Journal ArticleDOI
Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study.
Victor L. Villemagne,Samantha C. Burnham,Pierrick Bourgeat,Belinda M. Brown,Kathryn A. Ellis,Olivier Salvado,Cassandra Szoeke,S. Lance Macaulay,Ralph N. Martins,Paul Maruff,David Ames,Christopher C. Rowe,Colin L. Masters +12 more
Reads0
Chats0
TLDR
These projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches the authors' threshold of positivity at 17·0 (95% CI 14·9-19·9) years, hippocampal atrophy at 4·2 (3·6-5·1] years, and memory impairment at 3·3 (2·5-4·5) years before the onset of dementia (clinical dementia rating score 1).Abstract:
Summary Background Similar to most chronic diseases, Alzheimer's disease (AD) develops slowly from a preclinical phase into a fully expressed clinical syndrome. We aimed to use longitudinal data to calculate the rates of amyloid β (Aβ) deposition, cerebral atrophy, and cognitive decline. Methods In this prospective cohort study, healthy controls, patients with mild cognitive impairment (MCI), and patients with AD were assessed at enrolment and every 18 months. At every visit, participants underwent neuropsychological examination, MRI, and a carbon-11-labelled Pittsburgh compound B ( 11 C-PiB) PET scan. We included participants with three or more 11 C-PiB PET follow-up assessments. Aβ burden was expressed as 11 C-PiB standardised uptake value ratio (SUVR) with the cerebellar cortex as reference region. An SUVR of 1·5 was used to discriminate high from low Aβ burdens. The slope of the regression plots over 3–5 years was used to estimate rates of change for Aβ deposition, MRI volumetrics, and cognition. We included those participants with a positive rate of Aβ deposition to calculate the trajectory of each variable over time. Findings 200 participants (145 healthy controls, 36 participants with MCI, and 19 participants with AD) were assessed at enrolment and every 18 months for a mean follow-up of 3·8 (95% CI CI 3·6–3·9) years. At baseline, significantly higher Aβ burdens were noted in patients with AD (2·27, SD 0·43) and those with MCI (1·94, 0·64) than in healthy controls (1·38, 0·39). At follow-up, 163 (82%) of the 200 participants showed positive rates of Aβ accumulation. Aβ deposition was estimated to take 19·2 (95% CI 16·8–22·5) years in an almost linear fashion—with a mean increase of 0·043 (95% CI 0·037–0·049) SUVR per year—to go from the threshold of 11 C-PiB positivity (1·5 SUVR) to the levels observed in AD. It was estimated to take 12·0 (95% CI 10·1–14·9) years from the levels observed in healthy controls with low Aβ deposition (1·2 [SD 0·1] SUVR) to the threshold of 11 C-PiB positivity. As AD progressed, the rate of Aβ deposition slowed towards a plateau. Our projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches our threshold of positivity at 17·0 (95% CI 14·9–19·9) years, hippocampal atrophy at 4·2 (3·6–5·1) years, and memory impairment at 3·3 (2·5–4·5) years before the onset of dementia (clinical dementia rating score 1). Interpretation Aβ deposition is slow and protracted, likely to extend for more than two decades. Such predictions of the rate of preclinical changes and the onset of the clinical phase of AD will facilitate the design and timing of therapeutic interventions aimed at modifying the course of this illness. Funding Science and Industry Endowment Fund (Australia), The Commonwealth Scientific and Industrial Research Organisation (Australia), The National Health and Medical Research Council of Australia Program and Project Grants, the Austin Hospital Medical Research Foundation, Victorian State Government, The Alzheimer's Drug Discovery Foundation, and the Alzheimer's Association.read more
Citations
More filters
Journal ArticleDOI
Diffusion imaging changes in grey matter in Alzheimer’s disease: a potential marker of early neurodegeneration
TL;DR: A growing number of studies that assess grey matter diffusivity changes in AD are reviewed, finding this imaging technique may be useful in comparing and contrasting subtle variations in different disease subgroups, and as a sensitive outcome measure for presymptomatic clinical trials in AD and other neurodegenerative diseases.
Journal ArticleDOI
Biomarker-based prediction of progression in MCI: Comparison of AD signature and hippocampal volume with spinal fluid amyloid-β and tau.
TL;DR: In amnesic MCI, short-term prognosis of progression to dementia relates strongly to baseline markers of neurodegeneration, with the AD signature MRI biomarker of cortical thickness performing the best among MRI and CSF markers studied here.
Journal ArticleDOI
YKL-40 in the brain and cerebrospinal fluid of neurodegenerative dementias
Franc Llorens,Katrin Thüne,Katrin Thüne,Waqas Tahir,Eirini Kanata,Daniela Diaz-Lucena,Konstantinos Xanthopoulos,Eleni Kovatsi,Catharina Pleschka,Paula Garcia-Esparcia,Paula Garcia-Esparcia,Matthias Schmitz,Duru Ozbay,Susana Margarida da Silva Correia,Ângela Correia,Ira Milosevic,Olivier Andreoletti,Natalia Fernández-Borges,Ina Vorberg,Markus Glatzel,Theodoros Sklaviadis,Juan María Torres,Susanne Krasemann,Raquel Sánchez-Valle,Isidro Ferrer,Isidro Ferrer,Inga Zerr +26 more
TL;DR: It is unequivocally demonstrated that in neurodegenerative dementias, YKL-40 is a disease-specific marker of neuroinflammation showing its highest levels in prion diseases.
Journal ArticleDOI
Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease
Xiuming Zhang,Elizabeth C. Mormino,Nanbo Sun,Reisa A. Sperling,Mert R. Sabuncu,B.T. Thomas Yeo,Alzheimer’s Disease Neuroimaging Initiative +6 more
TL;DR: A data-driven Bayesian model is used to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer's disease (AD) dementia patients, suggesting that distinct patterns of atrophy influence decline across different cognitive domains.
Journal ArticleDOI
Rates of β-amyloid accumulation are independent of hippocampal neurodegeneration
Clifford R. Jack,Heather J. Wiste,David S. Knopman,Prashanthi Vemuri,Michelle M. Mielke,Stephen D. Weigand,Matthew L. Senjem,Jeffrey L. Gunter,Val J. Lowe,Brian E. Gregg,Vernon S. Pankratz,Ronald C. Petersen +11 more
TL;DR: A 2-feature biomarker approach to classifying elderly CN subjects that is complementary to the National Institute on Aging–Alzheimer's Association preclinical staging criteria is described and results support 2 key concepts in a model of the temporal evolution of AD biomarkers.
References
More filters
Journal ArticleDOI
Clinical diagnosis of Alzheimer's disease : report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease
Guy M. McKhann,David A. Drachman,Marshall F. Folstein,Robert Katzman,Donald L. Price,Emanuel M. Stadlan +5 more
TL;DR: The criteria proposed are intended to serve as a guide for the diagnosis of probable, possible, and definite Alzheimer's disease; these criteria will be revised as more definitive information becomes available.
Proceedings Article
Information Theory and an Extention of the Maximum Likelihood Principle
TL;DR: The classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion to provide answers to many practical problems of statistical model fitting.
Book ChapterDOI
Information Theory and an Extension of the Maximum Likelihood Principle
TL;DR: In this paper, it is shown that the classical maximum likelihood principle can be considered to be a method of asymptotic realization of an optimum estimate with respect to a very general information theoretic criterion.
Journal ArticleDOI
The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease
Guy M. McKhann,Guy M. McKhann,David S. Knopman,Howard Chertkow,Bradley T. Hyman,Clifford R. Jack,Claudia H. Kawas,William E. Klunk,Walter J. Koroshetz,Jennifer J. Manly,Richard Mayeux,Richard C. Mohs,John C. Morris,Martin N. Rossor,Philip Scheltens,Maria C. Carrillo,Bill Thies,Sandra Weintraub,Creighton H. Phelps +18 more
TL;DR: The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available.
Journal ArticleDOI
Mild Cognitive Impairment: Clinical Characterization and Outcome
Ronald C. Petersen,Glenn E. Smith,Stephen C. Waring,Robert J. Ivnik,Eric G. Tangalos,Emre Kokmen +5 more
TL;DR: Patients who meet the criteria for MCI can be differentiated from healthy control subjects and those with very mild AD, and appear to constitute a clinical entity that can be characterized for treatment interventions.
Related Papers (5)
Toward defining the preclinical stages of Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease
Reisa A. Sperling,Paul S. Aisen,Laurel A. Beckett,David A. Bennett,Suzanne Craft,Anne M. Fagan,Takeshi Iwatsubo,Clifford R. Jack,Jeffrey Kaye,Thomas J. Montine,Denise C. Park,Eric M. Reiman,Christopher C. Rowe,Eric Siemers,Yaakov Stern,Kristine Yaffe,Maria C. Carrillo,Bill Thies,Marcelle Morrison-Bogorad,Molly V. Wagster,Creighton H. Phelps +20 more
The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease
Guy M. McKhann,Guy M. McKhann,David S. Knopman,Howard Chertkow,Bradley T. Hyman,Clifford R. Jack,Claudia H. Kawas,William E. Klunk,Walter J. Koroshetz,Jennifer J. Manly,Richard Mayeux,Richard C. Mohs,John C. Morris,Martin N. Rossor,Philip Scheltens,Maria C. Carrillo,Bill Thies,Sandra Weintraub,Creighton H. Phelps +18 more
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B.
William E. Klunk,Henry Engler,Agneta Nordberg,Yanming Wang,G. Blomqvist,Daniel P. Holt,Mats Bergström,Irina Savitcheva,Guo Feng Huang,Sergio Estrada,Birgitta Ausén,Manik L. Debnath,Julien Barletta,Julie C. Price,Johan Sandell,Brian J. Lopresti,Anders Wall,Pernilla Koivisto,Gunnar Antoni,Chester A. Mathis,Bengt Långström +20 more