Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum
Language English Country United States Media print
Document type Journal Article
Grant support
R01 NS104147
NINDS NIH HHS - United States
U01 AG032438
NIA NIH HHS - United States
R01 AG031581
NIA NIH HHS - United States
G84/6523
Medical Research Council - United Kingdom
P30 AG062422
NIA NIH HHS - United States
P01 AG036694
NIA NIH HHS - United States
U01 AG024904
NIA NIH HHS - United States
PubMed
35099509
PubMed Central
PMC12138908
DOI
10.1001/jamaneurol.2021.5216
PII: 2788270
Knihovny.cz E-resources
- MeSH
- Alzheimer Disease * cerebrospinal fluid diagnostic imaging epidemiology MeSH
- Amyloid beta-Peptides cerebrospinal fluid MeSH
- Amyloidogenic Proteins MeSH
- Amyloidosis * MeSH
- Apolipoproteins E genetics MeSH
- Biomarkers cerebrospinal fluid MeSH
- Cognitive Dysfunction * diagnostic imaging epidemiology MeSH
- Middle Aged MeSH
- Humans MeSH
- Peptide Fragments cerebrospinal fluid MeSH
- Positron-Emission Tomography MeSH
- Prevalence MeSH
- tau Proteins cerebrospinal fluid MeSH
- Cross-Sectional Studies MeSH
- Aged MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Amyloid beta-Peptides MeSH
- Amyloidogenic Proteins MeSH
- Apolipoproteins E MeSH
- Biomarkers MeSH
- Peptide Fragments MeSH
- tau Proteins MeSH
IMPORTANCE: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. OBJECTIVE: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. EXPOSURES: Alzheimer disease biomarkers detected on PET or in CSF. MAIN OUTCOMES AND MEASURES: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. RESULTS: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18). CONCLUSIONS AND RELEVANCE: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
Aix Marseille Univ INSERM Institut de Neurosciences des Systèmes Marseille France
Avid Radiopharmaceuticals Philadelphia Pennsylvania
Banner Alzheimer's Institute Phoenix Arizona
Biogen Cambridge Massachusetts
Brain Health Imaging Institute Department of Radiology Weill Cornell Medicine New York New York
BrainNow Research Institute Guangdong Province Shenzhen China
Center for Neuroscience and Cell Biology University of Coimbra Coimbra Portugal
Center for Neurosciences Vrije Universiteit Brussel Brussels Belgium
Center for Research and Advanced Therapies CITA Alzheimer Foundation Donostia San Sebastian Spain
Centre de Référence Démences Rares Pitié Salpêtrière University Hospital AP HP Paris France
Centre for Age Related Medicine Stavanger University Hospital Stavanger Norway
Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas Madrid Spain
Chang Gung Memorial Foundation Linkou Taoyuan Taiwan
Clinical Memory Research Unit Department of Clinical Sciences Malmö Lund University Lund Sweden
Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden
Department of Biochemical Diagnostics University Hospital of Białystok Białystok Poland
Department of Biochemistry Postgraduate Institute of Medical Education and Research Chandigarh India
Department of Brain Sciences Imperial College London London United Kingdom
Department of Clinical Medicine University of Copenhagen Copenhagen Denmark
Department of Experimental Diagnostic and Specialty Medicine University of Bologna Bologna Spain
Department of Health Sciences University of Genoa Genoa Italy
Department of Imaging and Pathology Katholieke Universiteit Leuven Leuven Belgium
Department of Molecular and Translational Medicine University of Brescia Brescia Italy
Department of Molecular Imaging Austin Health Melbourne Victoria Australia
Department of Neurobiology Care Sciences and Society Karolinska Institutet Stockholm Sweden
Department of Neurodegeneration Diagnostics Medical University of Białystok Białystok Poland
Department of Neurodegenerative Diseases and Geriatric Psychiatry University of Bonn Bonn Germany
Department of Neurology Akershus University Hospital Lorenskog Norway
Department of Neurology Cliniques Universitaires Saint Luc Brussels Belgium
Department of Neurology Fundación Jiménez Díaz Madrid Spain
Department of Neurology Institute of Clinical Medicine University of Eastern Finland Kuopio Finland
Department of Neurology Medical Center Zaloska 7 Ljubljana Slovenia
Department of Neurology Osaka City University Graduate School of Medicine Osaka Japan
Department of Neurology University Hospital Basel Basel Switzerland
Department of Neurology University Hospital Leiden Leiden the Netherlands
Department of Neurology University Hospital of Trondheim Trondheim Norway
Department of Neurology University Medical Centre Ljubljana Ljubljana Slovenia
Department of Neurology University of Pennsylvania Philadelphia
Department of Neurology University of Pittsburgh Pittsburgh Pennsylvania
Department of Neurology Washington University School of Medicine in St Louis St Louis Missouri
Department of Neuropsychiatry Seoul National University Hospital Seoul South Korea
Department of Nuclear Medicine Klinikum Bayreuth Bayreuth Germany
Department of Nuclear Medicine Positron Emission Tomography Centre Aarhus University Aarhus Denmark
Department of Nuclear Medicine University Hospital of Cologne Cologne Germany
Department of Nuclear Medicine University Hospital of Leipzig Leipzig Germany
Department of Psychiatry and Psychotherapy University Medical Center Göttingen Göttingen Germany
Department of Psychiatry Faculty of Medicine McGill University Montreal Quebec Canada
Department of Psychiatry Massachusetts General Hospital Boston
Department of Psychiatry Medical Faculty University of Cologne Cologne Germany
Department of Psychiatry University of Pittsburgh School of Medicine Pittsburgh Pennsylvania
Department of Public Health and Caring Sciences Geriatrics Uppsala University Uppsala Sweden
Department of Radiation Oncology Emory University Atlanta Georgia
Department of Radiology Massachusetts General Hospital Boston
Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia
Deutsches Zentrum für Neurodegenerative Erkrankungen e 5 Bonn Germany
DIMES University of Bologna Bologna Italy
DINOGMI University of Genoa Genoa Italy
Division of Geriatrics University of Goettingen Medical School Goettingen Germany
Division of Infectious Diseases and Immunology University of Massachusetts Medical School Worcester
Division of Nuclear Medicine and Molecular Imaging University Hospitals Leuven Leuven Belgium
Douglas Mental Health University Institute Montreal Quebec Canada
Eli Lilly and Company Indianapolis Indiana
Faculty of Medicine University of Coimbra Azinhaga de Santa Comba Coimbra Portugal
Faculty of Medicine University of Lisboa Lisboa Portugal
Florey Department of Neuroscience University of Melbourne Melbourne Victoria Australia
Greek Association of Alzheimer's Disease and Related Disorders Thessaloniki Greece
Harvard Aging Brain Study Department of Neurology Harvard Medical School Boston Massachusetts
Helen Wills Neuroscience Institute University of California Berkeley Berkeley
Hong Kong Center for Neurodegenerative Diseases Hong Kong China
Institute of Clinical Medicine Neurology University of Eastern Finland Kuopio Finland
Istituto delle Scienze Neurologiche di Bologna IRCCS Bologna Italy
Klinik für Psychiatrie und Psychotherapie Charité Universitätsmedizin Berlin CBF Berlin Deutschland
Klinikum Bremen Ost University of Oldenburg Institute of Psychology Oldenburg Germany
Laboratory for Cognitive Neurology Department of Neurosciences University of Leuven Leuven Belgium
Life Molecular Imaging GmbH Berlin Germany
McConnell Brain Imaging Centre Montreal Neurological Institute Montreal Quebec Canada
Memory and Aging Center Department of Neurology University of California San Francisco San Francisco
Memory Clinic and Longevity Medicine Ana Aslan International Foundation Bucharest Romania
Memory Clinic Department of Geriatrics Uppsala University Hospital Uppsala Sweden
Memory Clinic University Department of Geriatric Medicine Felix Platter Hospital Basel Switzerland
Memory Clinic University Hospitals and University of Geneva Geneva Switzerland
Memory Disorder Unit Copenhagen University Hospital Copenhagen Denmark
Memory Unit Neurology Department Hospital de la Santa Creu i Sant Pau Barcelona Spain
Molecular Biomarkers in Psychiatry University of Pittsburgh Pittsburgh Pennsylvania
Neurobiology Research Unit Copenhagen University Hospital Copenhagen Denmark
Neurocenter Department of Neurology Kuopio University Hospital Kuopio Finland
Neurocenter Neurology Kuopio University Hospital Kuopio Finland
Neurology Department Hospital Universitario Marqués de Valdecilla and IDIVAL Santander Spain
Neurology Department University Hospitals Leuven Leuven Belgium
Neuroscience Center Samsung Medical Center Seoul South Korea
Ospedale Policlinico San Martino IRCCS Genoa Italy
Radboudumc Alzheimer Centre Radboud University Medical Center Nijmegen the Netherlands
Reference Center for Biological Markers of Dementia University of Antwerp Antwerp Belgium
School of Medical Sciences Örebro University Örebro Sweden
School of Psychology Faculty of Science The University of Sydney Sydney New South Wales Australia
Section for Geriatric Psychiatry University of Heidelberg Heidelberg Germany
Service of Neurology University Hospital Marqués de Valdecilla IDIVAL CIBERNED Santander Spain
Studies on Prevention of Alzheimer's Disease Centre Montreal Quebec Canada
Translational and Clinical Research Institute University of Newcastle upon Tyne United Kingdom
Translational Neuroscience Laboratory McLean Hospital Harvard Medical School Belmont Massachusetts
Turku PET Centre Turku Finland
Turku PET Centre University of Turku Turku Finland
UK Dementia Research Institute London United Kingdom
Unite Mixte de Recherche INSERM U930 French National Centre for Scientific Research ERL Tours France
Université de Paris Paris Université Paris Saclay BioMaps CEA CNRS INSERM Orsay France
See more in PubMed
Jack CR Jr, Bennett DA, Blennow K, et al.; Contributors. NIA-AA research framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–562. doi:10.1016/j.jalz.2018.02.018 PubMed DOI PMC
Scheltens P, De Strooper B, Kivipelto M, et al. Alzheimer’s disease. Lancet. 2021;397(10284):1577–1590. doi:10.1016/S0140-6736(20)32205-4 PubMed DOI PMC
Feldman HH, Haas M, Gandy S, et al.; One Mind for Research and the New York Academy of Sciences. Alzheimer’s disease research and development: a call for a new research roadmap. Ann N Y Acad Sci. 2014;1313:1–16. doi:10.1111/nyas.12424 PubMed DOI
Reiman EM, Langbaum JB, Tariot PN, et al. CAP–advancing the evaluation of preclinical Alzheimer disease treatments. Nat Rev Neurol. 2016;12(1):56–61. doi:10.1038/nrneurol.2015.177 PubMed DOI PMC
Sperling RA, Rentz DM, Johnson KA, et al. The A4 study: stopping AD before symptoms begin? Sci Transl Med. 2014;6(228):228fs13. doi:10.1126/scitranslmed.3007941 PubMed DOI PMC
Jansen WJ, Ossenkoppele R, Knol DL, et al.; Amyloid Biomarker Study Group. Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. JAMA. 2015;313(19):1924–1938. doi:10.1001/jama.2015.4668 PubMed DOI PMC
Ossenkoppele R, Jansen WJ, Rabinovici GD, et al.; Amyloid PET Study Group. Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA. 2015;313(19):1939–1949. doi:10.1001/jama.2015.4669 PubMed DOI PMC
Mattsson N, Andreasson U, Persson S, et al. The Alzheimer’s Association external quality control program for cerebrospinal fluid biomarkers. Alzheimers Dement. 2011;7(4):386–395.e6. doi:10.1016/j.jalz.2011.05.2243 PubMed DOI PMC
Vos SJ, Visser PJ, Verhey F, et al. Variability of CSF Alzheimer’s disease biomarkers: implications for clinical practice. PLoS One. 2014;9(6):e100784. doi:10.1371/journal.pone.0100784 PubMed DOI PMC
Dubois B, Villain N, Frisoni GB, et al. Clinical diagnosis of Alzheimer’s disease: recommendations of the International Working Group. Lancet Neurol. 2021;20(6):484–496. doi:10.1016/S1474-4422(21)00066-1 PubMed DOI PMC
Schindler SE, Sutphen CL, Teunissen C, et al. Upward drift in cerebrospinal fluid amyloid β 42 assay values for more than 10 years. Alzheimers Dement. 2018;14(1):62–70. doi:10.1016/j.jalz.2017.06.2264 PubMed DOI PMC
Tijms BM, Willemse EAJ, Zwan MD, et al. Unbiased approach to counteract upward drift in cerebrospinal fluid amyloid-β 1–42 analysis results. Clin Chem. 2018;64(3):576–585. doi:10.1373/clinchem.2017.281055 PubMed DOI
Bertens D, Tijms BM, Scheltens P, Teunissen CE, Visser PJ. Unbiased estimates of cerebrospinal fluid β-amyloid 1–42 cutoffs in a large memory clinic population. Alzheimers Res Ther. 2017;9(1):8. doi:10.1186/s13195-016-0233-7 PubMed DOI PMC
Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med. 2004;256(3):183–194. doi:10.1111/j.1365-2796.2004.01388.x PubMed DOI
Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment–beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med. 2004;256(3):240–246. doi:10.1111/j.1365-2796.2004.01380.x PubMed DOI
De Meyer G, Shapiro F, Vanderstichele H, et al.; Alzheimer’s Disease Neuroimaging Initiative. Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people. Arch Neurol. 2010;67(8):949–956. doi:10.1001/archneurol.2010.179 PubMed DOI PMC
Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. 2010;21(4):467–474. doi:10.1097/EDE.0b013e3181caeb90 PubMed DOI
Palmqvist S, Mattsson N, Hansson O; Alzheimer’s Disease Neuroimaging Initiative. Cerebrospinal fluid analysis detects cerebral amyloid-β accumulation earlier than positron emission tomography. Brain. 2016;139(pt 4):1226–1236. doi:10.1093/brain/aww015 PubMed DOI PMC
Reimand J, de Wilde A, Teunissen CE, et al. PET and CSF amyloid-β status are differently predicted by patient features: information from discordant cases. Alzheimers Res Ther. 2019;11(1):100. doi:10.1186/s13195-019-0561-5 PubMed DOI PMC
Lewczuk P, Riederer P, O’Bryant SE, et al.; Members of the WFSBP Task Force Working on this Topic: Peter Riederer, Carla Gallo, Dimitrios Kapogiannis, Andrea Lopez Mato, Florence Thibaut. Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: an update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry. World J Biol Psychiatry. 2018;19(4):244–328. doi:10.1080/15622975.2017.1375556 PubMed DOI PMC
Reimand J, Collij L, Scheltens P, Bouwman F, Ossenkoppele R; Alzheimer’s Disease Neuroimaging Initiative. Association of amyloid-β CSF/PET discordance and tau load 5 years later. Neurology. 2020;95(19):e2648–e2657. doi:10.1212/WNL.0000000000010739 PubMed DOI PMC
Johnson KA, Sperling RA, Gidicsin CM, et al.; AV45-A11 study group. Florbetapir (F18-AV-45) PET to assess amyloid burden in Alzheimer’s disease dementia, mild cognitive impairment, and normal aging. Alzheimers Dement. 2013;9(5, suppl):S72–S83. doi:10.1016/j.jalz.2012.10.007 PubMed DOI PMC
Bucci M, Savitcheva I, Farrar G, et al. A multisite analysis of the concordance between visual image interpretation and quantitative analysis of [18F]flutemetamol amyloid PET images. Eur J Nucl Med Mol Imaging. 2021;48(7):2183–2199. doi:10.1007/s00259-021-05311-5 PubMed DOI PMC
Sala A, Nordberg A, Rodriguez-Vieitez E; Alzheimer’s Disease Neuroimaging Initiative. Longitudinal pathways of cerebrospinal fluid and positron emission tomography biomarkers of amyloid-β positivity. Mol Psychiatry. Published online December 11, 2020. doi:10.1038/s41380-020-00950-w PubMed DOI PMC
Chételat G, Arbizu J, Barthel H, et al. Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer’s disease and other dementias. Lancet Neurol. 2020;19(11):951–962. doi:10.1016/S1474-4422(20)30314-8 PubMed DOI
Landau SM, Lu M, Joshi AD, et al.; Alzheimer’s Disease Neuroimaging Initiative. Comparing positron emission tomography imaging and cerebrospinal fluid measurements of β-amyloid. Ann Neurol. 2013;74(6):826–836. doi:10.1002/ana.23908 PubMed DOI PMC
Roberts RO, Aakre JA, Kremers WK, et al. Prevalence and outcomes of amyloid positivity among persons without dementia in a longitudinal, population-based setting. JAMA Neurol. 2018;75 (8):970–979. doi:10.1001/jamaneurol.2018.0629 PubMed DOI PMC
Mielke MM, Wiste HJ, Weigand SD, et al. Indicators of amyloid burden in a population-based study of cognitively normal elderly. Neurology. 2012;79(15):1570–1577. doi:10.1212/WNL.0b013e31826e2696 PubMed DOI PMC
Morris JC, Roe CM, Xiong C, et al. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol. 2010;67(1):122–131. doi:10.1002/ana.21843 PubMed DOI PMC
Rowe CC, Ellis KA, Rimajova M, et al. Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Neurobiol Aging. 2010;31(8):1275–1283. doi:10.1016/j.neurobiolaging.2010.04.007 PubMed DOI
Safieh M, Korczyn AD, Michaelson DM. ApoE4: an emerging therapeutic target for Alzheimer’s disease. BMC Med. 2019;17(1):64. doi:10.1186/s12916-019-1299-4 PubMed DOI PMC
Insel PS, Hansson O, Mattsson-Carlgren N. Association between apolipoprotein E ε2 vs ε4, age, and β-amyloid in adults without cognitive impairment. JAMA Neurol. 2021;78(2):229–235. doi:10.1001/jamaneurol.2020.3780 PubMed DOI PMC
Jack CR Jr, Wiste HJ, Weigand SD, et al. Age, sex, and APOE ε4 effects on memory, brain structure, and β-amyloid across the adult life span. JAMA Neurol. 2015;72(5):511–519. doi:10.1001/jamaneurol.2014.4821 PubMed DOI PMC
Stern Y Cognitive reserve and Alzheimer disease. Alzheimer Dis Assoc Disord. 2006;20(3, suppl 2):S69–S74. doi:10.1097/00002093-200607001-00010 PubMed DOI
Jansen WJ, Ossenkoppele R, Tijms BM, et al.; Amyloid Biomarker Study Group. Association of cerebral amyloid-β aggregation with cognitive functioning in persons without dementia. JAMA Psychiatry. 2018;75(1):84–95. doi:10.1001/jamapsychiatry.2017.3391 PubMed DOI PMC
Jack CR Jr, Wiste HJ, Lesnick TG, et al. Brain β-amyloid load approaches a plateau. Neurology. 2013;80(10):890–896. doi:10.1212/WNL.0b013e3182840bbe PubMed DOI PMC
Thomas D, Radji S, Benedetti A. Systematic review of methods for individual patient data meta-analysis with binary outcomes. BMC Med Res Methodol. 2014;14:79. doi:10.1186/1471-2288-14-79 PubMed DOI PMC
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