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Shaw LM, Korecka M, Figurski M, Toledo J, Irwin D, Kang JH, Trojanowski JQ. Detection of Alzheimer Disease Pathology in Patients Using Biochemical Biomarkers: Prospects and Challenges for Use in Clinical Practice. J Appl Lab Med 2020; 5:183-193. [PMID: 31848218 PMCID: PMC7246169 DOI: 10.1373/jalm.2019.029587] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 11/01/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Thirty-four years ago, amyloid-β 1-42 peptide was identified in amyloid plaques from brain tissue obtained from patients with Alzheimer disease (AD) and Down syndrome. This finding led to development of immunoassays for this marker of amyloid plaque burden in cerebrospinal fluid (CSF) approximately 10 years later. Subsequently, research immunoassays were developed for total τ protein and τ phosphorylated at the threonine 181 position. Subsequent studies documented the clinical utility of these biomarkers of amyloid plaque burden or τ tangle pathology in cohorts of living patients. CONTENT We describe the following: (a) clinical utility of AD biomarkers; (b) measurement challenges, including development of mass spectrometry-based reference methods and automated immunoassays; (c) development of "appropriate use criteria" (AUC) guidelines for safe/appropriate use of CSF testing for diagnosis of AD developed by neurologists, a neuroethicist, and laboratorians; (d) a framework, sponsored by the National Institute of Aging-Alzheimer's Association (NIA-AA), that defines AD on the basis of CSF and imaging methods for detecting amyloid plaque burden, τ tangle pathology, and neurodegeneration. This framework's purpose was investigative but has important implications for future clinical practice; (e) recognition of copathologies in AD patients and challenges for developing methods to detect these in living patients. SUMMARY The field can expect availability of validated research tools for detection of AD pathology that support clinical treatment trials of disease-modifying agents and, ultimately, use in clinical practice. Validated methods are becoming available for CSF testing; emergence of validated methods for AD biomarkers in plasma can be expected in the next few years.
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Affiliation(s)
- Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University
of Pennsylvania, Philadelphia, PA 19104
| | - Magdalena Korecka
- Department of Pathology and Laboratory Medicine, University
of Pennsylvania, Philadelphia, PA 19104
| | - Michal Figurski
- Department of Pathology and Laboratory Medicine, University
of Pennsylvania, Philadelphia, PA 19104
| | - Jon Toledo
- Department of Neurology, Houston Methodist Hospital,
Houston, TX
| | - David Irwin
- Department of Neurology, Perelman School of Medicine,
University of Pennsylvania, Philadelphia, PA 19104
| | - Ju Hee Kang
- Department of Pharmacology and Clinical Pharmacology,
College of Medicine, Inha University, Incheon, 22212, Republic of Korea
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University
of Pennsylvania, Philadelphia, PA 19104
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152
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Blazel MM, Lazar KK, Van Hulle CA, Ma Y, Cole A, Spalitta A, Davenport-Sis N, Bendlin BB, Wahoske M, Illingworth C, Gleason CE, Edwards DF, Blazel H, Asthana S, Johnson SC, Carlsson CM. Factors Associated with Lumbar Puncture Participation in Alzheimer's Disease Research. J Alzheimers Dis 2020; 77:1559-1567. [PMID: 32925041 PMCID: PMC7683076 DOI: 10.3233/jad-200394] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2020] [Indexed: 11/15/2022]
Abstract
BACKGROUND Cerebrospinal fluid (CSF) provides insight into the spectrum of Alzheimer's disease (AD) pathology. While lumbar punctures (LPs) for CSF collection are generally considered safe procedures, many participants remain hesitant to participate in research involving LPs. OBJECTIVE To explore factors associated with participant willingness to undergo a research LP at baseline and follow-up research study visit. METHODS We analyzed data from 700 participants with varying cognition (unimpaired, mild cognitive impairment, and dementia) in the Wisconsin Alzheimer's Disease Research Center. We evaluated the relationship of demographic variables (age, sex, race, ethnicity, and years of education) and clinical variables (waist-to-hip ratio, body mass index, AD parental history, cognitive diagnosis) on decision to undergo baseline LP1. We evaluated the relationship of prior LP1 experience (procedure success and adverse events) with the decision to undergo follow-up LP2. The strongest predictors were incorporated into regression models. RESULTS Over half of eligible participants opted into both baseline and follow-up LP. Participants who underwent LP1 had higher mean education than those who declined (p = 0.020). White participants were more likely to choose to undergo LP1 (p < 0.001); 33% of African American participants opted in compared to 65% of white participants. Controlling for age, education, and AD parental history, race was the only significant predictor for LP1 participation. Controlling for LP1 mild adverse events, successful LP1 predicted LP2 participation. CONCLUSION Race was the most important predictor of baseline LP participation, and successful prior LP was the most important predictor of follow-up LP participation.
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Affiliation(s)
- Madeleine M. Blazel
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Karen K. Lazar
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Aleshia Cole
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Alice Spalitta
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nancy Davenport-Sis
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Michelle Wahoske
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Chuck Illingworth
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carey E. Gleason
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Veterans Affairs Geriatric Research, Education and Clinical Center (VA GRECC), Madison, WI, USA
| | - Dorothy F. Edwards
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Hanna Blazel
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Veterans Affairs Geriatric Research, Education and Clinical Center (VA GRECC), Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute (WAI), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Veterans Affairs Geriatric Research, Education and Clinical Center (VA GRECC), Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center (ADRC), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer’s Institute (WAI), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Veterans Affairs Geriatric Research, Education and Clinical Center (VA GRECC), Madison, WI, USA
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153
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Marizzoni M, Ferrari C, Babiloni C, Albani D, Barkhof F, Cavaliere L, Didic M, Forloni G, Fusco F, Galluzzi S, Hensch T, Jovicich J, Marra C, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Ranjeva JP, Ribaldi F, Rolandi E, Rossini PM, Salvatore M, Soricelli A, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. CSF cutoffs for MCI due to AD depend on APOEε4 carrier status. Neurobiol Aging 2019; 89:55-62. [PMID: 32029236 DOI: 10.1016/j.neurobiolaging.2019.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 12/20/2019] [Accepted: 12/21/2019] [Indexed: 12/14/2022]
Abstract
Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aβ42 and Aβ42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis.
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Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino (FR), Cassino, Italy
| | - Diego Albani
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Federica Fusco
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Camillo Marra
- Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Rome, Italy
| | - José Luis Molinuevo
- Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Dept. of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, INSERM, Marseille, France; Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Federica Ribaldi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Elena Rolandi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Marco Salvatore
- SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | | | - Magda Tsolaki
- 1st University Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, the Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany; Medical Sciences Department, iBiMED, University of Aveiro, Aveiro, Portugal
| | | | - Régis Bordet
- University of Lille, Inserm, CHU, Lille, France; U1171 - Degenerative and Vascular Cognitive Disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-INSERM 1106, Service de Pharmacologie Clinique, APHM, Marseille, France
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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154
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Sonntag T, Moresco JJ, Yates JR, Montminy M. The KLDpT activation loop motif is critical for MARK kinase activity. PLoS One 2019; 14:e0225727. [PMID: 31794565 PMCID: PMC6890249 DOI: 10.1371/journal.pone.0225727] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 11/11/2019] [Indexed: 11/19/2022] Open
Abstract
MAP/microtubule-affinity regulating kinases (MARK1-4) are members of the AMPK family of Ser/Thr-specific kinases, which phosphorylate substrates at consensus LXRXXSXXXL motifs. Within microtubule-associated proteins, MARKs also mediate phosphorylation of variant KXGS or ζXKXGSXXNΨ motifs, interfering with the ability of tau and MAP2/4 to bind to microtubules. Here we show that, although MARKs and the closely related salt-inducible kinases (SIKs) phosphorylate substrates with consensus AMPK motifs comparably, MARKs are more potent in recognizing variant ζXKXGSXXNΨ motifs on cellular tau. In studies to identify regions of MARKs that confer catalytic activity towards variant sites, we found that the C-terminal kinase associated-1 (KA1) domain in MARK1-3 mediates binding to microtubule-associated proteins CLASP1/2; but this interaction is dispensable for ζXKXGSXXNΨ phosphorylation. Mutational analysis of MARK2 revealed that the N-terminal kinase domain of MARK2 is sufficient for phosphorylation of both consensus and variant ζXKXGSXXNΨ sites. Within this domain, the KLDpT activation loop motif promotes MARK2 activity both intracellularly and in vitro, but has no effect on SIK2 activity. As KLDpT is conserved in all vertebrates MARKs, we conclude that this sequence is crucial for MARK-dependent regulation of cellular polarity.
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Affiliation(s)
- Tim Sonntag
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, California, United States of America
| | - James J. Moresco
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States of America
| | - John R. Yates
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California, United States of America
| | - Marc Montminy
- Clayton Foundation Laboratories for Peptide Biology, The Salk Institute for Biological Studies, La Jolla, California, United States of America
- * E-mail:
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155
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Abstract
The development of blood-based biomarkers of Alzheimer's disease (AD) pathology as tools for screening the general population, and as the first step in a multistep process to determine which non-demented individuals are at greatest risk of developing AD dementia, is essential. Proteins that are reflective of AD pathology, such as amyloid beta 42 (Aβ42), tau proteins [total tau (T-tau) and phosphorylated tau (P-tau)], and neurofilament light chain (NfL), are detectable in the blood. However, a major challenge in measuring these blood-based proteins is that their concentrations are much lower in plasma or serum than in the cerebrospinal fluid. Single molecule array (SiMoA) is an ultrasensitive technology that can detect proteins in blood at sub-femtomolar concentrations (i.e., 10-16 M). In this review, we focus on the utility of SiMoA assays for the measurement of plasma or serum Aβ42, P-tau, T-tau, and NfL levels and discuss future directions.
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Affiliation(s)
- Danni Li
- Department of Lab Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA.
- Department of Neurology, Mayo Clinic College of Medicine, Rochester, MN, USA.
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156
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Weber DM, Tran D, Goldman SM, Taylor SW, Ginns EI, Lagier RJ, Rissman RA, Brewer JB, Clarke NJ. High-Throughput Mass Spectrometry Assay for Quantifying β-Amyloid 40 and 42 in Cerebrospinal Fluid. Clin Chem 2019; 65:1572-1580. [PMID: 31628138 DOI: 10.1373/clinchem.2018.300947] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 09/23/2019] [Indexed: 01/11/2023]
Abstract
BACKGROUND The ratio of β-amyloid 1-42 (Aβ42) to Aβ40 in cerebrospinal fluid (CSF) may be useful for evaluating Alzheimer disease (AD), but quantification is limited by factors including preanalytical analyte loss. We developed an LC-MS/MS assay that limits analyte loss. Here we describe the analytical characteristics of the assay and its performance in differentiating patients with AD from non-AD dementia and healthy controls. METHODS To measure Aβ42/Aβ40, we used unique proteolytically derived C-terminal peptides as surrogate markers of Aβ40 and Aβ42, which were analyzed and quantified by LC-MS/MS. The assay was analytically validated and applied to specimens from individuals with clinically diagnosed AD (n = 102), mild cognitive impairment (n = 37), and non-AD dementias (n = 22), as well as from healthy controls (n = 130). Aβ42/Aβ40 values were compared with APOE genotype inferred from phenotype, also measured by LC-MS/MS. RESULTS The assay had a reportable range of 100 to 25000 pg/mL, a limit of quantification of 100 pg/mL, recoveries between 93% and 111%, and intraassay and interassay CV <15% for both peptides. An Aβ42/Aβ40 ratio cutoff of <0.16 had a clinical sensitivity of 78% for distinguishing patients with AD from non-AD dementia (clinical specificity, 91%) and from healthy controls (clinical specificity, 81%). The Aβ42/Aβ40 ratio decreased significantly (P < 0.001) with increasing dose of APOE4 alleles. CONCLUSIONS This assay can be used to determine Aβ42/Aβ40 ratios, which correlate with the presence of AD.
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Affiliation(s)
- Darren M Weber
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA
| | - Diana Tran
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA
| | - Scott M Goldman
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA
| | - Steven W Taylor
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA
| | | | | | - Robert A Rissman
- University of California, San Diego (UCSD) ADRC Neuropathology Core and Brain Bank, La Jolla, CA.,Veterans Affairs San Diego Healthcare System, La Jolla, CA
| | - James B Brewer
- UC San Diego Department of Neurosciences and Shiley Marcos Alzheimer's Disease Research Center, La Jolla, CA
| | - Nigel J Clarke
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA;
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157
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Carandini T, Arighi A, Sacchi L, Fumagalli GG, Pietroboni AM, Ghezzi L, Colombi A, Scarioni M, Fenoglio C, De Riz MA, Marotta G, Scarpini E, Galimberti D. Testing the 2018 NIA-AA research framework in a retrospective large cohort of patients with cognitive impairment: from biological biomarkers to clinical syndromes. ALZHEIMERS RESEARCH & THERAPY 2019; 11:84. [PMID: 31615545 PMCID: PMC6794758 DOI: 10.1186/s13195-019-0543-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 09/27/2019] [Indexed: 12/29/2022]
Abstract
Background According to the 2018 NIA-AA research framework, Alzheimer’s disease (AD) is not defined by the clinical consequences of the disease, but by its underlying pathology, measured by biomarkers. Evidence of both amyloid-β (Aβ) and phosphorylated tau protein (p-tau) deposition—assessed interchangeably with amyloid-positron emission tomography (PET) and/or cerebrospinal fluid (CSF) analysis—is needed to diagnose AD in a living person. Our aim was to test the new NIA-AA research framework in a large cohort of cognitively impaired patients to evaluate correspondence between the clinical syndromes and the underlying pathologic process testified by biomarkers. Methods We retrospectively analysed 628 subjects referred to our centre in suspicion of dementia, who underwent CSF analysis, together with neuropsychological assessment and neuroimaging, and were diagnosed with different neurodegenerative dementias according to current criteria, or as cognitively unimpaired. Subjects were classified considering CSF biomarkers, and the prevalence of normal, AD-continuum and non-AD profiles in each clinical syndrome was calculated. The positivity threshold of each CSF biomarker was first assessed by receiver operating characteristic analysis, using Aβ-positive/negative status as determined by amyloid-PET visual reads. The agreement between CSF and amyloid-PET data was also evaluated. Results Among patients with a clinical diagnosis of AD, 94.1% were in the AD-continuum, whereas 5.5% were classified as non-AD and 0.4% were normal. The AD-continuum profile was found also in 26.2% of frontotemporal dementia, 48.6% of Lewy body dementia, 25% of atypical parkinsonism and 44.7% of vascular dementia. Biomarkers’ profile did not differ in amnestic and not amnestic mild cognitive impairment. CSF Aβ levels and amyloid-PET tracer binding negatively correlated, and the concordance between the two Aβ biomarkers was 89%. Conclusions The examination of the 2018 NIA-AA research framework in our clinical setting revealed a good, but incomplete, correspondence between the clinical syndromes and the underlying pathologic process measured by CSF biomarkers. The AD-continuum profile resulted to be a sensitive, but non-specific biomarker with regard to the clinical AD diagnosis. CSF and PET Aβ biomarkers were found to be not perfectly interchangeable to quantify the Aβ burden, possibly because they measure different aspects of AD pathology.
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Affiliation(s)
- Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy. .,Dino Ferrari Center, University of Milan, Milan, Italy.
| | - Andrea Arighi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Luca Sacchi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Giorgio G Fumagalli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy.,Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy
| | - Anna M Pietroboni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Laura Ghezzi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Annalisa Colombi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Marta Scarioni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | | | - Milena A De Riz
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Giorgio Marotta
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
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158
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Altomare D, de Wilde A, Ossenkoppele R, Pelkmans W, Bouwman F, Groot C, van Maurik I, Zwan M, Yaqub M, Barkhof F, van Berckel BN, Teunissen CE, Frisoni GB, Scheltens P, van der Flier WM. Applying the ATN scheme in a memory clinic population: The ABIDE project. Neurology 2019; 93:e1635-e1646. [PMID: 31597710 DOI: 10.1212/wnl.0000000000008361] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 05/21/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To apply the ATN scheme to memory clinic patients, to assess whether it discriminates patient populations with specific features. METHODS We included 305 memory clinic patients (33% subjective cognitive decline [SCD]: 60 ± 9 years, 61% M; 19% mild cognitive impairment [MCI]: 68 ± 9 years, 68% M; 48% dementia: 66 ± 10 years, 58% M) classified for positivity (±) of amyloid (A) ([18F]Florbetaben PET), tau (T) (CSF p-tau), and neurodegeneration (N) (medial temporal lobe atrophy). We assessed ATN profiles' demographic, clinical, and cognitive features at baseline, and cognitive decline over time. RESULTS The proportion of A+T+N+ patients increased with syndrome severity (from 1% in SCD to 14% in MCI and 35% in dementia), while the opposite was true for A-T-N- (from 48% to 19% and 6%). Compared to A-T-N-, patients with the Alzheimer disease profiles (A+T+N- and A+T+N+) were older (both p < 0.05) and had a higher prevalence of APOE ε4 (both p < 0.05) and lower Mini-Mental State Examination (MMSE) (both p < 0.05), memory (both p < 0.05), and visuospatial abilities (both p < 0.05) at baseline. Non-Alzheimer profiles A-T-N+ and A-T+N+ showed more severe white matter hyperintensities (both p < 0.05) and worse language performance (both p < 0.05) than A-T-N-. A linear mixed model showed faster decline on MMSE over time in A+T+N- and A+T+N+ (p = 0.059 and p < 0.001 vs A-T-N-), attributable mainly to patients without dementia. CONCLUSIONS The ATN scheme identified different biomarker profiles with overlapping baseline features and patterns of cognitive decline. The large number of profiles, which may have different implications in patients with vs without dementia, poses a challenge to the application of the ATN scheme.
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Affiliation(s)
- Daniele Altomare
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Arno de Wilde
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Rik Ossenkoppele
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Wiesje Pelkmans
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Femke Bouwman
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Colin Groot
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Ingrid van Maurik
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Marissa Zwan
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Maqsood Yaqub
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Frederik Barkhof
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Bart N van Berckel
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Charlotte E Teunissen
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Giovanni B Frisoni
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Philip Scheltens
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland
| | - Wiesje M van der Flier
- From the Alzheimer Center Amsterdam, Department of Neurology (D.A., A.d.W., R.O., W.P., F.B., C.G., I.v.M., M.Z., B.N.v.B., P.S., W.M.v.d.F.), Department of Radiology & Nuclear Medicine (R.O., C.G., M.Y., F.B., B.N.v.B.), and Neurochemistry Laboratory, Department of Clinical Chemistry (C.E.T.), Amsterdam Neuroscience, and Department of Epidemiology & Biostatistics (I.v.M., W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Laboratory of Neuroimaging of Aging (LANVIE) (D.A., G.B.F.), University of Geneva, Switzerland; Memory Clinic (D.A.), University Hospitals of Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE) (D.A.), Saint John of God Clinical Research Centre; Department of Molecular and Translational Medicine (D.A.), University of Brescia, Italy; Clinical Memory Research Unit (R.O.), Lund University, Malmö, Sweden; Institutes of Neurology and Healthcare Engineering (F.B.), UCL, London, UK; and Memory Clinic (D.A., G.B.F.), University Hospitals of Geneva, Switzerland.
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159
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Kim SE, Woo S, Kim SW, Chin J, Kim HJ, Lee BI, Park J, Park KW, Kang DY, Noh Y, Ye BS, Yoo HS, Lee JS, Kim Y, Kim SJ, Cho SH, Na DL, Lockhart SN, Jang H, Seo SW. A Nomogram for Predicting Amyloid PET Positivity in Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2019; 66:681-691. [PMID: 30320571 DOI: 10.3233/jad-180048] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Most clinical trials focus on amyloid-β positive (Aβ+) amnestic mild cognitive impairment (aMCI), but screening failures are high because only a half of patients with aMCI are positive on Aβ PET. Therefore, it becomes necessary for clinicians to predict which patients will have Aβ biomarker. OBJECTIVE We aimed to compare clinical factors, neuropsychological (NP) profiles, and apolipoprotein E (APOE) genotype between Aβ+ aMCI and Aβ-aMCI and to develop a clinically useful prediction model of Aβ positivity on PET (PET-Aβ+) in aMCI using a nomogram. METHODS We recruited 523 aMCI patients who underwent Aβ PET imaging in a nation-wide multicenter cohort. The results of NP measures were divided into following subgroups: 1) Stage (Early and Late-stage), 2) Modality (Visual, Verbal, and Both), 3) Recognition failure, and 4) Multiplicity (Single and Multiple). A nomogram for PET-Aβ+ in aMCI patients was constructed using a logistic regression model. RESULTS PET-Aβ+ had significant associations with NP profiles for several items, including high Clinical Dementia Rating Scale Sum of Boxes score (OR 1.47, p = 0.013) and impaired memory modality (impaired both visual and verbal memories compared with visual only, OR 3.25, p = 0.001). Also, presence of APOEɛ4 (OR 4.14, p < 0.001) was associated with PET-Aβ+. These predictors were applied to develop the nomogram, which showed good prediction performance (C-statistics = 0.79). Its prediction performances were 0.77/0.74 in internal/external validation. CONCLUSIONS The nomogram consisting of NP profiles, especially memory domain, and APOEɛ4 genotype may provide a useful predictive model of PET-Aβ+ in patients with aMCI.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Sookyoung Woo
- Statistics and Data Center, Samsung Medical Center, Seoul, Korea
| | - Seon Woo Kim
- Statistics and Data Center, Samsung Medical Center, Seoul, Korea
| | - Juhee Chin
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Hee Jin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Byung In Lee
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Jinse Park
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A University College of Medicine, Dong-A University Medical Center, Busan, Korea
| | - Do-Young Kang
- Department of Nuclear Medicine, Dong-A University College of Medicine, Dong-A University Medical Center, Busan, Korea
| | - Young Noh
- Department of Neurology, Gachon University Gil Medical Center, Incheon, Korea
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University School of Medicine, Severance hospital, Seoul, Korea
| | - Han Soo Yoo
- Department of Neurology, Yonsei University School of Medicine, Severance hospital, Seoul, Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University Hospital, Seoul, Korea
| | - Yeshin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Kangwon National University College of Medicine, Chuncheon-si, Gangwon-do, Korea
| | - Seung Joo Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Soo Hyun Cho
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Samuel N Lockhart
- Department of Internal Medicine, Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Hyemin Jang
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
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160
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O'Bryhim BE, Apte RS, Kung N, Coble D, Van Stavern GP. Association of Preclinical Alzheimer Disease With Optical Coherence Tomographic Angiography Findings. JAMA Ophthalmol 2019; 136:1242-1248. [PMID: 30352114 DOI: 10.1001/jamaophthalmol.2018.3556] [Citation(s) in RCA: 173] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Importance Biomarker testing for asymptomatic, preclinical Alzheimer disease (AD) is invasive and expensive. Optical coherence tomographic angiography (OCTA) is a noninvasive technique that allows analysis of retinal and microvascular anatomy, which is altered in early-stage AD. Objective To determine whether OCTA can detect early retinal alterations in cognitively normal study participants with preclinical AD diagnosed by criterion standard biomarker testing. Design, Setting, and Participants This case-control study included 32 participants recruited from the Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St Louis, St Louis, Missouri. Results of extensive neuropsychometric testing determined that all participants were cognitively normal. Participants underwent positron emission tomography and/or cerebral spinal fluid testing to determine biomarker status. Individuals with prior ophthalmic disease, media opacity, diabetes, or uncontrolled hypertension were excluded. Data were collected from July 1, 2016, through September 30, 2017, and analyzed from July 30, 2016, through December 31, 2017. Main Outcomes and Measures Automated measurements of retinal nerve fiber layer thickness, ganglion cell layer thickness, inner and outer foveal thickness, vascular density, macular volume, and foveal avascular zone were collected using an OCTA system from both eyes of all participants. Separate model III analyses of covariance were used to analyze individual data outcome. Results Fifty-eight eyes from 30 participants (53% female; mean [SD] age, 74.5 [5.6] years; age range, 62-92 years) were included in the analysis. One participant was African American and 29 were white. Fourteen participants had biomarkers positive for AD and thus a diagnosis of preclinical AD (mean [SD] age, 73.5 [4.7] years); 16 without biomarkers served as a control group (mean [SD] age, 75.4 [6.6] years). The foveal avascular zone was increased in the biomarker-positive group compared with controls (mean [SD], 0.364 [0.095] vs 0.275 [0.060] mm2; P = .002). Mean (SD) inner foveal thickness was decreased in the biomarker-positive group (66.0 [9.9] vs 75.4 [10.6] μm; P = .03). Conclusions and Relevance This study suggests that cognitively healthy individuals with preclinical AD have retinal microvascular abnormalities in addition to architectural alterations and that these changes occur at earlier stages of AD than has previously been demonstrated. Longitudinal studies in larger cohorts are needed to determine whether this finding has value in identifying preclinical AD.
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Affiliation(s)
- Bliss Elizabeth O'Bryhim
- Department of Ophthalmology and Vision Science, Washington University in St Louis, St Louis, Missouri
| | - Rajendra S Apte
- Department of Ophthalmology and Vision Science, Washington University in St Louis, St Louis, Missouri.,Department of Medicine, Washington University in St Louis, St Louis, Missouri.,Department of Developmental Biology, Washington University in St Louis, St Louis, Missouri
| | | | - Dean Coble
- Division of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | - Gregory P Van Stavern
- Department of Ophthalmology and Vision Science, Washington University in St Louis, St Louis, Missouri.,Department of Neurology, Washington University in St Louis, St Louis, Missouri
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161
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Respondek G, Grimm MJ, Piot I, Arzberger T, Compta Y, Englund E, Ferguson LW, Gelpi E, Roeber S, Giese A, Grossman M, Irwin DJ, Meissner WG, Nilsson C, Pantelyat A, Rajput A, van Swieten JC, Troakes C, Höglinger GU. Validation of the movement disorder society criteria for the diagnosis of 4-repeat tauopathies. Mov Disord 2019; 35:171-176. [PMID: 31571273 DOI: 10.1002/mds.27872] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 08/17/2019] [Accepted: 09/03/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The Movement Disorder Society criteria for progressive supranuclear palsy introduced the category "probable 4-repeat (4R)-tauopathy" for joint clinical diagnosis of progressive supranuclear palsy and corticobasal degeneration. OBJECTIVES To validate the accuracy of these clinical criteria for "probable 4R-tauopathy" to predict underlying 4R-tauopathy pathology. METHODS Diagnostic accuracy for 4R-tauopathies according to the established criteria was estimated retrospectively in autopsy-confirmed patients with progressive supranuclear palsy and corticobasal degeneration (grouped as 4R-tauopathies), and Parkinson's disease, multiple system atrophy, and frontotemporal lobar degeneration (grouped as non-4R-tauopathies). RESULTS We identified 250 cases with progressive supranuclear palsy (N = 195) and corticobasal degeneration (N = 55) and with and non-4R-tauopathies (N = 161). Sensitivity and specificity of "probable 4R-tauopathy" was 10% and 99% in the first year and 59% and 88% at final record. CONCLUSIONS The new diagnostic category "probable 4R-tauopathy" showed high specificity and may be suitable for the recruitment of patients with progressive supranuclear palsy and corticobasal degeneration into therapeutic trials targeting 4R-tauopathy. The low sensitivity underpins the need for diagnostic biomarkers. © 2019 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Gesine Respondek
- Department of Neurology, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany
| | - Max-Joseph Grimm
- Department of Neurology, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany
| | - Ines Piot
- Department of Neurology, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany
| | - Thomas Arzberger
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, Munich, Germany.,Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Yaroslau Compta
- Parkinson's Disease & Movement Disorders Unit, Hospital Clínic/August Pi i Sunyer Biomedical Research Institute (IDIBAPS)/Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas(CIBERNED)/European Reference Network for Rare Neurological Diseases/Institut de Neurociències, Maeztu center, Universitat de Barcelona, Catalonia, Spain
| | - Elisabet Englund
- Department of Clinical Sciences, Division of Neurology, Lund University, Lund, Sweden
| | - Leslie W Ferguson
- Division of Neurology, Royal University Hospital, University of Saskatchewan, Saskatchewan, Canada
| | - Ellen Gelpi
- Neurological Tissue Bank and Neurology Department, Hospital Clínic de Barcelona, Universitat de Barcelona, IDIBAPS, Centres de Recerca de Catalunya (CERCA), Barcelona, Catalonia, Spain.,Institute of Neurology, Medical University of Vienna, Vienna, Austria
| | - Sigrun Roeber
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Armin Giese
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Murray Grossman
- Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J Irwin
- Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Wassilios G Meissner
- Univ. de Bordeaux, Institut des Maladies Neurodégénératives, Unité Mixte de Recherche (UMR), 5293, 33000, Bordeaux, France.,Service de Neurologie, Hôpital Pellegrin, Centre Hospitalier Universitaire (CHU) de Bordeaux, 33000, Bordeaux, France.,Department of Medicine, University of Otago, Christchurch, New Zealand.,New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Christer Nilsson
- Department of Clinical Sciences, Division of Neurology, Lund University, Lund, Sweden
| | | | - Alex Rajput
- Division of Neurology, Royal University Hospital, University of Saskatchewan, Saskatchewan, Canada
| | - John C van Swieten
- Department of Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Claire Troakes
- London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Günter U Höglinger
- Department of Neurology, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases, Munich, Germany.,Department of Neurology, Hanover Medical School, Hanover, Germany
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162
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van Maurik IS, Vos SJ, Bos I, Bouwman FH, Teunissen CE, Scheltens P, Barkhof F, Frolich L, Kornhuber J, Wiltfang J, Maier W, Peters O, Rüther E, Nobili F, Frisoni GB, Spiru L, Freund-Levi Y, Wallin AK, Hampel H, Soininen H, Tsolaki M, Verhey F, Kłoszewska I, Mecocci P, Vellas B, Lovestone S, Galluzzi S, Herukka SK, Santana I, Baldeiras I, de Mendonça A, Silva D, Chetelat G, Egret S, Palmqvist S, Hansson O, Visser PJ, Berkhof J, van der Flier WM. Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study. Lancet Neurol 2019; 18:1034-1044. [PMID: 31526625 DOI: 10.1016/s1474-4422(19)30283-2] [Citation(s) in RCA: 85] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 07/02/2019] [Accepted: 07/09/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. METHODS In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework. FINDINGS We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76). INTERPRETATION We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. FUNDING ZonMW-Memorabel.
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Affiliation(s)
- Ingrid S van Maurik
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.
| | - Stephanie J Vos
- Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht, Netherlands
| | - Isabelle Bos
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht, Netherlands
| | - Femke H Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Lutz Frolich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, Medical Faculty Mannheim University of Heidelberg, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August-University, Göttingen, Germany; German Center for Neurodegenerative Diseases, Göttingen, Germany; iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Wolfgang Maier
- Department of Neurodegenerative Diseases and Gerotopsychiatry, University of Bonn, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Oliver Peters
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; German Center for Neurodegenerative Diseases, Berlin, Germany
| | - Eckart Rüther
- Department of Psychiatry and Psychotherapy, University of Göttingen, Göttingen, Germany
| | - Flavio Nobili
- Clinical Neurology, Department of Neurosciences, University of Genoa, Genoa, Italy; Neurology Department, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Giovanni B Frisoni
- Memory Clinic, University Hospital and University of Geneva, Geneva, Switzerland
| | - Luiza Spiru
- Geriatrics, Gerontology and Old Age Psychiatry Clinical Department, Carol Davila University of Medicine and Pharmacy-"Elias" Emergency Clinical Hospital, Bucharest, Romania; Memory Clinic and Longevity Medicine, Ana Aslan International Foundation, Romania
| | - Yvonne Freund-Levi
- School of Medical Sciences, Örebro University, Örebro, Sweden; Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet Center for Alzheimer Research, Stockholm, Sweden; Department of Old Age Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Asa K Wallin
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Harald Hampel
- Alzheimer Precision Medicine, GRC 21, Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Paris, France; Eisai, Neurology Business Group, Woodcliff Lake, NJ, USA
| | - Hilkka Soininen
- Institute of Clinical Medicine, Neurology, University of Eastern Finland and Neurocenter, Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Magda Tsolaki
- 1st Department of Neurology, Aristotle University of Thessaloniki, Memory and Dementia Center, "AHEPA" General Hospital, Thessaloniki, Greece
| | - Frans Verhey
- Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht, Netherlands
| | - Iwona Kłoszewska
- Department of Geriatric Psychiatry and Psychotic Disorders, Medical University of Lodz, Lodz, Poland
| | - Patrizia Mecocci
- Institute of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy
| | | | | | - Samantha Galluzzi
- Lab Alzheimer's Neuroimaging and Epidemiology, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sanna-Kaisa Herukka
- Institute of Clinical Medicine, Neurology, University of Eastern Finland and Neurocenter, Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Isabel Santana
- Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal; Department of Neurology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Ines Baldeiras
- Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal; Department of Neurology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | | | - Dina Silva
- Institute of Molecular Medicine, University of Lisbon, Lisbon, Portugal; Faculty of Medicine, University of Lisbon, Lisbon, Portugal; Centre for Biomedical Research, Universidade do Algarve, Faro, Portugal
| | - Gael Chetelat
- Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen, France
| | - Stephanie Egret
- Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen, France
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht, Netherlands
| | - Johannes Berkhof
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands; Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
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163
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de Wilde A, Reimand J, Teunissen CE, Zwan M, Windhorst AD, Boellaard R, van der Flier WM, Scheltens P, van Berckel BNM, Bouwman F, Ossenkoppele R. Discordant amyloid-β PET and CSF biomarkers and its clinical consequences. ALZHEIMERS RESEARCH & THERAPY 2019; 11:78. [PMID: 31511058 PMCID: PMC6739952 DOI: 10.1186/s13195-019-0532-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 08/19/2019] [Indexed: 12/31/2022]
Abstract
Background In vivo, high cerebral amyloid-β load has been associated with (i) reduced concentrations of Aβ42 in cerebrospinal fluid and (ii) increased retention using amyloid-β positron emission tomography. Although these two amyloid-β biomarkers generally show good correspondence, ~ 10–20% of cases have discordant results. To assess the consequences of having discordant amyloid-β PET and CSF biomarkers on clinical features, biomarkers, and longitudinal cognitive trajectories. Methods We included 768 patients (194 with subjective cognitive decline (SCD), 127 mild cognitive impairment (MCI), 309 Alzheimer’s dementia (AD), and 138 non-AD) who were categorized as concordant-negative (n = 315, 41%), discordant (n = 97, 13%), or concordant-positive (n = 356, 46%) based on CSF and PET results. We compared discordant with both concordant-negative and concordant-positive groups on demographics, clinical syndrome, apolipoprotein E (APOE) ε4 status, CSF tau, and clinical and neuropsychological progression. Results We found an increase from concordant-negative to discordant to concordant-positive in rates of APOE ε4 (28%, 55%, 70%, Z = − 10.6, P < 0.001), CSF total tau (25%, 45%, 78%, Z = − 13.7, P < 0.001), and phosphorylated tau (28%, 43%, 80%, Z = − 13.7, P < 0.001) positivity. In patients without dementia, linear mixed models showed that Mini-Mental State Examination and memory composite scores did not differ between concordant-negative (β [SE] − 0.13[0.08], P = 0.09) and discordant (β 0.08[0.15], P = 0.15) patients (Pinteraction = 0.19), while these scores declined in concordant-positive (β − 0.75[0.08] patients (Pinteraction < 0.001). In patients with dementia, longitudinal cognitive scores were not affected by amyloid-β biomarker concordance or discordance. Clinical progression rates from SCD to MCI or dementia (P = 0.01) and from MCI to dementia (P = 0.003) increased from concordant-negative to discordant to concordant-positive. Conclusions Discordant cases were intermediate to concordant-negative and concordant-positive patients in terms of genetic (APOE ε4) and CSF (tau) markers of AD. While biomarker agreement did not impact cognition in patients with dementia, discordant biomarkers are not benign in patients without dementia given their higher risk of clinical progression. Electronic supplementary material The online version of this article (10.1186/s13195-019-0532-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Arno de Wilde
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Juhan Reimand
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia.,Center of Radiology, North Estonia Medical Centre, Tallinn, Estonia
| | - Charlotte E Teunissen
- Neurochemistry laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marissa Zwan
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Femke Bouwman
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands.,Clinical Memory Research Unit, Lund University, Malmö, Sweden
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164
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Spallazzi M, Barocco F, Michelini G, Immovilli P, Taga A, Morelli N, Ruffini L, Caffarra P. CSF biomarkers and amyloid PET: concordance and diagnostic accuracy in a MCI cohort. Acta Neurol Belg 2019; 119:445-452. [PMID: 30847669 DOI: 10.1007/s13760-019-01112-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 02/27/2019] [Indexed: 02/07/2023]
Abstract
Brain amyloid deposition is one of the main hallmarks of Alzheimer's disease (AD) and two approaches are available for assessing amyloid pathology in vivo: cerebrospinal fluid (CSF) biomarkers levels and amyloid load visualized by amyloid beta positron emission tomography imaging (Amy-PET) probes. We aimed to investigate the concordance between CSF biomarkers and Amy-PET in a memory clinic cohort. Moreover, using a proper clinical follow-up, we wanted to assess the diagnostic accuracy of CSF and PET biomarkers in predicting the progression of patients with mild cognitive impairment (MCI) to AD dementia. We included 31 MCI patients who underwent [18F]florbetaben PET and CSF sampling (Aβ1-42, t-Tau, p-Tau). A semiquantitative visual scan assessment was used to quantify amyloid deposition in 5 brain regions, rating from 1 (negative), to 2 and 3 (positive). CSF biomarkers were considered abnormal if: Aβ1-42 < 600 pg/ml, p-Tau/Aβ1-42 > 0.08 and t-Tau/Aβ1-42 > 0.52. We also applied less lenient cutoffs of 550 pg/ml and 450 pg/ml for Aβ1-42. The concordance rate was 77% between Amy-PET and CSF Aβ1-42 levels, and 89% between Amy-PET and p-Tau/Aβ1-42 and t-Tau/Aβ1-42. According to the clinical follow-up, Amy-PET (sensitivity [SE] 93.7%, specificity [SP] 80%) exhibited the best diagnostic accuracy in discriminating AD from non-AD, followed by p-Tau/Aβ1-42 ratio and t-Tau/Aβ1-42 ratio (SE 93.7%, SP 66.6%), and Aβ1-42 levels (SE 81%, SP 60%). The regional uptake of [18F]florbetaben PET in the precuneus and the striatum showed the best SP (86.6%). In discordant cases, the clinical diagnosis was most often in agreement with PET results. In general, concordance between CSF biomarkers and Amy-PET was good, especially when the ratios between CSF amyloid and Tau biomarkers were used. However, Amy-PET proved to be superior to CSF Aβ1-42 in terms of diagnostic accuracy for AD, with the possibility to further increase its specificity by focusing the analysis in specific areas such as the precuneus/posterior cingulate cortex and the striatum.
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Affiliation(s)
- Marco Spallazzi
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy.
| | | | | | - Paolo Immovilli
- Department of Neurology, Guglielmo da Saliceto Hospital, Piacenza, Italy
| | - Arens Taga
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy
| | - Nicola Morelli
- Department of Neurology, Guglielmo da Saliceto Hospital, Piacenza, Italy
| | - Livia Ruffini
- Nuclear Medicine Department, Azienda Ospedaliero-Universitaria, Parma, Italy
| | - Paolo Caffarra
- Department of Medicine and Surgery, Section of Neurology, Azienda Ospedaliero-Universitaria, Via Gramsci, 14, 43126, Parma, Italy
- Alzheimer Center, Briolini Hospital, Gazzaniga, Bergamo, Italy
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165
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Ramusino MC, Garibotto V, Bacchin R, Altomare D, Dodich A, Assal F, Mendes A, Costa A, Tinazzi M, Morbelli SD, Bauckneht M, Picco A, Dottorini ME, Tranfaglia C, Farotti L, Salvadori N, Moretti D, Savelli G, Tarallo A, Nobili F, Parapini M, Cavaliere C, Salvatore E, Salvatore M, Boccardi M, Frisoni GB. Incremental value of amyloid-PET versus CSF in the diagnosis of Alzheimer's disease. Eur J Nucl Med Mol Imaging 2019; 47:270-280. [PMID: 31388720 DOI: 10.1007/s00259-019-04466-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 07/26/2019] [Indexed: 10/26/2022]
Abstract
PURPOSE To compare the incremental diagnostic value of amyloid-PET and CSF (Aβ42, tau, and phospho-tau) in AD diagnosis in patients with mild cognitive impairment (MCI) or mild dementia, in order to improve the definition of diagnostic algorithm. METHODS Two independent dementia experts provided etiological diagnosis and relative diagnostic confidence in 71 patients on 3 rounds, based on (1) clinical, neuropsychological, and structural MRI information alone; (2) adding one biomarker (CSF amyloid and tau levels or amyloid-PET with a balanced randomized design); and (3) adding the other biomarker. RESULTS Among patients with a pre-biomarker diagnosis of AD, negative PET induced significantly more diagnostic changes than amyloid-negative CSF at both rounds 2 (CSF 67%, PET 100%, P = 0.028) and 3 (CSF 0%; PET 78%, P < 0.001); PET induced a diagnostic confidence increase significantly higher than CSF on both rounds 2 and 3. CONCLUSIONS Amyloid-PET should be prioritized over CSF biomarkers in the diagnostic workup of patients investigated for suspected AD, as it provides greater changes in diagnosis and diagnostic confidence. TRIAL REGISTRATION EudraCT no.: 2014-005389-31.
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Affiliation(s)
- Matteo Cotta Ramusino
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland. .,Center for Cognitive and Behavioral Disorders, IRCCS Mondino Foundation and Dept of Brain and Behavior, University of Pavia, 27100, Pavia, Italy.
| | - Valentina Garibotto
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, CH1205, Geneva, Switzerland.,Division of Nuclear Medicine, Geneva University Hospitals, CH1205, Geneva, Switzerland
| | - Ruggero Bacchin
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland.,Dept of Neurosciences, Biomedicine and Movement Sciences, Section of Neurology, University of Verona, 34134, Verona, Italy
| | - Daniele Altomare
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland
| | - Alessandra Dodich
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, CH1205, Geneva, Switzerland
| | - Frederic Assal
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland
| | - Aline Mendes
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland
| | - Alfredo Costa
- Center for Cognitive and Behavioral Disorders, IRCCS Mondino Foundation and Dept of Brain and Behavior, University of Pavia, 27100, Pavia, Italy
| | - Michele Tinazzi
- Dept of Neurosciences, Biomedicine and Movement Sciences, Section of Neurology, University of Verona, 34134, Verona, Italy
| | - Silvia D Morbelli
- Nuclear Medicine, Dept of Health Sciences (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, 16132, Genoa, Italy
| | - Matteo Bauckneht
- Nuclear Medicine, Dept of Health Sciences (DISSAL), University of Genoa and IRCCS AOU San Martino-IST, 16132, Genoa, Italy
| | - Agnese Picco
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa, 16126, Genoa, Italy
| | - Massimo E Dottorini
- Nuclear Medicine Division, "S. Maria della Misericordia" Hospital, 06129, Perugia, Italy
| | - Cristina Tranfaglia
- Nuclear Medicine Division, "S. Maria della Misericordia" Hospital, 06129, Perugia, Italy
| | - Lucia Farotti
- Center for Memory Disturbances, Laboratory of Clinical Neurochemistry, University of Perugia, 06123, Perugia, Italy
| | - Nicola Salvadori
- Center for Memory Disturbances, Laboratory of Clinical Neurochemistry, University of Perugia, 06123, Perugia, Italy
| | - Davide Moretti
- Alzheimer's Disease Operative Unit, IRCCS S, Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Giordano Savelli
- Nuclear Medicine Division, Fondazione Poliambulanza Istituto Ospedaliero, 25124, Brescia, Italy
| | - Anna Tarallo
- LANE-Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Flavio Nobili
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa, 16126, Genoa, Italy.,IRCCS Ospedale Policlinico San Martino, 16132, Genoa, Italy
| | - Maura Parapini
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland
| | | | | | | | - Marina Boccardi
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland.,LANE-Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE -Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Chemin du Petit Bel-Air 2, Bâtiment Voirons, CH1225, Geneva, Switzerland
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Dou KX, Zhang C, Tan CC, Xu W, Li JQ, Cao XP, Tan L, Yu JT. Genome-wide association study identifies CBFA2T3 affecting the rate of CSF Aβ 42 decline in non-demented elders. Aging (Albany NY) 2019; 11:5433-5444. [PMID: 31370031 PMCID: PMC6710044 DOI: 10.18632/aging.102125] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 07/21/2019] [Indexed: 11/30/2022]
Abstract
Brain amyloid deposition is an early pathological event in Alzheimer's disease (AD), and abnormally low levels amyloid-β42 peptide (Aβ42) in cerebrospinal fluid (CSF) can be detected in preclinical AD. To identify the genetic determinants that regulate the rate of CSF Aβ42 decline among non-demented elders, we conducted a genome-wide association study involved 321 non-demented elders from Alzheimer's Disease Neuroimaging Initiative (ADNI) 1/GO/2 cohorts restricted to non-Hispanic Caucasians. A novel genome-wide significant association of higher annualized percent decline of CSF Aβ42 in the gene CBFA2T3 (CBFA2/RUNX1 translocation partner 3; rs13333659-T; p = 2.24 × 10-9) was identified. Besides displaying abnormal CSF Aβ42 levels, rs13333659-T carriers were more likely to exhibit a greater longitudinal cognitive decline (p = 0.029, β = 0.097) and hippocampal atrophy (p = 0.029, β = -0.160) in the non-demented elders, especially for the participants who were amyloid-positive at baseline. These findings suggest rs13333659 in CBFA2T3 as a risk locus to modulate the decline rate of CSF Aβ42 preceding the onset of clinical symptoms.
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Affiliation(s)
- Kai-Xin Dou
- Department of Neurology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Can Zhang
- Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases (MIND), Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Chen-Chen Tan
- Department of Neurology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Jie-Qiong Li
- Department of Neurology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Xi-Peng Cao
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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Puzo C, Labriola C, Sugarman MA, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Stein TD, Kowall NW, McKee AC, Mez J, Killiany RJ, Stern RA, Alosco ML. Independent effects of white matter hyperintensities on cognitive, neuropsychiatric, and functional decline: a longitudinal investigation using the National Alzheimer's Coordinating Center Uniform Data Set. Alzheimers Res Ther 2019; 11:64. [PMID: 31351489 PMCID: PMC6661103 DOI: 10.1186/s13195-019-0521-0] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 07/14/2019] [Indexed: 01/18/2023]
Abstract
BACKGROUND Longitudinal investigations are needed to improve understanding of the contributions of cerebral small vessel disease to the clinical manifestation of Alzheimer's disease, particularly in the early disease stages. This study leveraged the National Alzheimer's Coordinating Center Uniform Data Set to longitudinally examine the association between white matter hyperintensities and neuropsychological, neuropsychiatric, and functional decline among participants with normal cognition. METHODS The sample included 465 participants from the National Alzheimer's Coordinating Center Uniform Data Set who had quantitated volume of white matter hyperintensities from fluid-attenuated inversion recovery MRI, had normal cognition at the time of their MRI, and were administered the National Alzheimer's Coordinating Center Uniform Data Set neuropsychological test battery within 1 year of study evaluation and had at least two post-MRI time points of clinical data. Neuropsychiatric status was assessed by the Geriatric Depression Scale-15 and Neuropsychiatric Inventory-Questionnaire. Clinical Dementia Rating Sum of Boxes defined functional status. For participants subsequently diagnosed with mild cognitive impairment (MCI) or dementia, their impairment must have been attributed to Alzheimer's disease (AD) to evaluate the relationships between WMH and the clinical presentation of AD. RESULTS Of the 465 participants, 56 converted to MCI or AD dementia (average follow-up = 5 years). Among the 465 participants, generalized estimating equations controlling for age, sex, race, education, APOE ε4, and total brain and hippocampal volume showed that higher baseline log-white matter hyperintensities predicted accelerated decline on the following neuropsychological tests in rank order of effect size: Trails B (p < 0.01), Digit Symbol Coding (p < 0.01), Logical Memory Immediate Recall (p = 0.02), Trail Making A (p < 0.01), and Semantic Fluency (p < 0.01). White matter hyperintensities predicted increases in Clinical Dementia Rating Sum of Boxes (p < 0.01) and Geriatric Depression Scale-15 scores (p = 0.01). Effect sizes were comparable to total brain and hippocampal volume. White matter hyperintensities did not predict diagnostic conversion. All effects also remained after including individuals with non-AD suspected etiologies for those who converted to MCI or dementia. CONCLUSIONS In this baseline cognitively normal sample, greater white matter hyperintensities were associated with accelerated cognitive, neuropsychiatric, and functional decline independent of traditional risk factors and MRI biomarkers for Alzheimer's disease.
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Affiliation(s)
- Christian Puzo
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Caroline Labriola
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Michael A Sugarman
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Eric G Steinberg
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Departments of Neurosurgery and Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Michael L Alosco
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA.
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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Insel PS, Weiner M, Mackin RS, Mormino E, Lim YY, Stomrud E, Palmqvist S, Masters CL, Maruff PT, Hansson O, Mattsson N. Determining clinically meaningful decline in preclinical Alzheimer disease. Neurology 2019; 93:e322-e333. [PMID: 31289148 PMCID: PMC6669933 DOI: 10.1212/wnl.0000000000007831] [Citation(s) in RCA: 97] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/17/2019] [Indexed: 11/15/2022] Open
Abstract
Objective To determine the time required for a preclinical Alzheimer disease population to decline in a meaningful way, use estimates of decline to update previous clinical trial design assumptions, and identify factors that modify β-amyloid (Aβ)–related decline. Methods In 1,120 cognitively unimpaired individuals from 3 international cohorts, we estimated the relationship between Aβ status and longitudinal changes across multiple cognitive domains and assessed interactions between Aβ and baseline factors. Power analyses were performed to explore sample size as a function of treatment effect. Results Cognitively unimpaired Aβ+ participants approach mild cognitive impairment (MCI) levels of performance 6 years after baseline, on average. Achieving 80% power in a simulated 4-year treatment trial, assuming a 25% treatment effect, required 2,000 participants/group. Multiple factors interacted with Aβ to predict cognitive decline; however, these findings were all cohort-specific. Despite design differences across the cohorts, with large sample sizes and sufficient follow-up time, the Aβ+ groups declined consistently on cognitive composite measures. Conclusions A preclinical AD population declines to the cognitive performance of an early MCI population in 6 years. Slowing this rate of decline by 40%–50% delays clinically relevant impairment by 3 years—a potentially meaningful treatment effect. However, assuming a 40%–50% drug effect highlights the difficulties in preclinical AD trial design, as a more commonly assumed treatment effect of 25% results in a required sample size of 2,000/group. Designers of preclinical AD treatment trials need to prepare for larger and longer trials than are currently being considered. Interactions with Aβ status were inconsistent and not readily generalizable.
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Affiliation(s)
- Philip S Insel
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia.
| | - Michael Weiner
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - R Scott Mackin
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Elizabeth Mormino
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Yen Ying Lim
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Erik Stomrud
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Sebastian Palmqvist
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Colin L Masters
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Paul T Maruff
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Oskar Hansson
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Niklas Mattsson
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
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van Loenhoud AC, van der Flier WM, Wink AM, Dicks E, Groot C, Twisk J, Barkhof F, Scheltens P, Ossenkoppele R. Cognitive reserve and clinical progression in Alzheimer disease: A paradoxical relationship. Neurology 2019; 93:e334-e346. [PMID: 31266904 PMCID: PMC6669930 DOI: 10.1212/wnl.0000000000007821] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Accepted: 03/08/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate the relationship between cognitive reserve (CR) and clinical progression across the Alzheimer disease (AD) spectrum. METHODS We selected 839 β-amyloid (Aβ)-positive participants with normal cognition (NC, n = 175), mild cognitive impairment (MCI, n = 437), or AD dementia (n = 227) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). CR was quantified using standardized residuals (W scores) from a (covariate-adjusted) linear regression with global cognition (13-item Alzheimer's Disease Assessment Scale-cognitive subscale) as an independent variable of interest, and either gray matter volumes or white matter hyperintensity volume as dependent variables. These W scores, reflecting whether an individual's degree of cerebral damage is lower or higher than clinically expected, were tested as predictors of diagnostic conversion (i.e., NC to MCI/AD dementia, or MCI to AD dementia) and longitudinal changes in memory (ADNI-MEM) and executive functions (ADNI-EF). RESULTS The median follow-up period was 24 months (interquartile range 6-42). Corrected for age, sex, APOE4 status, and baseline cerebral damage, higher gray matter volume-based W scores (i.e., greater CR) were associated with a lower diagnostic conversion risk (hazard ratio [HR] 0.22, p < 0.001) and slower decline in memory (β = 0.48, p < 0.001) and executive function (β = 0.67, p < 0.001). Stratified by disease stage, we found similar results for NC (diagnostic conversion: HR 0.30, p = 0.038; ADNI-MEM: β = 0.52, p = 0.028; ADNI-EF: β = 0.42, p = 0.077) and MCI (diagnostic conversion: HR 0.21, p < 0.001; ADNI-MEM: β = 0.43, p = 0.003; ADNI-EF: β = 0.59, p < 0.001), but opposite findings (i.e., more rapid decline) for AD dementia (ADNI-MEM: β = -0.91, p = 0.002; ADNI-EF: β = -0.77, p = 0.081). CONCLUSIONS Among Aβ-positive individuals, greater CR related to attenuated clinical progression in predementia stages of AD, but accelerated cognitive decline after the onset of dementia.
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Affiliation(s)
- Anna Catharina van Loenhoud
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - Wiesje Maria van der Flier
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Alle Meije Wink
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Ellen Dicks
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Colin Groot
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Jos Twisk
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From Alzheimer Center Amsterdam, Department of Neurology (A.C.v.L., W.M.v.d.F., E.D., C.G., P.S., R.O.), and Department of Radiology and Nuclear Medicine (A.M.W., F.B., R.O.), Amsterdam Neuroscience, and Department of Epidemiology and Biostatistics (W.M.v.d.F., J.T.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; Institutes of Neurology and Healthcare Engineering (F.B.), University College London, UK; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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170
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Alosco ML, Sugarman MA, Besser LM, Tripodis Y, Martin B, Palmisano JN, Kowall NW, Au R, Mez J, DeCarli C, Stein TD, McKee AC, Killiany RJ, Stern RA. A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer's Disease Neuropathology. J Alzheimers Dis 2019; 63:1347-1360. [PMID: 29843242 DOI: 10.3233/jad-180017] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) on magnetic resonance imaging (MRI) have been postulated to be a core feature of Alzheimer's disease. Clinicopathological studies are needed to elucidate and confirm this possibility. OBJECTIVE This study examined: 1) the association between antemortem WMH and autopsy-confirmed Alzheimer's disease neuropathology (ADNP), 2) the relationship between WMH and dementia in participants with ADNP, and 3) the relationships among cerebrovascular disease, WMH, and ADNP. METHODS The sample included 82 participants from the National Alzheimer's Coordinating Center's Data Sets who had quantitated volume of WMH from antemortem FLAIR MRI and available neuropathological data. The Clinical Dementia Rating (CDR) scale (from MRI visit) operationalized dementia status. ADNP+ was defined by moderate to frequent neuritic plaques and Braak stage III-VI at autopsy. Cerebrovascular disease neuropathology included infarcts or lacunes, microinfarcts, arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy. RESULTS 60/82 participants were ADNP+. Greater volume of WMH predicted increased odds for ADNP (p = 0.037). In ADNP+ participants, greater WMH corresponded with increased odds for dementia (CDR≥1; p = 0.038). WMH predicted cerebral amyloid angiopathy, microinfarcts, infarcts, and lacunes (ps < 0.04). ADNP+ participants were more likely to have moderate-severe arteriolosclerosis and cerebral amyloid angiopathy compared to ADNP-participants (ps < 0.04). CONCLUSIONS This study found a direct association between total volume of WMH and increased odds for having ADNP. In patients with Alzheimer's disease, FLAIR MRI WMH may be able to provide key insight into disease severity and progression. The association between WMH and ADNP may be explained by underlying cerebrovascular disease.
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Affiliation(s)
- Michael L Alosco
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Michael A Sugarman
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neuropsychology, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA
| | - Lilah M Besser
- National Alzheimer's Coordinating Center, University of Washington, Seattle, WA, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,Neurology Service, VA Boston Healthcare System, Boston, MA, USA
| | - Rhoda Au
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA, USA.,Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Charles DeCarli
- Department of Neurology, University of California at Davis Health System, Sacramento, CA, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA.,Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA.,U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, USA.,Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.,Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center, Boston University School of Medicine, Boston, MA, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA, USA.,Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.,Department of Neurosurgery, Boston University School of Medicine, Boston, MA, USA
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171
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NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement 2019; 14:535-562. [PMID: 29653606 PMCID: PMC5958625 DOI: 10.1016/j.jalz.2018.02.018] [Citation(s) in RCA: 6353] [Impact Index Per Article: 1058.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 02/21/2018] [Accepted: 02/27/2018] [Indexed: 02/06/2023]
Abstract
In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
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172
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Kalheim LF, Fladby T, Coello C, Bjørnerud A, Selnes P. [18F]-Flutemetamol Uptake in Cortex and White Matter: Comparison with Cerebrospinal Fluid Biomarkers and [18F]-Fludeoxyglucose. J Alzheimers Dis 2019; 62:1595-1607. [PMID: 29504529 PMCID: PMC6218124 DOI: 10.3233/jad-170582] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Flutemetamol (18F-Flut) is an [18F]-labelled amyloid PET tracer with increasing availability. The main objectives of this study were to investigate 1) cerebrospinal fluid (CSF) Aβ 1-42 (Aβ42) concentrations associated with regional 18F-Flut uptake, 2) associations between cortical 18F-Flut and [18F]-fludeoxyglucose (18F-FDG)-PET, and 3) the potential use of 18F-Flut in WM pathology. Cognitively impaired, nondemented subjects were recruited (n = 44). CSF was drawn, and 18F-Flut-PET, 18F-FDG-PET, and MRI performed. Our main findings were: 1) Different Alzheimer’s disease predilection areas showed increased 18F-Flut retention at different CSF Aβ42 concentrations (posterior regions were involved at higher concentrations). 2) There were strong negative correlations between regional cortical 18F-Flut and 18F-FDG uptake. 3) Increased 18F-Flut uptake were observed in multiple subcortical regions in amyloid positive subjects, including investigated reference regions. However, WM hyperintensity 18F-Flut standardized uptake value ratios (SUVr) were not significantly different, thus we cannot definitely conclude that the higher uptake in 18F-Flut(+) is due to amyloid deposition. In conclusion, our findings support clinical use of CSF Aβ42, putatively relate decreasing CSF Aβ42 concentrations to a sequence of regional amyloid deposition, and associate amyloid pathology to cortical hypometabolism. However, we cannot conclude that 18F-Flut-PET is a suitable marker for WM pathology due to high aberrant WM uptake.
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Affiliation(s)
- Lisa Flem Kalheim
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Christopher Coello
- Preclinical PET/CT, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Atle Bjørnerud
- The Intervention Centre, Oslo University Hospital, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
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Abstract
Following the development of the first methods to measure the core Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers total-tau (T-tau), phosphorylated tau (P-tau) and the 42 amino acid form of amyloid-β (Aβ42), there has been an enormous expansion of this scientific research area. Today, it is generally acknowledged that these biochemical tests reflect several central pathophysiological features of AD and contribute diagnostically relevant information, also for prodromal AD. In this article in the 20th anniversary issue of the Journal of Alzheimer’s Disease, we review the AD biomarkers, from early assay development to their entrance into diagnostic criteria. We also summarize the long journey of standardization and the development of assays on fully automated instruments, where we now have high precision and stable assays that will serve as the basis for common cut-off levels and a more general introduction of these diagnostic tests in clinical routine practice. We also discuss the latest expansion of the AD CSF biomarker toolbox that now also contains synaptic proteins such as neurogranin, which seemingly is specific for AD and predicts rate of future cognitive deterioration. Last, we are at the brink of having blood biomarkers that may be implemented as screening tools in the early clinical management of patients with cognitive problems and suspected AD. Whether this will become true, and whether it will be plasma Aβ42, the Aβ42/40 ratio, or neurofilament light, or a combination of these, remains to be established in future clinical neurochemical studies.
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Affiliation(s)
- Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
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174
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Ballard C, Atri A, Boneva N, Cummings JL, Frölich L, Molinuevo JL, Tariot PN, Raket LL. Enrichment factors for clinical trials in mild-to-moderate Alzheimer's disease. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2019; 5:164-174. [PMID: 31193334 PMCID: PMC6527908 DOI: 10.1016/j.trci.2019.04.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Introduction Heterogeneity of outcomes in Alzheimer's disease (AD) clinical trials necessitates large sample sizes and contributes to study failures. This analysis determined whether mild-to-moderate AD populations could be enriched for cognitive decline based on apolipoprotein (APOE) ε4 genotype, family history of AD, and amyloid abnormalities. Methods Modeling estimated the number of randomized patients needed to detect a 2-point treatment difference on the AD Assessment Scale–Cognitive subscale using placebo data from three randomized, double-blind trials (ClinicalTrials.gov Identifiers: NCT01955161, NCT02006641, and NCT02006654). Results An 80% power to detect a 2-point treatment effect required the randomization of 148 amyloid-positive patients; 178 ε4 homozygous or amyloid-positive patients; and 231 ε4 homozygous, family history-positive, or amyloid-positive patients, compared with 1619 unenriched patients (per arm). Discussion Enrichment in mild-to-moderate AD clinical trials can be achieved using combinations of biomarkers/risk factors to increase the likelihood of observing potential treatment effects. APOE ɛ4, family history, and amyloid status can enrich mild-to-moderate AD samples. Enrichment increases the likelihood of detecting a treatment effect on cognition. Enrichment may reduce sample sizes in clinical trials of symptomatic drugs in AD.
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Affiliation(s)
- Clive Ballard
- University of Exeter Medical School, Exeter, UK
- Corresponding author. Tel.: +44 1392 722894.
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, AZ, USA
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Lutz Frölich
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - José Luis Molinuevo
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Hospital Clinic i Universitari, Barcelona, Spain
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
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175
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Hlavka JP, Mattke S, Liu JL. Assessing the Preparedness of the Health Care System Infrastructure in Six European Countries for an Alzheimer's Treatment. RAND HEALTH QUARTERLY 2019; 8:2. [PMID: 31205802 PMCID: PMC6557037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
No disease-modifying therapy is currently available for Alzheimer's disease, but therapies are in development, and one may become available in the near future. Based on results from early-stage clinical trials, therapeutic development has focused on the hypothesis that Alzheimer's dementia must be prevented rather than cured, because candidate treatments have not been able to reverse the course of dementia. Thus, current trials target patients with early-stage Alzheimer's disease. Were a therapy to become available, patients could undergo first screening for signs of early-stage memory loss or mild cognitive impairment (MCI), testing for the Alzheimer's disease pathology, and then treatment with the aim of halting or slowing progression to Alzheimer's dementia. An important health systems challenge will arise if this new treatment paradigm bears out in late-stage clinical trials. In the 28 European Union countries, we estimate that approximately 20 million individuals over age 55 have MCI, although most people have not been tested for disease pathology. Thus, when a therapy first becomes available, there would be a substantial number of existing (or prevalent) MCI patients who would require screening, diagnosis, and then treatment as quickly as possible to prevent the progression to full-blown Alzheimer's dementia. This research analyzes the preparedness of the health care systems in six European countries-France, Germany, Italy, Spain, Sweden, and the United Kingdom-to ensure timely diagnosis and treatment of patients if a disease-modifying therapy for Alzheimer's becomes available.
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176
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CSF level of β-amyloid peptide predicts mortality in Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2019; 11:29. [PMID: 30922415 PMCID: PMC6440001 DOI: 10.1186/s13195-019-0481-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 03/08/2019] [Indexed: 12/31/2022]
Abstract
Objective Alzheimer’s disease (AD) is the sixth leading cause of death, with an average survival estimated between 5 and 10 years after diagnosis. Despite recent advances in diagnostic criteria of AD, few studies have used biomarker-based diagnostics to determine the prognostic factors of AD. We investigate predictors of death and institutionalization in a population of AD patients with high probability of AD physiopathology process assessed by positivity of three CSF biomarkers. Methods Three hundred twenty-one AD patients with abnormal values for CSF beta-amyloid peptide (Aβ42), tau, and phosphorylated tau levels were recruited from a memory clinic-based registry between 2008 and 2017 (Lariboisiere hospital, Paris, France) and followed during a median period of 3.9 years. We used multivariable Cox models to estimate the hazard ratio (HR) of death and institutionalization for baseline clinical data, genotype of the apolipoprotein E (APOE), and levels of CSF biomarkers. Results A total of 71 (22%) patients were institutionalized and 57 (18%) died during the follow-up. Greater age, male sex, lower MMSE score, and lower CSF Aβ42 level were associated with an increased risk of mortality. One standard deviation lower CSF Aβ42 (135 pg/mL) was associated with a 89% increased risk of death (95% CI = 1.25–2.86; p = 0.002). This association was not modified by age, sex, education, APOE ε4, and disease severity. There was no evidence of an association of tau CSF biomarkers with mortality. None of the CSF biomarkers were associated with institutionalization. Conclusions Lower CSF Aβ42 is a strong prognostic marker of mortality in AD patients, independently of age or severity of the disease. Whether drugs targeting beta-amyloid peptide could have an effect on mortality of AD patients should be investigated in future clinical trials.
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177
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Salvadó G, Molinuevo JL, Brugulat-Serrat A, Falcon C, Grau-Rivera O, Suárez-Calvet M, Pavia J, Niñerola-Baizán A, Perissinotti A, Lomeña F, Minguillon C, Fauria K, Zetterberg H, Blennow K, Gispert JD. Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers. Alzheimers Res Ther 2019; 11:27. [PMID: 30902090 PMCID: PMC6429814 DOI: 10.1186/s13195-019-0478-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 02/27/2019] [Indexed: 01/22/2023]
Abstract
BACKGROUND The Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts. METHODS A total of 516 participants of the ALFA+ Study (N = 205) and ADNI (N = 311) underwent amyloid PET imaging ([18F]flutemetamol and [18F]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys® tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of Aβ42, tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden's J Index or the overall percentage agreement recorded. RESULTS All Centiloid cut-offs fell within the range of 25-35, except for CSF Aβ42 that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/Aβ42 ratios was higher than that of CSF Aβ42. Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs. CONCLUSIONS A cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels. TRIAL REGISTRATION ALFA+ Study, NCT02485730 ALFA PET Sub-study, NCT02685969.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Anna Brugulat-Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
| | - Javier Pavia
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
- Nuclear Medicine Department, Hospital Clínic, Barcelona, Spain
- Instititut d’Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | | | | | | | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005 Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Bioengeniería, Biomateriales y Nanomedicina, Madrid, Spain
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178
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Association of IL1RAP-related genetic variation with cerebrospinal fluid concentration of Alzheimer-associated tau protein. Sci Rep 2019; 9:2460. [PMID: 30792413 PMCID: PMC6385252 DOI: 10.1038/s41598-018-36650-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 11/26/2018] [Indexed: 11/13/2022] Open
Abstract
A possible involvement of the gene IL1RAP (interleukin-1 receptor-associated protein) in the pathogenesis of Alzheimer’s disease (AD) has been suggested in GWASs of cerebrospinal fluid (CSF) tau levels and longitudinal change in brain amyloid burden. The aim of this study was to examine previously implicated genetic markers in and near IL1RAP in relation to AD risk, CSF tau and Aβ biomarkers, as well as cognitive decline, in a case (AD)-control study and an age homogenous population-based cohort. Genotyping of IL1RAP-related single nucleotide polymorphisms (SNPs), selected based on previous GWAS results, was performed. 3446 individuals (1154 AD cases and 2292 controls) were included in the analyses of AD risk, 1400 individuals (cognitively normal = 747, AD = 653) in the CSF biomarker analyses, and 861 individuals in the analyses of cognitive decline. We found no relation between IL1RAP-related SNPs and AD risk. However, CSF total-tau and phospho-tau were associated with the SNP rs9877502 (p = 6 × 10−3 and p = 5 × 10−4). Further, nominal associations (p = 0.03–0.05) were found between three other SNPs and CSF biomarker levels, or levels of cognitive performance and decline in a sub-sample from the general population. These results support previous studies suggesting an association of IL1RAP with disease intensity of AD.
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179
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Maletínská L, Popelová A, Železná B, Bencze M, Kuneš J. The impact of anorexigenic peptides in experimental models of Alzheimer's disease pathology. J Endocrinol 2019; 240:R47-R72. [PMID: 30475219 DOI: 10.1530/joe-18-0532] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 11/20/2018] [Indexed: 12/16/2022]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the elderly population. Numerous epidemiological and experimental studies have demonstrated that patients who suffer from obesity or type 2 diabetes mellitus have a higher risk of cognitive dysfunction and AD. Several recent studies demonstrated that food intake-lowering (anorexigenic) peptides have the potential to improve metabolic disorders and that they may also potentially be useful in the treatment of neurodegenerative diseases. In this review, the neuroprotective effects of anorexigenic peptides of both peripheral and central origins are discussed. Moreover, the role of leptin as a key modulator of energy homeostasis is discussed in relation to its interaction with anorexigenic peptides and their analogs in AD-like pathology. Although there is no perfect experimental model of human AD pathology, animal studies have already proven that anorexigenic peptides exhibit neuroprotective properties. This phenomenon is extremely important for the potential development of new drugs in view of the aging of the human population and of the significantly increasing incidence of AD.
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Affiliation(s)
- Lenka Maletínská
- Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic
| | - Andrea Popelová
- Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic
| | - Blanka Železná
- Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic
| | - Michal Bencze
- Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic
- Institute of Physiology AS CR, Prague, Czech Republic
| | - Jaroslav Kuneš
- Institute of Organic Chemistry and Biochemistry AS CR, Prague, Czech Republic
- Institute of Physiology AS CR, Prague, Czech Republic
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180
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Parnetti L, Chipi E, Salvadori N, D'Andrea K, Eusebi P. Prevalence and risk of progression of preclinical Alzheimer's disease stages: a systematic review and meta-analysis. ALZHEIMERS RESEARCH & THERAPY 2019; 11:7. [PMID: 30646955 PMCID: PMC6334406 DOI: 10.1186/s13195-018-0459-7] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 12/10/2018] [Indexed: 01/10/2023]
Abstract
Background Alzheimer’s disease (AD) pathology begins several years before the clinical onset. The long preclinical phase is composed of three stages according to the 2011National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria, followed by mild cognitive impairment (MCI), a featured clinical entity defined as “due to AD”, or “prodromal AD”, when pathophysiological biomarkers (i.e., cerebrospinal fluid or positron emission tomography with amyloid tracer) are positive. In the clinical setting, there is a clear need to detect the earliest symptoms not yet fulfilling MCI criteria, in order to proceed to biomarker assessment for diagnostic definition, thus offering treatment with disease-modifying drugs to patients as early as possible. According to the available evidence, we thus estimated the prevalence and risk of progression at each preclinical AD stage, with special interest in Stage 3. Methods Cross-sectional and longitudinal studies published from April 2008 to May 2018 were obtained through MEDLINE-PubMed, screened, and systematically reviewed by four independent reviewers. Data from included studies were meta-analyzed using random-effects models. Heterogeneity was assessed by I2 statistics. Results Estimated overall prevalence of preclinical AD was 22% (95% CI = 18–26%). Rate of biomarker positivity overlapped in cognitively normal individuals and people with subjective cognitive decline. The risk of progression increases across preclinical AD stages, with individuals classified as NIA-AA Stage 3 showing the highest risk (73%, 95% CI = 40–92%) compared to those in Stage 2 (38%, 95% CI = 21–59%) and Stage 1 (20%, 95% CI = 10–34%). Conclusion Available data consistently show that risk of progression increases across the preclinical AD stages, where Stage 3 shows a risk of progression comparable to MCI due to AD. Accordingly, an effort should be made to also operationalize the diagnostic work-up in subjects with subtle cognitive deficits not yet fulfilling MCI criteria. The possibility to define, in the clinical routine, a patient as “pre-MCI due to AD” could offer these subjects the opportunity to use disease-modifying drugs at best. Electronic supplementary material The online version of this article (10.1186/s13195-018-0459-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lucilla Parnetti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy.
| | - Elena Chipi
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Nicola Salvadori
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Katia D'Andrea
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
| | - Paolo Eusebi
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy
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Leuzy A, Chiotis K, Lemoine L, Gillberg PG, Almkvist O, Rodriguez-Vieitez E, Nordberg A. Tau PET imaging in neurodegenerative tauopathies-still a challenge. Mol Psychiatry 2019; 24:1112-1134. [PMID: 30635637 PMCID: PMC6756230 DOI: 10.1038/s41380-018-0342-8] [Citation(s) in RCA: 415] [Impact Index Per Article: 69.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 10/19/2018] [Accepted: 11/26/2018] [Indexed: 12/14/2022]
Abstract
The accumulation of pathological misfolded tau is a feature common to a collective of neurodegenerative disorders known as tauopathies, of which Alzheimer's disease (AD) is the most common. Related tauopathies include progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), Down's syndrome (DS), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Investigation of the role of tau pathology in the onset and progression of these disorders is now possible due the recent advent of tau-specific ligands for use with positron emission tomography (PET), including first- (e.g., [18F]THK5317, [18F]THK5351, [18F]AV1451, and [11C]PBB3) and second-generation compounds [namely [18F]MK-6240, [18F]RO-948 (previously referred to as [18F]RO69558948), [18F]PI-2620, [18F]GTP1, [18F]PM-PBB3, and [18F]JNJ64349311 ([18F]JNJ311) and its derivative [18F]JNJ-067)]. In this review we describe and discuss findings from in vitro and in vivo studies using both initial and new tau ligands, including their relation to biomarkers for amyloid-β and neurodegeneration, and cognitive findings. Lastly, methodological considerations for the quantification of in vivo ligand binding are addressed, along with potential future applications of tau PET, including therapeutic trials.
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Affiliation(s)
- Antoine Leuzy
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Konstantinos Chiotis
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0000 9241 5705grid.24381.3cTheme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Laetitia Lemoine
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Per-Göran Gillberg
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Ove Almkvist
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,0000 0004 1936 9377grid.10548.38Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- 0000 0004 1937 0626grid.4714.6Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. .,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
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182
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Arendash G, Cao C, Abulaban H, Baranowski R, Wisniewski G, Becerra L, Andel R, Lin X, Zhang X, Wittwer D, Moulton J, Arrington J, Smith A. A Clinical Trial of Transcranial Electromagnetic Treatment in Alzheimer's Disease: Cognitive Enhancement and Associated Changes in Cerebrospinal Fluid, Blood, and Brain Imaging. J Alzheimers Dis 2019; 71:57-82. [PMID: 31403948 PMCID: PMC6839500 DOI: 10.3233/jad-190367] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/13/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Small aggregates (oligomers) of the toxic proteins amyloid-β (Aβ) and phospho-tau (p-tau) are essential contributors to Alzheimer's disease (AD). In mouse models for AD or human AD brain extracts, Transcranial Electromagnetic Treatment (TEMT) disaggregates both Aβ and p-tau oligomers, and induces brain mitochondrial enhancement. These apparent "disease-modifying" actions of TEMT both prevent and reverse memory impairment in AD transgenic mice. OBJECTIVE To evaluate the safety and initial clinical efficacy of TEMT against AD, a comprehensive open-label clinical trial was performed. METHODS Eight mild/moderate AD patients were treated with TEMT in-home by their caregivers for 2 months utilizing a unique head device. TEMT was given for two 1-hour periods each day, with subjects primarily evaluated at baseline, end-of-treatment, and 2 weeks following treatment completion. RESULTS No deleterious behavioral effects, discomfort, or physiologic changes resulted from 2 months of TEMT, as well as no evidence of tumor or microhemorrhage induction. TEMT induced clinically important and statistically significant improvements in ADAS-cog, as well as in the Rey AVLT. TEMT also produced increases in cerebrospinal fluid (CSF) levels of soluble Aβ1-40 and Aβ1-42, cognition-related changes in CSF oligomeric Aβ, a decreased CSF p-tau/Aβ1-42 ratio, and reduced levels of oligomeric Aβ in plasma. Pre- versus post-treatment FDG-PET brain scans revealed stable cerebral glucose utilization, with several subjects exhibiting enhanced glucose utilization. Evaluation of diffusion tensor imaging (fractional anisotropy) scans in individual subjects provided support for TEMT-induced increases in functional connectivity within the cognitively-important cingulate cortex/cingulum. CONCLUSION TEMT administration to AD subjects appears to be safe, while providing cognitive enhancement, changes to CSF/blood AD markers, and evidence of stable/enhanced brain connectivity.
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Affiliation(s)
| | - Chuanhai Cao
- College of Pharmacy, University of South Florida, Tampa, FL, USA
| | - Haitham Abulaban
- University of South Florida Health/Byrd Alzheimer’s Institute, Tampa, FL, USA
| | | | | | | | - Ross Andel
- School of Aging Studies, University of South Florida, Tampa, FL, USA
- Department of Neurology, 2nd Faculty of Medicine, Charles University/Motol University Hospital, Prague, Czech Republic
| | - Xiaoyang Lin
- College of Pharmacy, University of South Florida, Tampa, FL, USA
| | - Xiaolin Zhang
- College of Pharmacy, University of South Florida, Tampa, FL, USA
| | | | | | | | - Amanda Smith
- University of South Florida Health/Byrd Alzheimer’s Institute, Tampa, FL, USA
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183
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Westwood S, Baird AL, Hye A, Ashton NJ, Nevado-Holgado AJ, Anand SN, Liu B, Newby D, Bazenet C, Kiddle SJ, Ward M, Newton B, Desai K, Tan Hehir C, Zanette M, Galimberti D, Parnetti L, Lleó A, Baker S, Narayan VA, van der Flier WM, Scheltens P, Teunissen CE, Visser PJ, Lovestone S. Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [ 18F]-Flutemetamol PET Scan Result. Front Aging Neurosci 2018; 10:409. [PMID: 30618716 PMCID: PMC6297196 DOI: 10.3389/fnagi.2018.00409] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/28/2018] [Indexed: 01/01/2023] Open
Abstract
Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ42 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ42 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ42 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/Aβ42. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ42 (P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.
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Affiliation(s)
- Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alison L. Baird
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Abdul Hye
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Nicholas J. Ashton
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | | | - Sneha N. Anand
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Benjamine Liu
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Chantal Bazenet
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
| | - Steven J. Kiddle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
| | - Malcolm Ward
- Proteomics Facility, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Ben Newton
- GE Healthcare Life Sciences Core Imaging, London, United Kingdom
| | - Keyur Desai
- Biosciences, GE Global Research, Niskayuna, NY, United States
| | | | - Michelle Zanette
- GE Healthcare Life Sciences Core Imaging, Marlborough, MA, United States
| | - Daniela Galimberti
- Neurodegenerative Diseases Unit, Centro Dino Ferrari, University of Milan, Milan, Italy
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Lucilla Parnetti
- Center for Memory Disorders and Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
| | - Alberto Lleó
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Susan Baker
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Vaibhav A. Narayan
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Charlotte E. Teunissen
- Department of Clinical Chemistry, Neurochemistry Lab and Biobank, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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184
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Demaegd K, Schymkowitz J, Rousseau F. Transcellular Spreading of Tau in Tauopathies. Chembiochem 2018; 19:2424-2432. [PMID: 30133080 PMCID: PMC6391987 DOI: 10.1002/cbic.201800288] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Revised: 08/21/2018] [Indexed: 11/20/2022]
Abstract
Tau, a microtubule-associated protein playing a key role in a group of neurodegenerative diseases such as Alzheimer's disease, spreads throughout the brain, inducing pathology. A model akin to the spreading of prions has been raised owing to similar characteristics of inducing an abnormal protein conformation as a method of self-amplification, spreading protein aggregates over anatomically linked pathways. The search to identify the "seeds" that induce conformational change has received much attention; however, less is known about the mechanisms by which tau is transmitted from cell to cell, so-called "transcellular spreading". In this review, we gather evidence regarding the spreading of tau throughout the brain and provide an overview of methods by which tau can be released from neurons as well as taken up. Furthermore, we bring together mechanisms of neurotoxicity behind tau spreading. Advancing our understanding about the spreading of tau can guide the search for therapeutic options for multiple neurodegenerative diseases aggregating tau.
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Affiliation(s)
- Koen Demaegd
- Switch LaboratoryDepartment of Cellular and Molecular MedicineKULeuvenHerestraat 49Box 802Room 08.6833000LeuvenBelgium
- Switch LaboratoryVIB Center for Brain and Disease ResearchHerestraat 49, box 802, room 08.6833000LeuvenBelgium
| | - Joost Schymkowitz
- Switch LaboratoryDepartment of Cellular and Molecular MedicineKULeuvenHerestraat 49Box 802Room 08.6833000LeuvenBelgium
- Switch LaboratoryVIB Center for Brain and Disease ResearchHerestraat 49, box 802, room 08.6833000LeuvenBelgium
| | - Frederic Rousseau
- Switch LaboratoryDepartment of Cellular and Molecular MedicineKULeuvenHerestraat 49Box 802Room 08.6833000LeuvenBelgium
- Switch LaboratoryVIB Center for Brain and Disease ResearchHerestraat 49, box 802, room 08.6833000LeuvenBelgium
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185
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Li R, Nguyen T, Potter T, Zhang Y. Dynamic cortical connectivity alterations associated with Alzheimer's disease: An EEG and fNIRS integration study. NEUROIMAGE-CLINICAL 2018; 21:101622. [PMID: 30527906 PMCID: PMC6411655 DOI: 10.1016/j.nicl.2018.101622] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 11/08/2018] [Accepted: 12/01/2018] [Indexed: 12/18/2022]
Abstract
Emerging evidence indicates that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain network. Exploring alterations in the AD brain network is therefore of great importance for understanding and treating the disease. This study employs an integrative functional near-infrared spectroscopy (fNIRS) – electroencephalography (EEG) analysis approach to explore dynamic, regional alterations in the AD-linked brain network. FNIRS and EEG data were simultaneously recorded from 14 participants (8 healthy controls and 6 patients with mild AD) during a digit verbal span task (DVST). FNIRS-based spatial constraints were used as priors for EEG source localization. Graph-based indices were then calculated from the reconstructed EEG sources to assess regional differences between the groups. Results show that patients with mild AD revealed weaker and suppressed cortical connectivity in the high alpha band and in beta band to the orbitofrontal and parietal regions. AD-induced brain networks, compared to the networks of age-matched healthy controls, were mainly characterized by lower degree, clustering coefficient at the frontal pole and medial orbitofrontal across all frequency ranges. Additionally, the AD group also consistently showed higher index values for these graph-based indices at the superior temporal sulcus. These findings not only validate the feasibility of utilizing the proposed integrated EEG-fNIRS analysis to better understand the spatiotemporal dynamics of brain activity, but also contribute to the development of network-based approaches for understanding the mechanisms that underlie the progression of AD. Dynamic brain networks of healthy controls and patients with mild AD are documented via an integrative fNIRS-EEG approach. FNIRS-based constraints are employed as spatial priors for EEG source localization. Mild AD group reveals weaker connectivity to the orbitofrontal and parietal regions in high alpha band and beta band. AD-linked brain networks are characterized by lower degree and clustering coefficient at the frontal area. AD group also reveals higher index values for these graph-based indices at the superior temporal sulcus.
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Affiliation(s)
- Rihui Li
- Department of Biomedical Engineering, University of Houston, Houston, USA; Guangdong Provincial Work Injury Rehabilitation Hospital, Guangzhou, China
| | - Thinh Nguyen
- Department of Biomedical Engineering, University of Houston, Houston, USA
| | - Thomas Potter
- Department of Biomedical Engineering, University of Houston, Houston, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, USA.
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186
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Molinuevo JL, Ayton S, Batrla R, Bednar MM, Bittner T, Cummings J, Fagan AM, Hampel H, Mielke MM, Mikulskis A, O'Bryant S, Scheltens P, Sevigny J, Shaw LM, Soares HD, Tong G, Trojanowski JQ, Zetterberg H, Blennow K. Current state of Alzheimer's fluid biomarkers. Acta Neuropathol 2018; 136:821-853. [PMID: 30488277 PMCID: PMC6280827 DOI: 10.1007/s00401-018-1932-x] [Citation(s) in RCA: 360] [Impact Index Per Article: 51.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 11/05/2018] [Accepted: 11/07/2018] [Indexed: 12/12/2022]
Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with a complex and heterogeneous pathophysiology. The number of people living with AD is predicted to increase; however, there are no disease-modifying therapies currently available and none have been successful in late-stage clinical trials. Fluid biomarkers measured in cerebrospinal fluid (CSF) or blood hold promise for enabling more effective drug development and establishing a more personalized medicine approach for AD diagnosis and treatment. Biomarkers used in drug development programmes should be qualified for a specific context of use (COU). These COUs include, but are not limited to, subject/patient selection, assessment of disease state and/or prognosis, assessment of mechanism of action, dose optimization, drug response monitoring, efficacy maximization, and toxicity/adverse reactions identification and minimization. The core AD CSF biomarkers Aβ42, t-tau, and p-tau are recognized by research guidelines for their diagnostic utility and are being considered for qualification for subject selection in clinical trials. However, there is a need to better understand their potential for other COUs, as well as identify additional fluid biomarkers reflecting other aspects of AD pathophysiology. Several novel fluid biomarkers have been proposed, but their role in AD pathology and their use as AD biomarkers have yet to be validated. In this review, we summarize some of the pathological mechanisms implicated in the sporadic AD and highlight the data for several established and novel fluid biomarkers (including BACE1, TREM2, YKL-40, IP-10, neurogranin, SNAP-25, synaptotagmin, α-synuclein, TDP-43, ferritin, VILIP-1, and NF-L) associated with each mechanism. We discuss the potential COUs for each biomarker.
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Affiliation(s)
- José Luis Molinuevo
- BarcelonaBeta Brain Research Center, Fundació Pasqual Maragall, Universitat Pompeu Fabra, Barcelona, Spain
- Unidad de Alzheimer y otros trastornos cognitivos, Hospital Clinic-IDIBAPS, Barcelona, Spain
| | - Scott Ayton
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Richard Batrla
- Roche Centralised and Point of Care Solutions, Roche Diagnostics International, Rotkreuz, Switzerland
| | - Martin M Bednar
- Neuroscience Therapeutic Area Unit, Takeda Development Centre Americas Ltd, Cambridge, MA, USA
| | - Tobias Bittner
- Genentech, A Member of the Roche Group, Basel, Switzerland
| | - Jeffrey Cummings
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Harald Hampel
- AXA Research Fund and Sorbonne University Chair, Paris, France
- Sorbonne University, GRC No 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Paris, France
- Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France
- Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Michelle M Mielke
- Departments of Epidemiology and Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Sid O'Bryant
- Department of Pharmacology and Neuroscience; Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Philip Scheltens
- Department of Neurology and Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Jeffrey Sevigny
- Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Holly D Soares
- Clinical Development Neurology, AbbVie, North Chicago, IL, USA
| | | | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal Campus, Sahlgrenska University Hospital, 431 80, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal Campus, Sahlgrenska University Hospital, 431 80, Mölndal, Sweden.
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187
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Blennow K, Zetterberg H. Biomarkers for Alzheimer's disease: current status and prospects for the future. J Intern Med 2018; 284:643-663. [PMID: 30051512 DOI: 10.1111/joim.12816] [Citation(s) in RCA: 562] [Impact Index Per Article: 80.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Accumulating data from the clinical research support that the core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers amyloid-β (Aβ42), total tau (T-tau), and phosphorylated tau (P-tau) reflect key elements of AD pathophysiology. Importantly, a large number of clinical studies very consistently show that these biomarkers contribute with diagnostically relevant information, also in the early disease stages. Recent technical developments have made it possible to measure these biomarkers using fully automated assays with high precision and stability. Standardization efforts have given certified reference materials for CSF Aβ42, with the aim to harmonize results between assay formats that would allow for uniform global reference limits and cut-off values. These encouraging developments have led to that the core AD CSF biomarkers have a central position in the novel diagnostic criteria for the disease and in the recent National Institute on Aging and Alzheimer's Association biological definition of AD. Taken together, this progress will likely serve as the basis for a more general introduction of these diagnostic tests in clinical routine practice. However, the heterogeneity of pathology in late-onset AD calls for an expansion of the AD CSF biomarker toolbox with additional biomarkers reflecting additional aspects of AD pathophysiology. One promising candidate is the synaptic protein neurogranin that seems specific for AD and predicts future rate of cognitive deterioration. Further, recent studies bring hope for easily accessible and cost-effective screening tools in the early diagnostic evaluation of patients with cognitive problems (and suspected AD) in primary care. In this respect, technical developments with ultrasensitive immunoassays and novel mass spectrometry techniques give promise of biomarkers to monitor brain amyloidosis (the Aβ42/40 or APP669-711/Aβ42 ratios) and neurodegeneration (tau and neurofilament light proteins) in plasma samples, but future studies are warranted to validate these promising results further.
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Affiliation(s)
- K Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - H Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
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188
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Yoo YK, Lee J, Kim H, Hwang KS, Yoon DS, Lee JH. Toward Exosome-Based Neuronal Diagnostic Devices. MICROMACHINES 2018; 9:mi9120634. [PMID: 30501125 PMCID: PMC6315917 DOI: 10.3390/mi9120634] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 11/16/2018] [Accepted: 11/22/2018] [Indexed: 12/13/2022]
Abstract
Targeting exosome for liquid biopsy has gained significant attention for its diagnostic and therapeutic potential. For detecting neuronal disease diagnosis such as Alzheimer's disease (AD), the main technique for identifying AD still relies on positron-emission tomography (PET) imaging to detect the presence of amyloid-β (Aβ). While the detection of Aβ in cerebrospinal fluid has also been suggested as a marker for AD, the lack of quantitative measurements has compromised existing assays. In cerebrospinal fluid, in addition to Aβ, T-Tau, and P-Tau, alpha-synuclein has been considered a biomarker of neurodegeneration. This review suggests that and explains how the exosome can be used as a neuronal diagnostic component. To this end, we summarize current progress in exosome preparation/isolation and quantification techniques and comment on the outlooks for neuronal exosome-based diagnostic techniques.
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Affiliation(s)
- Yong Kyoung Yoo
- Department of Electrical Engineering, Kwangwoon University, 447-1 Wolgye, Nowon, Seoul 01897, Korea.
| | - Junwoo Lee
- Department of Electrical Engineering, Kwangwoon University, 447-1 Wolgye, Nowon, Seoul 01897, Korea.
| | - Hyungsuk Kim
- Department of Electrical Engineering, Kwangwoon University, 447-1 Wolgye, Nowon, Seoul 01897, Korea.
| | - Kyo Seon Hwang
- Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, Seoul 02447, Korea.
| | - Dae Sung Yoon
- School of Biomedical Engineering, Korea University, Seoul 02841, Korea.
| | - Jeong Hoon Lee
- Department of Electrical Engineering, Kwangwoon University, 447-1 Wolgye, Nowon, Seoul 01897, Korea.
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189
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Li R, Rui G, Chen W, Li S, Schulz PE, Zhang Y. Early Detection of Alzheimer's Disease Using Non-invasive Near-Infrared Spectroscopy. Front Aging Neurosci 2018; 10:366. [PMID: 30473662 PMCID: PMC6237862 DOI: 10.3389/fnagi.2018.00366] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2018] [Accepted: 10/23/2018] [Indexed: 11/13/2022] Open
Abstract
Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, wherein patients have an increased likelihood of developing Alzheimer’s disease (AD). The classification of MCI and different AD stages is therefore fundamental for understanding and treating the disease. This study aimed to comprehensively investigate the hemodynamic response patterns among various subject groups. Functional near-infrared spectroscopy (fNIRS) was employed to measure signals from the frontal and bilateral parietal cortices of healthy controls (n = 8), patients with MCI (n = 9), mild (n = 6), and moderate/severe AD (n = 7) during a digit verbal span task (DVST). The concentration changes of oxygenated hemoglobin (HbO) in various subject groups were thoroughly explored and tested. Result revealed that abnormal patterns of hemodynamic response were observed across all subject groups. Greater and steeper reductions in HbO concentration were consistently observed across all regions of interest (ROIs) as disease severity developed from MCI to moderate/severe AD. Furthermore, all the fNIRS-derived indexes were found to be significantly and positively correlated to the clinical scores in all ROIs (R ≥ 0.4, P < 0.05). These findings demonstrate the feasibility of utilizing fNIRS for the early detection of AD, suggesting that fNIRS-based approaches hold great promise for exploring the mechanisms underlying the progression of AD.
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Affiliation(s)
- Rihui Li
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States.,Guangdong Provincial Work Injury Rehabilitation Hospital, Guangzhou, China
| | - Guoxing Rui
- Nanjing Ruihaibo Medical Rehabilitation Center, Nanjing, China
| | - Wei Chen
- Nanjing Ruihaibo Medical Rehabilitation Center, Nanjing, China
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Paul E Schulz
- Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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190
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Abstract
The past decade has seen tremendous efforts in biomarker discovery and validation for neurodegenerative diseases. The source and type of biomarkers has continued to grow for central nervous system diseases, from biofluid-based biomarkers (blood or cerebrospinal fluid (CSF)), to nucleic acids, tissue, and imaging. While DNA remains a predominant biomarker used to identify familial forms of neurodegenerative diseases, various types of RNA have more recently been linked to familial and sporadic forms of neurodegenerative diseases during the past few years. Imaging approaches continue to evolve and are making major contributions to target engagement and early diagnostic biomarkers. Incorporation of biomarkers into drug development and clinical trials for neurodegenerative diseases promises to aid in the development and demonstration of target engagement and drug efficacy for neurologic disorders. This review will focus on recent advancements in developing biomarkers for clinical utility in Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).
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Affiliation(s)
| | - Robert Bowser
- Iron Horse Diagnostics, Inc., Scottsdale, AZ, 85255, USA.
- Divisions of Neurology and Neurobiology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 W Thomas Rd, Phoenix, AZ, 85013, USA.
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191
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Palmqvist S, Insel PS, Zetterberg H, Blennow K, Brix B, Stomrud E, Mattsson N, Hansson O. Accurate risk estimation of β-amyloid positivity to identify prodromal Alzheimer's disease: Cross-validation study of practical algorithms. Alzheimers Dement 2018; 15:194-204. [PMID: 30365928 PMCID: PMC6374284 DOI: 10.1016/j.jalz.2018.08.014] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 06/14/2018] [Accepted: 08/21/2018] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The aim was to create readily available algorithms that estimate the individual risk of β-amyloid (Aβ) positivity. METHODS The algorithms were tested in BioFINDER (n = 391, subjective cognitive decline or mild cognitive impairment) and validated in Alzheimer's Disease Neuroimaging Initiative (n = 661, subjective cognitive decline or mild cognitive impairment). The examined predictors of Aβ status were demographics; cognitive tests; white matter lesions; apolipoprotein E (APOE); and plasma Aβ42/Aβ40, tau, and neurofilament light. RESULTS Aβ status was accurately estimated in BioFINDER using age, 10-word delayed recall or Mini-Mental State Examination, and APOE (area under the receiver operating characteristics curve = 0.81 [0.77-0.85] to 0.83 [0.79-0.87]). When validated, the models performed almost identical in Alzheimer's Disease Neuroimaging Initiative (area under the receiver operating characteristics curve = 0.80-0.82) and within different age, subjective cognitive decline, and mild cognitive impairment populations. Plasma Aβ42/Aβ40 improved the models slightly. DISCUSSION The algorithms are implemented on http://amyloidrisk.com where the individual probability of being Aβ positive can be calculated. This is useful in the workup of prodromal Alzheimer's disease and can reduce the number needed to screen in Alzheimer's disease trials.
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Affiliation(s)
- Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden.
| | - Philip S Insel
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, United Kingdom; UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | | | - Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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192
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Vogel JW, Mattsson N, Iturria-Medina Y, Strandberg OT, Schöll M, Dansereau C, Villeneuve S, van der Flier WM, Scheltens P, Bellec P, Evans AC, Hansson O, Ossenkoppele R. Data-driven approaches for tau-PET imaging biomarkers in Alzheimer's disease. Hum Brain Mapp 2018; 40:638-651. [PMID: 30368979 DOI: 10.1002/hbm.24401] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2018] [Revised: 08/09/2018] [Accepted: 09/04/2018] [Indexed: 12/14/2022] Open
Abstract
Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions-of-interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post-mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data-driven method to identify spatial patterns of tau-PET distribution, and to compare these patterns to previously published "pathology-driven" ROIs. Tau-PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimer's disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18 F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18 F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18 F]AV1451 uptake in the data-driven clusters, and in 35 previously published pathology-driven ROIs, was extracted from ADNI [18 F]AV1451 scans. We performed linear models comparing [18 F]AV1451 signal across all 40 ROIs to tests of global cognition and episodic memory, adjusting for age, sex, and education. Two data-driven ROIs consistently demonstrated the strongest or near-strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data-driven, one pathology-driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18 F]AV1451-PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.
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Affiliation(s)
- Jacob W Vogel
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Niklas Mattsson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | | | | | - Michael Schöll
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Christian Dansereau
- Department of Computer Science and Operations Research, Université de Montréal, Montreal, Quebec, Canada.,Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, University of Montreal, Montreal, Quebec, Canada
| | - Sylvia Villeneuve
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Wiesje M van der Flier
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Pierre Bellec
- Department of Computer Science and Operations Research, Université de Montréal, Montreal, Quebec, Canada.,Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, University of Montreal, Montreal, Quebec, Canada
| | - Alan C Evans
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands.,Clinical Memory Research Unit, Lund University, Lund, Sweden
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193
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Lei B, Yang P, Zhuo Y, Zhou F, Ni D, Chen S, Xiao X, Wang T. Neuroimaging Retrieval via Adaptive Ensemble Manifold Learning for Brain Disease Diagnosis. IEEE J Biomed Health Inform 2018; 23:1661-1673. [PMID: 30281500 DOI: 10.1109/jbhi.2018.2872581] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative and non-curable disease, with serious cognitive impairment, such as dementia. Clinically, it is critical to study the disease with multi-source data in order to capture a global picture of it. In this respect, an adaptive ensemble manifold learning (AEML) algorithm is proposed to retrieve multi-source neuroimaging data. Specifically, an objective function based on manifold learning is formulated to impose geometrical constraints by similarity learning. The complementary characteristics of various sources of brain disease data for disorder discovery are investigated by tuning weights from ensemble learning. In addition, a generalized norm is explicitly explored for adaptive sparseness degree control. The proposed AEML algorithm is evaluated by the public AD neuroimaging initiative database. Results obtained from the extensive experiments demonstrate that our algorithm outperforms the traditional methods.
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194
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Abnormal CSF amyloid-β42 and tau levels in hip fracture patients without dementia. PLoS One 2018; 13:e0204695. [PMID: 30252906 PMCID: PMC6155555 DOI: 10.1371/journal.pone.0204695] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2018] [Accepted: 09/12/2018] [Indexed: 11/29/2022] Open
Abstract
Background There is strong association of Alzheimer’s disease (AD) pathology with gait disorder and falls in older adults without dementia. The goal of the study was to examine the prevalence and severity of AD pathology in older adults without dementia who fall and sustain hip fracture. Methods Cerebrospinal fluid (CSF) was obtained from 168 hip fracture patients. CSF Aβ42/40 ratio, p-tau, and t-tau measures were dichotomized into normal vs. abnormal, and categorized according to the A/T/N classification. Results Among the hip fracture patients, 88.6% of the cognitively normal (Clinical Dementia Rating-CDR 0; n = 70) and 98.8% with mild cognitive impairment (CDR 0.5; n = 81) fell in the abnormal biomarker categories by the A/T/N classification. Conclusions A large proportion of older hip fracture patients have CSF evidence of AD pathology. Preoperative determination of AD biomarkers may play a crucial role in identifying persons without dementia who have underlying AD pathology in perioperative settings.
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195
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Leuzy A, Heurling K, Ashton NJ, Schöll M, Zimmer ER. In vivo Detection of Alzheimer's Disease. THE YALE JOURNAL OF BIOLOGY AND MEDICINE 2018; 91:291-300. [PMID: 30258316 PMCID: PMC6153625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Recent revisions to the diagnostic criteria for Alzheimer's disease (AD) incorporated conceptual advances in the field. Specifically, AD is now recognized to encompass a continuum, spanning from preclinical (accruing brain pathology in the absence of symptoms) through symptomatic predementia (prodromal AD, mild cognitive impairment) and dementia phases. The role of biological markers (biomarkers) of both the underlying molecular pathologies and related neurodegenerative changes has also been acknowledged. In this abridged review, we provide an overview of fluid (cerebrospinal fluid and blood) and molecular imaging-based biomarkers used within the field and discuss the potential role of computer driven artificial intelligence approaches for both the early and accurate identification of AD and as a tool for population enrichment in clinical trials testing candidate disease modifying therapies.
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Affiliation(s)
- Antoine Leuzy
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Kerstin Heurling
- Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Nicholas J. Ashton
- Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden,Clinical Memory Research Unit, Lund University, Sweden
| | - Eduardo R. Zimmer
- Department of Pharmacology, Federal University of Rio Grande do Sul, Porto Alegre, Brazil,Graduate Program in Biological Sciences: Biochemistry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil,Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil,To whom all correspondence should be addressed: Eduardo R. Zimmer, PhD, Department of Pharmacology, Federal University of Rio Grande do Sul, 500 Sarmento Leite Street, 90050-170, Porto Alegre, RS, Brazil; Tel: +55 51 33085558,
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196
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Mattsson N, Ossenkoppele R, Smith R, Strandberg O, Ohlsson T, Jögi J, Palmqvist S, Stomrud E, Hansson O. Greater tau load and reduced cortical thickness in APOE ε4-negative Alzheimer's disease: a cohort study. Alzheimers Res Ther 2018; 10:77. [PMID: 30086796 PMCID: PMC6081879 DOI: 10.1186/s13195-018-0403-x] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Accepted: 07/09/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND Alzheimer's disease is characterized by aggregated β-amyloid and tau proteins, but the clinical presentations and patterns of brain atrophy vary substantially. A part of this heterogeneity may be linked to the risk allele APOE ε4. The spread of tau pathology is related to atrophy and cognitive decline, but little data exist on the effects of APOE ε4 on tau. The objective of this preliminary study was therefore to test if tau load and brain structure differ by APOE ε4 in Alzheimer's disease. METHODS Sixty-five β-amyloid-positive patients at the prodromal and dementia stages of Alzheimer's disease were enrolled, including APOE ε4-positive (n = 46) and APOE ε4-negative (n = 19) patients. 18F-AV-1451 positron emission tomography was used to measure tau and brain magnetic resonance imaging (MRI) was used to measure cortical thickness. RESULTS Compared with their APOE ε4-positive counterparts, APOE ε4-negative patients had greater tau load and reduced cortical thickness, with the most pronounced effects for both in the parietal cortex. Relative to the overall cortical tau load, APOE ε4-positive patients had greater tau load in the entorhinal cortex. APOE ε4-positive patients also had slightly greater cortical β-amyloid load. There was an interaction between APOE ε4 and 18F-AV-1451 on cortical thickness, with greater effects of 18F-AV-1451 on cortical thickness in APOE ε4-negative patients. APOE ε4 and 18F-AV-1451 were independent predictors of cognition, but showed distinct associations with different cognitive tests. CONCLUSIONS APOE genotype may be associated with differences in pathways in Alzheimer's disease, potentially through differential development and spread of tau, as well as through effects on cognitive outcomes involving non-tau-related mechanisms.
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Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
- VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
- VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Tomas Ohlsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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197
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Mielke MM, Hagen CE, Xu J, Chai X, Vemuri P, Lowe VJ, Airey DC, Knopman DS, Roberts RO, Machulda MM, Jack CR, Petersen RC, Dage JL. Plasma phospho-tau181 increases with Alzheimer's disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Alzheimers Dement 2018; 14:989-997. [PMID: 29626426 PMCID: PMC6097897 DOI: 10.1016/j.jalz.2018.02.013] [Citation(s) in RCA: 421] [Impact Index Per Article: 60.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Revised: 01/25/2018] [Accepted: 02/05/2018] [Indexed: 01/17/2023]
Abstract
INTRODUCTION We examined and compared plasma phospho-tau181 (pTau181) and total tau: (1) across the Alzheimer's disease (AD) clinical spectrum; (2) in relation to brain amyloid β (Aβ) positron emission tomography (PET), tau PET, and cortical thickness; and (3) as a screening tool for elevated brain Aβ. METHODS Participants included 172 cognitively unimpaired, 57 mild cognitively impaired, and 40 AD dementia patients with concurrent Aβ PET (Pittsburgh compound B), tau PET (AV1451), magnetic resonance imaging, plasma total tau, and pTau181. RESULTS Plasma total tau and pTau181 levels were higher in AD dementia patients than those in cognitively unimpaired. Plasma pTau181 was more strongly associated with both Aβ and tau PET. Plasma pTau181 was a more sensitive and specific predictor of elevated brain Aβ than total tau and was as good as, or better than, the combination of age and apolipoprotein E (APOE). DISCUSSION Plasma pTau181 may have utility as a biomarker of AD pathophysiology and as a noninvasive screener for elevated brain Aβ.
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Affiliation(s)
- Michelle M Mielke
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA.
| | - Clinton E Hagen
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Jing Xu
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | - Xiyun Chai
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - David C Airey
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Rosebud O Roberts
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Ronald C Petersen
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Jeffrey L Dage
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
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198
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Abstract
Alzheimer’s disease is the most common cause of dementia worldwide, with the prevalence continuing to grow in part because of the aging world population. This neurodegenerative disease process is characterized classically by two hallmark pathologies: β-amyloid plaque deposition and neurofibrillary tangles of hyperphosphorylated tau. Diagnosis is based upon clinical presentation fulfilling several criteria as well as fluid and imaging biomarkers. Treatment is currently targeted toward symptomatic therapy, although trials are underway that aim to reduce the production and overall burden of pathology within the brain. Here, we discuss recent advances in our understanding of the clinical evaluation and treatment of Alzheimer’s disease, with updates regarding clinical trials still in progress.
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Affiliation(s)
- Jason Weller
- Department of Neurology, Boston VA Hospital, 150 South Huntington Street, Jamaica Plain, MA, 02130, USA.,Department of Neurology, Boston University School of Medicine, 72 East Concord Street C-309, Boston, MA, USA
| | - Andrew Budson
- Department of Neurology, Boston VA Hospital, 150 South Huntington Street, Jamaica Plain, MA, 02130, USA.,Department of Neurology, Boston University School of Medicine, 72 East Concord Street C-309, Boston, MA, USA
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199
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Vergallo A, Bun RS, Toschi N, Baldacci F, Zetterberg H, Blennow K, Cavedo E, Lamari F, Habert MO, Dubois B, Floris R, Garaci F, Lista S, Hampel H. Association of cerebrospinal fluid α-synuclein with total and phospho-tau 181 protein concentrations and brain amyloid load in cognitively normal subjective memory complainers stratified by Alzheimer's disease biomarkers. Alzheimers Dement 2018; 14:1623-1631. [PMID: 30055132 DOI: 10.1016/j.jalz.2018.06.3053] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 04/30/2018] [Accepted: 06/15/2018] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Several neurodegenerative brain proteinopathies, including Alzheimer's disease (AD), are associated with cerebral deposition of insoluble aggregates of α-synuclein. Previous studies reported a trend toward increased cerebrospinal fluid (CSF) α-synuclein (α-syn) concentrations in AD compared with other neurodegenerative diseases and healthy controls. METHODS The pathophysiological role of CSF α-syn in asymptomatic subjects at risk of AD has not been explored. We performed a large-scale cross-sectional observational monocentric study of preclinical individuals at risk for AD (INSIGHT-preAD). RESULTS We found a positive association between CSF α-syn concentrations and brain β-amyloid deposition measures as mean cortical standard uptake value ratios. We demonstrate positive correlations between CSF α-syn and both CSF t-tau and p-tau181 concentrations. DISCUSSION Animal models presented evidence, indicating that α-syn may synergistically and directly induce fibrillization of both tau and β-amyloid. Our data indicate an association of CSF α-syn with AD-related pathophysiological mechanisms, during the preclinical phase of the disease.
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Affiliation(s)
- Andrea Vergallo
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France.
| | - René-Sosata Bun
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy; Department of Radiology, "Athinoula A. Martinos" Center for Biomedical Imaging, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Filippo Baldacci
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France; Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute, London, UK
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Enrica Cavedo
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France; Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Foudil Lamari
- AP-HP, UF Biochimie des Maladies Neuro-métaboliques, Service de Biochimie Métabolique, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Marie-Odile Habert
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France; Centre pour l'Acquisition et le Traitement des Images (www.cati-neuroimaging.com), France; AP-HP, Hôpital Pitié-Salpêtrière, Département de Médecine Nucléaire, Paris, France
| | - Bruno Dubois
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France
| | - Roberto Floris
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
| | - Francesco Garaci
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy; Casa di Cura "San Raffaele Cassino", Cassino, Italy
| | - Simone Lista
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France
| | - Harald Hampel
- AXA Research Fund & Sorbonne University Chair, Paris, France; Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Paris, France; Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, Paris, France; Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Paris, France
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Dumurgier J, Hanseeuw BJ, Hatling FB, Judge KA, Schultz AP, Chhatwal JP, Blacker D, Sperling RA, Johnson KA, Hyman BT, Gómez-Isla T. Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults. J Alzheimers Dis 2018; 60:1451-1459. [PMID: 29036824 DOI: 10.3233/jad-170511] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Identifying older adults at risk of cognitive decline represents a challenge as Alzheimer's disease (AD) modifying therapies move toward preclinical stages. OBJECTIVE To investigate the relationship between AD biomarkers and subsequent change in cognition in a cohort of cognitively intact older adults. METHODS 84 cognitively normal subjects (mean age 72.0 years, 59% women) were recruited through the Massachusetts Alzheimer's Disease Research Center and the Harvard Aging Brain Study and followed over 3 years. Measurements of amyloid-β 1-42 (Aβ42), total Tau (t-Tau), and Tau phosphorylated at threonine 181 (p-Tau181) in the cerebrospinal fluid (CSF) at study entry were available in all cases. Baseline brain MRI, FDG-PET, and PiB-PET data were available in the majority of participants. Relationship between baseline AD biomarkers and longitudinal change in cognition was assessed using Cox proportional hazard regression and linear mixed models. RESULTS 14% participants increased their global Clinical Dementia Rating (CDR) score from 0 to 0.5 during follow-up. A CDR score increase was associated with higher baseline CSF t-Tau and p-Tau181, higher global cortical PiB retention, and lower hippocampal volume. The combination of high CSF t-Tau and low Aβ42 or low hippocampal volume was more strongly related to cognitive outcome than each single biomarker. Higher CSF t-Tau was the only biomarker associated with subsequent decline in MMSE score. CONCLUSIONS Baseline CSF t-Tau and p-Tau181, in vivo amyloid load, and hippocampal volume were all independently associated with future decline in cognition. The discriminatory ability of these biomarkers to predict risk of cognitive decline, however, was only modest.
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Affiliation(s)
- Julien Dumurgier
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA.,INSERM U942 and Memory Clinical Center, Saint Louis - Lariboisiere - Fernand Widal Hospital, AP-HP, University Paris VII Denis Diderot, Paris, France
| | - Bernard J Hanseeuw
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Frances B Hatling
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kelly A Judge
- Department of Radiology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA.,Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Deborah Blacker
- Department of Psychiatry, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA, USA
| | - Keith A Johnson
- Department of Radiology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Teresa Gómez-Isla
- Department of Neurology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA, USA
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