examination (≥26), Memory Impairment Screen (≥6), Time Orientation Subtest of the Barcelona Test II (≥68), verbal semantic fluency (naming animals ≥12). Clinical Dementia Rating (CDR) had to be 0. RESULTS 155 participants (27.0%) presented with at least one IF. Relevant WMH were present in 7.8% of the participants, and vascular abnormalities, cyst and brain volume loss in 10.7%, 3.1% and 6.9% of the study volunteers, respectively. Neoplastic brain findings were found in 2.4% of participants and within these, meningiomas were the most common (1.7%) and more frequently found in women. A positive correlation between increasing age and the presence of IF was found. Additionally, brain atrophy greater than that expected by age was significantly more prevalent in participants without a parental history of AD. CONCLUSIONS Brain MRIs of healthy middle-aged participants show a relatively high prevalence of IF even when study participants have been screened for subtle cognitive alterations. Most of our participants are first-degree descendants of patients with AD, and therefore these results are of special relevance for novel imaging studies in the context of AD prevention in cognitively healthy middle-aged participants. TRIAL REGISTRATION NUMBER NCT02198586.
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Affiliation(s)
- Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Santiago Rojas
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Unit of Human Anatomy and Embryology, Faculty of Medicine, Department of Morphological Sciences, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Nuria Bargalló
- Magnetic Resonance Imaging Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centre Mèdic Diagnòstic Alomar, Barcelona, Spain
| | - Gerardo Conesa
- Servicio de Neurocirugía, Hospital del Mar, Barcelona, Spain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Nina Gramunt
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
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295
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Abner EL, Kryscio RJ, Schmitt FA, Fardo DW, Moga DC, Ighodaro ET, Jicha GA, Yu L, Dodge HH, Xiong C, Woltjer RL, Schneider JA, Cairns NJ, Bennett DA, Nelson PT. Outcomes after diagnosis of mild cognitive impairment in a large autopsy series. Ann Neurol 2017; 81:549-559. [PMID: 28224671 DOI: 10.1002/ana.24903] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 02/20/2017] [Accepted: 02/20/2017] [Indexed: 11/10/2022]
Abstract
OBJECTIVE To determine clinical and neuropathological outcomes following a clinical diagnosis of mild cognitive impairment (MCI). METHODS Data were drawn from a large autopsy series (N = 1,337) of individuals followed longitudinally from normal or MCI status to death, derived from 4 Alzheimer Disease (AD) Centers in the United States. RESULTS Mean follow-up was 7.9 years. Of the 874 individuals ever diagnosed with MCI, final clinical diagnoses were varied: 39.2% died with an MCI diagnosis, 46.8% with a dementia diagnosis, and 13.9% with a diagnosis of intact cognition. The latter group had pathological features resembling those with a final clinical diagnosis of MCI. In terms of non-AD pathologies, both primary age-related tauopathy (p < 0.05) and brain arteriolosclerosis pathology (p < 0.001) were more severe in MCI than cognitively intact controls. Among the group that remained MCI until death, mixed AD neuropathologic changes (ADNC; ≥1 comorbid pathology) were more frequent than "pure" ADNC pathology (55% vs 22%); suspected non-Alzheimer pathology comprised the remaining 22% of cases. A majority (74%) of subjects who died with MCI were without "high"-level ADNC, Lewy body disease, or hippocampal sclerosis pathologies; this group was enriched in cerebrovascular pathologies. Subjects who died with dementia and were without severe neurodegenerative pathologies tended to have cerebrovascular pathology and carry the MCI diagnosis for a longer interval. INTERPRETATION MCI diagnosis usually was associated with comorbid neuropathologies; less than one-quarter of MCI cases showed "pure" AD at autopsy. Ann Neurol 2017;81:549-559.
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Affiliation(s)
- Erin L Abner
- Department of Epidemiology, University of Kentucky, Lexington, KY
| | | | | | - David W Fardo
- Department of Biostatistics, University of Kentucky, Lexington, KY
| | - Daniela C Moga
- Department of Pharmacy Practice and Science, University of Kentucky, Lexington, KY
| | - Eseosa T Ighodaro
- Department of Anatomy and Neurobiology, University of Kentucky, Lexington, KY
| | - Gregory A Jicha
- Department of Neurology, University of Kentucky, Lexington, KY
| | - Lei Yu
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL
| | - Hiroko H Dodge
- Department of Neurology, Oregon Health & Science University, Portland, OR
| | - Chengjie Xiong
- Division of Biostatistics, Washington University, St Louis, MO
| | - Randall L Woltjer
- Department of Pathology, Oregon Health & Science University, Portland, OR
| | - Julie A Schneider
- Department of Pathology, Rush University Medical Center, Chicago, IL
| | - Nigel J Cairns
- Department of Neurology, Washington University, St Louis, MO
| | - David A Bennett
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL
| | - Peter T Nelson
- Department of Pathology, University of Kentucky, Lexington, KY
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296
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Huynh RA, Mohan C. Alzheimer's Disease: Biomarkers in the Genome, Blood, and Cerebrospinal Fluid. Front Neurol 2017; 8:102. [PMID: 28373857 PMCID: PMC5357660 DOI: 10.3389/fneur.2017.00102] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 03/01/2017] [Indexed: 01/20/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that slowly destroys memory and thinking skills, resulting in behavioral changes. It is estimated that nearly 36 million are affected globally with numbers reaching 115 million by 2050. AD can only be definitively diagnosed at autopsy since its manifestations of senile plaques and neurofibrillary tangles throughout the brain cannot yet be fully captured with current imaging technologies. Current AD therapeutics have also been suboptimal. Besides identifying markers that distinguish AD from controls, there has been a recent drive to identify better biomarkers that can predict the rates of cognitive decline and neocortical amyloid burden in those who exhibit preclinical, prodromal, or clinical AD. This review covers biomarkers of three main types: genes, cerebrospinal fluid-derived, and blood-derived biomarkers. Looking ahead, cutting-edge OMICs technologies, including proteomics and metabolomics, ought to be fully tapped in order to mine even better biomarkers for AD that are more predictive.
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Affiliation(s)
- Rose Ann Huynh
- Department of Biomedical Engineering, University of Houston , Houston, TX , USA
| | - Chandra Mohan
- Department of Biomedical Engineering, University of Houston , Houston, TX , USA
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297
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Grober E, Wakefield D, Ehrlich AR, Mabie P, Lipton RB. Identifying memory impairment and early dementia in primary care. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2017; 6:188-195. [PMID: 28289701 PMCID: PMC5338866 DOI: 10.1016/j.dadm.2017.01.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
INTRODUCTION This study examined the operating characteristics of two-stage case finding to identify memory impairment and very mild dementia. METHODS Primary care patients underwent two-stage testing and a subsequent diagnostic assessment to assess outcomes. Patients who screen positive for subjective cognitive decline on the Informant Questionnaire on Cognitive Decline in the Elderly undergo memory testing with the Free and Cued Selective Reminding Test with Immediate Recall. Outcomes were determined without access to these data. A split-half design with discovery and confirmatory samples was used. RESULTS One hundred seventeen of 563 (21%) patients had dementia and 68 (12%) had memory impairment but not dementia. Operating characteristics were similar in the discovery and confirmatory samples. In the pooled sample, combined, patients with memory impairment or dementia were identified with good sensitivity (72%) and high specificity (90%). Differences in ethnicity, educational level, or age (≤75, >75) did not affect classification accuracy. DISCUSSION Two-stage screening facilitates the efficient identification of older adults with memory impairment or dementia.
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Affiliation(s)
- Ellen Grober
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
| | | | - Amy R. Ehrlich
- Division of Geriatrics, Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
| | - Peter Mabie
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
| | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
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298
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299
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Millar PR, Balota DA, Maddox GB, Duchek JM, Aschenbrenner AJ, Fagan AM, Benzinger TLS, Morris JC. Process dissociation analyses of memory changes in healthy aging, preclinical, and very mild Alzheimer disease: Evidence for isolated recollection deficits. Neuropsychology 2017; 31:708-723. [PMID: 28206782 DOI: 10.1037/neu0000352] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE Recollection and familiarity are independent processes that contribute to memory performance. Recollection is dependent on attentional control, which has been shown to be disrupted in early stage Alzheimer's disease (AD), whereas familiarity is independent of attention. The present longitudinal study examines the sensitivity of recollection estimates based on Jacoby's (1991) process dissociation procedure to AD-related biomarkers in a large sample of well-characterized cognitively normal middle-aged and older adults (N = 519) and the extent to which recollection discriminates these individuals from individuals with very mild symptomatic AD (N = 64). METHOD Participants studied word pairs (e.g., knee bone), then completed a primed, explicit, cued fragment-completion memory task (e.g., knee b_n_). Primes were either congruent with the correct response (e.g., bone), incongruent (e.g., bend), or neutral (e.g., &&&). This design allowed for the estimation of independent contributions of recollection and familiarity processes, using the process dissociation procedure. RESULTS Recollection, but not familiarity, was impaired in healthy aging and in very mild AD. Recollection discriminated cognitively normal individuals from the earliest detectable stage of symptomatic AD above and beyond standard psychometric tests. In cognitively normal individuals, baseline CSF measures indicative of AD pathology were related to lower initial recollection and less practice-related improvement in recollection over time. Finally, presence of amyloid plaques, as imaged by PIB-PET, was also related to less improvement in recollection over time. CONCLUSIONS These findings suggest that attention-demanding memory processes, such as recollection, may be particularly sensitive to both symptomatic and preclinical AD pathology. (PsycINFO Database Record
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Affiliation(s)
- Peter R Millar
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | - David A Balota
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | | | - Janet M Duchek
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | | | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis
| | - Tammie L S Benzinger
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. Louis
| | - John C Morris
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. Louis
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300
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Epelbaum S, Genthon R, Cavedo E, Habert MO, Lamari F, Gagliardi G, Lista S, Teichmann M, Bakardjian H, Hampel H, Dubois B. Preclinical Alzheimer's disease: A systematic review of the cohorts underlying the concept. Alzheimers Dement 2017; 13:454-467. [PMID: 28188032 DOI: 10.1016/j.jalz.2016.12.003] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Revised: 10/25/2016] [Accepted: 12/08/2016] [Indexed: 12/20/2022]
Abstract
Preclinical Alzheimer's disease (AD) is a relatively recent concept describing an entity characterized by the presence of a pathophysiological biomarker signature characteristic for AD in the absence of specific clinical symptoms. There is rising interest in the scientific community to define such an early target population mainly because of failures of all recent clinical trials despite evidence of biological effects on brain amyloidosis for some compounds. A conceptual framework has recently been proposed for this preclinical phase of AD. However, few data exist on this silent stage of AD. We performed a systematic review to investigate how the concept is defined across studies. The review highlights the substantial heterogeneity concerning the three main determinants of preclinical AD: "normal cognition," "cognitive decline," and "AD pathophysiological signature." We emphasize the need for a harmonized nomenclature of the preclinical AD concept and standardized population-based and case-control studies using unified operationalized criteria.
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Affiliation(s)
- Stéphane Epelbaum
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France.
| | - Rémy Genthon
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Enrica Cavedo
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Marie Odile Habert
- ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France; AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de médecine nucléaire, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Foudil Lamari
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Laboratoire de Biochimie, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Geoffroy Gagliardi
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France
| | - Simone Lista
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; IHU-A-ICM, Paris Institute of Translational Neurosciences, Hôpital de la Pitié-Salpêtrière, Paris, France; AXA Research Fund & UPMC Chair, Paris, France
| | - Marc Teichmann
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France
| | - Hovagim Bakardjian
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; IHU-A-ICM, Paris Institute of Translational Neurosciences, Hôpital de la Pitié-Salpêtrière, Paris, France; AXA Research Fund & UPMC Chair, Paris, France
| | - Harald Hampel
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France; AXA Research Fund & UPMC Chair, Paris, France
| | - Bruno Dubois
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Département de Neurologie, Institut de la mémoire et de la maladie d'Alzheimer, Groupe Hospitalier Pitié-Salpêtrière, Paris, France; ICM, CNRS UMR 7225, Inserm U 1127, UPMC-P6 UMR S 1127, GH Pitié-Salpêtrière, Paris, France
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