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Grill JD, Raman R, Ernstrom K, Wang S, Donohue MC, Aisen PS, Karlawish J, Henley D, Romano G, Novak G, Brashear HR, Sperling RA. Immediate Reactions to Alzheimer Biomarker Disclosure in Cognitively Unimpaired Individuals in a Global Truncated Randomized Trial. Neurol Clin Pract 2024; 14:e200265. [PMID: 38585443 PMCID: PMC10996909 DOI: 10.1212/cpj.0000000000200265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 11/21/2023] [Indexed: 04/09/2024]
Abstract
Background and Objectives Preclinical Alzheimer disease (AD) trials simultaneously test candidate treatments and the implications of disclosing biomarker information to cognitively unimpaired individuals. Methods The EARLY trial was a randomized, double-blind, placebo-controlled, phase 2b/3 study conducted in 143 centers across 14 countries from November 2015 to December 2018 after being stopped prematurely because of treatment-related hepatotoxicity. Participants age 60-85 years deemed cognitively unimpaired were disclosed an elevated or not elevated brain amyloid result by a certified clinician. Among 3,686 participants, 2,066 underwent amyloid imaging, 1,394 underwent CSF biomarker assessment, and 226 underwent both. Among biomarker-tested participants with at least one change score on an outcome of interest, 680 with elevated and 2,698 with not elevated amyloid were included in this analysis. We compared the Geriatric Depression Scale (GDS), the State-Trait Anxiety Scale (STAI), and the Columbia Suicide Severity Rating Scale (CSSRS) before disclosure between amyloid groups. After disclosure, we assessed for differences in the Impact of Events Scale (IES, collected 24-72 hours after disclosure), a measure of intrusive thoughts. Additional scales included the Concerns for AD scale. Results Among 3378 included participants, the mean (SD) age was 69.0 (5.3); most were female (60%) and White race (84%). No differences were observed before disclosure between participants with elevated and not elevated amyloid for the GDS, STAI, or CSSRS. Participants with elevated amyloid demonstrated higher Concerns for AD scores compared with participants with not elevated amyloid before disclosure. Participants with elevated amyloid demonstrated higher IES scores (9.6 [10.8] vs 5.1 [8.0]) after disclosure and increased Concerns about AD. Patterns of reactions (elevated vs not elevated) were similar for biomarker modalities, although scores were lower among those undergoing CSF compared with PET testing. Although score differences were apparent comparing geographical regions, patterns of group differences were similar. Discussion Although sample bias must be considered, these results suggest that amyloid disclosure resulted in increased perceived risk and mild distress in those learning an elevated result. Although this study did not assess psychological safety, observed associations intrusive thoughts and distress could be important considerations in the future clinical practice.
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Affiliation(s)
- Joshua D Grill
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Rema Raman
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Karin Ernstrom
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Shunran Wang
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Michael C Donohue
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Paul S Aisen
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Jason Karlawish
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - David Henley
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Gary Romano
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Gerald Novak
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - H Robert Brashear
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
| | - Reisa A Sperling
- Institute for Memory Impairments and Neurological Disorders (JDG), Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California Irvine, Irvine; Alzheimer's Therapeutic Research Institute (RR, KE, SW, MCD, PSA), University of Southern California, San Diego; University of Pennsylvania (JK), Philadelphia; Janssen Research & Development LLC (DH, GR, GN), Titusville, NJ; Indiana University School of Medicine (DH, HRB), Indianapolis; University of Virginia (HRB), Charlottesville; and Brigham and Women's Hospital (RAS), Harvard Medical School, Boston, MA
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Petersen RC, Graf A, Brady C, De Santi S, Florian H, Landen J, Pontecorvo M, Randolph C, Sink KM, Carrillo MC, Weber CJ. Operationalizing selection criteria for clinical trials in Alzheimer's disease: Biomarker and clinical considerations. Alzheimers Dement (N Y) 2023; 9:e12434. [PMID: 38023620 PMCID: PMC10655199 DOI: 10.1002/trc2.12434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 10/11/2023] [Indexed: 12/01/2023]
Abstract
Alzheimer's disease (AD) staging criteria lack standardized, empirical description. Well-defined AD staging criteria are an important consideration in protocol design, influencing a more standardized inclusion/exclusion criteria and defining what constitutes meaningful differentiation among the stages. However, many trials are being designed on the basis of biomarker features and the two need to be coordinated. The Alzheimer's Association Research Roundtable (AARR) Spring 2021 meeting discussed the implementation of preclinical AD staging criteria, and provided recommendations for how they may best be incorporated into clinical trials research. Discussion also included what currently available tools for global clinical trials may best define populations in preclinical AD trials, and if are we able to differentiate preclinical from clinical stages of the disease. Well-defined AD staging criteria are key to improving early detection, diagnostics, clinical trial enrollment, and identifying statistically significant clinical changes, and researchers discussed how emerging blood biomarkers may help with more efficient screening in preclinical stages.
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Affiliation(s)
| | - Ana Graf
- Novartis Pharma AGBaselSwitzerland
| | - Chris Brady
- WCG Clinical Endpoint Solutions, PrincetonNew JerseyUSA
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Constantinides VC, Paraskevas GP, Boufidou F, Bourbouli M, Pyrgelis ES, Stefanis L, Kapaki E. CSF Aβ42 and Aβ42/Aβ40 Ratio in Alzheimer's Disease and Frontotemporal Dementias. Diagnostics (Basel) 2023; 13:diagnostics13040783. [PMID: 36832271 PMCID: PMC9955886 DOI: 10.3390/diagnostics13040783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Alzheimer's disease dementia (ADD) may manifest with atypical phenotypes, resembling behavioral variant frontotemporal dementia (bvFTD) and corticobasal syndrome (CBS), phenotypes which typically have an underlying frontotemporal lobar degeneration with tau proteinopathy (FTLD-tau), such as Pick's disease, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), or FTLD with TDP-43 proteinopathy (FTLD-TDP). CSF biomarkers total and phosphorylated tau (τT and τP-181), and amyloid beta with 42 and 40 amino acids (Aβ42 and Aβ40) are biomarkers of AD pathology. The primary aim of this study was to compare the diagnostic accuracy of Aβ42 to Aβ42/Aβ40 ratio in: (a) differentiating ADD vs. frontotemporal dementias; (b) patients with AD pathology vs. non-AD pathologies; (c) compare biomarker ratios and composite markers to single CSF biomarkers in the differentiation of AD from FTD; Methods: In total, 263 subjects were included (ADD: n = 98; bvFTD: n = 49; PSP: n = 50; CBD: n = 45; controls: n = 21). CSF biomarkers were measured by commercially available ELISAs (EUROIMMUN). Multiple biomarker ratios (Aβ42/Aβ40; τT/τP-181; τT/Aβ42; τP-181/Aβ42) and composite markers (t-tau: τT/(Aβ42/Aβ40); p-tau: τP-181/(Aβ42/Aβ40) were calculated. ROC curve analysis was performed to compare AUCs of Aβ42 and Aβ42/Aβ40 ratio and relevant composite markers between ADD and FTD, as defined clinically. BIOMARKAPD/ABSI criteria (abnormal τT, τP-181 Aβ42, and Aβ42/Aβ40 ratio) were used to re-classify all patients into AD pathology vs. non-AD pathologies, and ROC curve analysis was repeated to compare Aβ42 and Aβ42/Aβ40; Results: Aβ42 did not differ from Aβ42/Aβ40 ratio in the differentiation of ADD from FTD (AUCs 0.752 and 0.788 respectively; p = 0.212). The τT/Aβ42 ratio provided maximal discrimination between ADD and FTD (AUC:0.893; sensitivity 88.8%, specificity 80%). BIOMARKAPD/ABSI criteria classified 60 patients as having AD pathology and 211 as non-AD. A total of 22 had discrepant results and were excluded. Aβ42/Aβ40 ratio was superior to Aβ42 in the differentiation of AD pathology from non-AD pathology (AUCs: 0.939 and 0.831, respectively; p < 0.001). In general, biomarker ratios and composite markers were superior to single CSF biomarkers in both analyses. CONCLUSIONS Aβ42/Aβ40 ratio is superior to Aβ42 in identifying AD pathology, irrespective of the clinical phenotype. CSF biomarker ratios and composite markers provide higher diagnostic accuracy compared to single CSF biomarkers.
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Affiliation(s)
- Vasilios C. Constantinides
- First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
- Neurochemistry and Biological Markers Unit, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
- Correspondence: ; Tel.: +30-21-0728-9285
| | - George P. Paraskevas
- Neurochemistry and Biological Markers Unit, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
- Second Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” University General Hospital, Rimini 1, 12462 Athens, Greece
| | - Fotini Boufidou
- Neurochemistry and Biological Markers Unit, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
| | - Mara Bourbouli
- Neurochemistry and Biological Markers Unit, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
| | - Efstratios-Stylianos Pyrgelis
- First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
| | - Leonidas Stefanis
- First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
| | - Elisabeth Kapaki
- First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
- Neurochemistry and Biological Markers Unit, First Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, Eginition Hospital, Vass. Sophias Ave. 74, 11528 Athens, Greece
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Abildgaard A, Parkner T, Knudsen CS, Gottrup H, Klit H. Diagnostic Cut-offs for CSF β-amyloid and tau proteins in a Danish dementia clinic. Clin Chim Acta 2023; 539:244-249. [PMID: 36572135 DOI: 10.1016/j.cca.2022.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Analysis of beta-amyloid 1-42 (Aβ42), total tau (t-tau) and phosphorylated-tau 181 (p-tau) in the cerebrospinal fluid (CSF) is often performed as a part of the diagnostic work-up in case of suspected Alzheimer's dementia (AD). Unfortunately, studies on optimal CSF biomarker cut-offs in a real-world clinical setting are scarce. METHODS We retrospectively evaluated the biomarker levels of 264 consecutive patients referred to our dementia clinic. The biomarkers were analysed with the Elecsys(R) assays. Diagnoses were based on all available clinical information, including FDG-PET scans. RESULTS In total, we identified 233 patients diagnosed with dementia. The median MMSE score was 22 (IQR 18-25). AD pathophysiology was suspected in 156 patients, and the corresponding cut-offs based on the Youden index were: Aβ42: 903 ng/L (ROC-AUC 0.78); t-tau: 272 ng/L (ROC-AUC 0.78); p-tau: 24 ng/L (ROC-AUC 0.85); t-tau/Aβ42 ratio: 0.34 (ROC-AUC 0.91); p-tau/Aβ42 ratio: 0.029 (ROC-AUC 0.92). CONCLUSIONS We found the tau/Aβ42 ratios to possess the best diagnostic performance, but our estimated cut-off values for the ratios were somewhat higher than previously reported. Consequently, if the CSF analyses are used to support a diagnosis of AD in a heterogeneous high-prevalence cohort, adjustment of the cut-offs may be warranted.
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Affiliation(s)
- Anders Abildgaard
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark.
| | - Tina Parkner
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Cindy Soendersoe Knudsen
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Hanne Gottrup
- Department of Neurology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Henriette Klit
- Department of Neurology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
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Collij LE, Salvadó G, de Wilde A, Altomare D, Shekari M, Gispert JD, Bullich S, Stephens A, Barkhof F, Scheltens P, Bouwman F, van der Flier WM. Quantification of [
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F]florbetaben amyloid‐PET imaging in a mixed memory clinic population: The ABIDE project. Alzheimers Dement 2022. [DOI: 10.1002/alz.12886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/25/2022] [Accepted: 10/27/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Lyduine E. Collij
- Department of Radiology and Nuclear Medicine Amsterdam University Medical Center Amsterdam Neuroscience Amsterdam The Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- Clinical Memory Research Unit Department of Clinical Sciences Lund University Malmö Sweden
| | - Arno de Wilde
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE) University of Geneva Geneva Switzerland
- Memory Center Geneva University Hospitals Geneva Switzerland
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain
- Pompeu Fabra University Barcelona Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain
- Centro de Investigación Biomédica en Red de Bioingeniería Biomateriales y Nanomedicina (CIBER‐BBN) Madrid Spain
| | | | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine Amsterdam University Medical Center Amsterdam Neuroscience Amsterdam The Netherlands
- Centre for Medical Image Computing and Queen Square Institute of Neurology UCL London UK
| | - Philip Scheltens
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Femke Bouwman
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Wiesje M. van der Flier
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
- Department of Epidemiology & Data Science Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
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Nojima H, Ito S, Kushida A, Abe A, Motsuchi W, Verbel D, Vandijck M, Jannes G, Vandenbroucke I, Aoyagi K. Clinical utility of cerebrospinal fluid biomarkers measured by LUMIPULSE ® system. Ann Clin Transl Neurol 2022; 9:1898-1909. [PMID: 36321325 PMCID: PMC9735374 DOI: 10.1002/acn3.51681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/03/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVES Cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) are well-established in research settings, but their use in routine clinical practice remains a largely unexploited potential. Here, we examined the relationship between CSF biomarkers, measured by a fully automated immunoassay platform, and brain β-amyloid (Aβ) deposition status confirmed by amyloid positron emission tomography (PET). METHODS One hundred ninety-nine CSF samples from clinically diagnosed AD patients enrolled in a clinical study and who underwent amyloid PET were used for the measurement of CSF biomarkers Aβ 1-40 (Aβ40), Aβ 1-42 (Aβ42), total tau (t-Tau), and phosphorylated tau-181 (p-Tau181) using the LUMIPULSE system. These biomarkers and their combinations were compared to amyloid PET classification (negative or positive) using visual read assessments. Several combinations were also analyzed with a multivariable logistic regression model. RESULTS Aβ42, t-Tau, and p-Tau181, and the ratios of Aβ42 with other biomarkers had a good diagnostic agreement with amyloid PET imaging. The multivariable logistic regression analysis showed that amyloid PET status was associated with Aβ40 and Aβ42, but other factors, such as MMSE, sex, t-Tau, and p-Tau181, did not significantly add information to the model. CONCLUSIONS CSF biomarkers measured with the LUMIPULSE system showed good agreement with amyloid PET imaging. The ratio of Aβ42 with the other analyzed biomarkers showed a higher correlation with amyloid PET than Aβ42 alone, suggesting that the combinations of biomarkers could be useful in the diagnostic assessment in clinical research and potentially in routine clinical practice.
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Affiliation(s)
- Hisashi Nojima
- FUJIREBIO Inc.2‐1‐1, Nishishinjuku, Shinjuku‐kuTokyo163‐0410Japan
| | - Satoshi Ito
- Eisai Co., Ltd. 4‐6‐10 KoishikawaBunkyo‐kuTokyo112‐8088Japan,Eisai Inc.200 Metro BoulevardNutleyNew Jersey07110USA
| | - Akira Kushida
- FUJIREBIO Inc.2‐1‐1, Nishishinjuku, Shinjuku‐kuTokyo163‐0410Japan
| | - Aki Abe
- FUJIREBIO Inc.2‐1‐1, Nishishinjuku, Shinjuku‐kuTokyo163‐0410Japan
| | - Wataru Motsuchi
- FUJIREBIO Inc.2‐1‐1, Nishishinjuku, Shinjuku‐kuTokyo163‐0410Japan
| | - David Verbel
- Eisai Inc.200 Metro BoulevardNutleyNew Jersey07110USA
| | - Manu Vandijck
- Fujirebio‐Europe N.V.Technologiepark 69052GhentBelgium
| | - Geert Jannes
- Fujirebio‐Europe N.V.Technologiepark 69052GhentBelgium
| | | | - Katsumi Aoyagi
- FUJIREBIO Inc.2‐1‐1, Nishishinjuku, Shinjuku‐kuTokyo163‐0410Japan
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Abstract
The number of patients with Alzheimer’s disease (AD) and non-Alzheimer’s disease (non-AD) has drastically increased over recent decades. The amyloid cascade hypothesis attributes a vital role to amyloid-β protein (Aβ) in the pathogenesis of AD. As the main pathological hallmark of AD, amyloid plaques consist of merely the 42 and 40 amino acid variants of Aβ (Aβ 42 and Aβ 40). The cerebrospinal fluid (CSF) biomarker Aβ 42/40 has been extensively investigated and eventually integrated into important diagnostic tools to support the clinical diagnosis of AD. With the development of highly sensitive assays and technologies, blood-based Aβ 42/40, which was obtained using a minimally invasive and cost-effective method, has been proven to be abnormal in synchrony with CSF biomarker values. This paper presents the recent progress of the CSF Aβ 42/40 ratio and plasma Aβ 42/40 for AD as well as their potential clinical application as diagnostic markers or screening tools for dementia.
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Affiliation(s)
- Chang Xu
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Li Zhao
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Chunbo Dong
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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9
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Nicsanu R, Cervellati C, Benussi L, Squitti R, Zanardini R, Rosta V, Trentini A, Ferrari C, Saraceno C, Longobardi A, Bellini S, Binetti G, Zanetti O, Zuliani G, Ghidoni R. Increased Serum Beta-Secretase 1 Activity is an Early Marker of Alzheimer's Disease. J Alzheimers Dis 2022; 87:433-441. [PMID: 35275540 PMCID: PMC9198762 DOI: 10.3233/jad-215542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Beta-site APP cleaving enzyme 1 (BACE1) is the rate-limiting enzyme in amyloid-β (Aβ) plaques formation. BACE1 activity is increased in brains of patients with AD and mild cognitive impairment (MCI) and plasma levels of BACE1 appears to reflect those in the brains. OBJECTIVE In this work, we investigated the role of serum BACE1 activity as biomarker for AD, estimating the diagnostic accuracy of the assay and assessing the correlation of BACE1 activity with levels of Aβ 1 - 40, Aβ 1 - 42, and Aβ 40/42 ratio in serum, known biomarkers of brain amyloidosis. METHODS Serum BACE1 activity and levels of Aβ 1 - 40, Aβ 1 - 42, were assessed in 31 AD, 28 MCI, diagnosed as AD at follow-up (MCI-AD), and 30 controls. The BACE1 analysis was performed with a luciferase assay, where interpolation of relative fluorescence units with a standard curve of concentration reveals BACE1 activity. Serum levels of Aβ 1 - 40, Aβ 1 - 42 were measured with the ultrasensitive Single Molecule Array technology. RESULTS BACE1 was increased (higher than 60%) in AD and MCI-AD: a cut-off of 11.04 kU/L discriminated patients with high sensitivity (98.31%) and specificity (100%). Diagnostic accuracy was higher for BACE1 than Aβ 40/42 ratio. High BACE1 levels were associated with worse cognitive performance and earlier disease onset, which was anticipated by 8 years in patients with BACE1 values above the median value (> 16.67 kU/L). CONCLUSION Our results provide new evidence supporting serum/plasma BACE1 activity as an early biomarker of AD.
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Affiliation(s)
- Roland Nicsanu
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Carlo Cervellati
- Department of Translational Medicine and for Romagna, University of Ferrara, Ferrara, Italy
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Rosanna Squitti
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Roberta Zanardini
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Valentina Rosta
- Department of Translational Medicine and for Romagna, University of Ferrara, Ferrara, Italy
| | - Alessandro Trentini
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Italy
| | - Clarissa Ferrari
- Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Claudia Saraceno
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonio Longobardi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sonia Bellini
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giuliano Binetti
- MAC-Memory Clinic and Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Orazio Zanetti
- Alzheimer's Research Unit and MAC Memory Clinic, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni Zuliani
- Department of Translational Medicine and for Romagna, University of Ferrara, Ferrara, Italy
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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10
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Graff-Radford J, Jones DT, Wiste HJ, Cogswell PM, Weigand SD, Lowe V, Elder BD, Vemuri P, Van Harten A, Mielke MM, Knopman DS, Graff-Radford NR, Petersen RC, Jack CR, Gunter JL. Cerebrospinal fluid dynamics and discordant amyloid biomarkers. Neurobiol Aging 2022; 110:27-36. [PMID: 34844077 PMCID: PMC8758540 DOI: 10.1016/j.neurobiolaging.2021.10.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 02/03/2023]
Abstract
Do MRI-based metrics of a CSF-dynamics disorder, disproportionately enlarged subarachnoid-space hydrocephalus (DESH), correlate with discordant amyloid biomarkers (low CSF β-amyloid 1-42, normal Aβ-PET scan)? Individuals ≥50 years from the Mayo Clinic Study of Aging, with MRI, 11C-Pittsburgh compound B (Aβ) PET scans, and CSF phosphorylated-tau protein and Aβ42, were categorized into 4 groups: normal and/or abnormal by CSF β-amyloid 1-42 and Aβ amyloid PET. Within groups, we noted MRI patterns of CSF-dynamics disorders and Aβ-PET accumulation-change rate. One-hundred participants (21%) in the abnormal-CSF and/or normal-PET group had highest DESH-pattern scores and lowest CSF-phosphorylated-tau levels. Among normal amyloid-PET individuals, a 1-unit DESH-pattern score increase correlated with 30%-greater odds of abnormal amyloid CSF after age, and sex adjustment. Mean rate over time of amyloid-PET accumulation in abnormal-CSF and/or normal-PET individuals approximated individuals with normal amyloid values. Adjusting for phosphorylated-tau, abnormal CSF-amyloid and/or normal amyloid-PET individuals had higher mean amyloid-PET accumulation rates than normal individuals. CSF dynamics disorders confound β-amyloid and phosphorylated-tau CSF-biomarker interpretation.
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Affiliation(s)
- Jonathan Graff-Radford
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - David T. Jones
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Heather J. Wiste
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Petrice M. Cogswell
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Stephen D. Weigand
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Val Lowe
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Benjamin D. Elder
- Department of Neurologic Surgery, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA,Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Argonde Van Harten
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Michelle M. Mielke
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - David S. Knopman
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Neill R. Graff-Radford
- Department of Enterprise Application Services, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905 USA
| | - Jeffrey L. Gunter
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, Florida 32224 USA
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11
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Cardoso S, Silva D, Alves L, Guerreiro M, Mendonça AD. The Outcome of Patients with Amyloid-Negative Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2022; 86:629-640. [DOI: 10.3233/jad-215465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Patients with amnestic mild cognitive impairment (aMCI) are usually at an initial stage of Alzheimer’s disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology characteristic of AD. The significance of amyloid-negative aMCI is not presently clear. Objective: To know the etiology and prognosis of amyloid-negative aMCI. Methods: Patients who fulfilled criteria for aMCI and were amyloid negative were selected from a large cohort of non-demented patients with cognitive complaints and were followed with clinical and neuropsychological assessments. Results: Few amyloid-negative aMCI had evidence of neurodegeneration at the baseline, as reflected in cerebrospinal fluid elevated tau protein levels. About half of the patients remained essentially stable for long periods of time. Others manifested a psychiatric disorder that was not apparent at baseline, namely major depression or bipolar disorder. Remarkably, about a quarter of patients developed neurodegenerative disorders other than AD, mostly frontotemporal dementia or Lewy body disease. Conclusion: Amyloid-negative aMCI is a heterogeneous condition. Many patients remain clinically stable, but others may later manifest psychiatric conditions or evolve to neurodegenerative disorders. Prudence is needed when communicating to the patient and family the results of biomarkers, and clinical follow-up should be advised.
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Affiliation(s)
- Sandra Cardoso
- Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Dina Silva
- Cognitive Neuroscience Research Group, Department of Psychology and Educational Sciences and Centre for Biomedical Research (CBMR), Universidade do Algarve, Faro, Portugal
| | - Luísa Alves
- Chronic Diseases Research Centre, NOVA Medical School, NOVA University of Lisbon, Portugal
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12
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Teipel SJ, Dyrba M, Vergallo A, Lista S, Habert MO, Potier MC, Lamari F, Dubois B, Hampel H, Grothe MJ. Partial Volume Correction Increases the Sensitivity of 18F-Florbetapir-Positron Emission Tomography for the Detection of Early Stage Amyloidosis. Front Aging Neurosci 2022; 13:748198. [PMID: 35002673 PMCID: PMC8729321 DOI: 10.3389/fnagi.2021.748198] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 11/05/2021] [Indexed: 11/25/2022] Open
Abstract
Purpose: To test whether correcting for unspecific signal from the cerebral white matter increases the sensitivity of amyloid-PET for early stages of cerebral amyloidosis. Methods: We analyzed 18F-Florbetapir-PET and cerebrospinal fluid (CSF) Aβ42 data from 600 older individuals enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including people with normal cognition, mild cognitive impairment (MCI), and Alzheimer’s disease (AD) dementia. We determined whether three compartmental partial volume correction (PVC-3), explicitly modeling signal spill-in from white matter, significantly improved the association of CSF Aβ42 levels with global 18F-Florbetapir-PET values compared with standard processing without PVC (non-PVC) and a widely used two-compartmental PVC method (PVC-2). In additional voxel-wise analyses, we determined the sensitivity of PVC-3 compared with non-PVC and PVC-2 for detecting early regional amyloid build-up as modeled by decreasing CSF Aβ42 levels. For replication, we included an independent sample of 43 older individuals with subjective memory complaints from the INveStIGation of AlzHeimer’s PredicTors cohort (INSIGHT-preAD study). Results: In the ADNI sample, PVC-3 18F-Florbetapir-PET values normalized to whole cerebellum signal showed significantly stronger associations with CSF Aβ42 levels than non-PVC or PVC-2, particularly in the lower range of amyloid levels. These effects were replicated in the INSIGHT-preAD sample. PVC-3 18F-Florbetapir-PET data detected regional amyloid build-up already at higher (less abnormal) CSF Aβ42 levels than non-PVC or PVC-2 data. Conclusion: A PVC approach that explicitly models unspecific white matter binding improves the sensitivity of amyloid-PET for identifying the earliest stages of cerebral amyloid pathology which has implications for future primary prevention trials.
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Affiliation(s)
- Stefan J Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Andrea Vergallo
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'Hôpital, Paris, France
| | - Simone Lista
- 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.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'Hôpital, Paris, France
| | - Marie Odile Habert
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, LIB, Sorbonne University, Paris, France.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.,Centre d'Acquisition et Traitement des Images (CATI platform), Paris, France
| | - Marie-Claude Potier
- ICM Institut du Cerveau et de la Moelle Épinière, CNRS UMR 7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Bd de l'Hôpital, Paris, France
| | - Foudil Lamari
- UF Biochimie des Maladies Neurométaboliques, Service de Biochimie Métabolique, Hôpital Pitié-Salpêtrière, Paris, France
| | - Bruno Dubois
- Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'Hôpital, Paris, France
| | - Harald Hampel
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'Hôpital, Paris, France
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
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13
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Agostinho D, Caramelo F, Moreira AP, Santana I, Abrunhosa A, Castelo-Branco M. Combined Structural MR and Diffusion Tensor Imaging Classify the Presence of Alzheimer's Disease With the Same Performance as MR Combined With Amyloid Positron Emission Tomography: A Data Integration Approach. Front Neurosci 2022; 15:638175. [PMID: 35069090 PMCID: PMC8766722 DOI: 10.3389/fnins.2021.638175] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
Abstract
Background: In recent years, classification frameworks using imaging data have shown that multimodal classification methods perform favorably over the use of a single imaging modality for the diagnosis of Alzheimer's Disease. The currently used clinical approach often emphasizes the use of qualitative MRI and/or PET data for clinical diagnosis. Based on the hypothesis that classification of isolated imaging modalities is not predictive of their respective value in combined approaches, we investigate whether the combination of T1 Weighted MRI and diffusion tensor imaging (DTI) can yield an equivalent performance as the combination of quantitative structural MRI (sMRI) with amyloid-PET. Methods: We parcellated the brain into regions of interest (ROI) following different anatomical labeling atlases. For each region of interest different metrics were extracted from the different imaging modalities (sMRI, PiB-PET, and DTI) to be used as features. Thereafter, the feature sets were reduced using an embedded-based feature selection method. The final reduced sets were then used as input in support vector machine (SVM) classifiers. Three different base classifiers were created, one for each imaging modality, and validated using internal (n = 41) and external data from the ADNI initiative (n = 330 for sMRI, n = 148 for DTI and n = 55 for PiB-PET) sources. Finally, the classifiers were ensembled using a weighted method in order to evaluate the performance of different combinations. Results: For the base classifiers the following performance levels were found: sMRI-based classifier (accuracy, 92%; specificity, 97% and sensitivity, 87%), PiB-PET (accuracy, 91%; specificity, 89%; and sensitivity, 92%) and the lowest performance was attained with DTI (accuracy, 80%; specificity, 76%; and sensitivity, 82%). From the multimodal approaches, when integrating two modalities, the following results were observed: sMRI+PiB-PET (accuracy, 98%; specificity, 98%; and sensitivity, 99%), sMRI+DTI (accuracy, 97%; specificity, 99%; and sensitivity, 94%) and PiB-PET+DTI (accuracy, 91%; specificity, 90%; and sensitivity, 93%). Finally, the combination of all imaging modalities yielded an accuracy of 98%, specificity of 97% and sensitivity of 99%. Conclusion: Although DTI in isolation shows relatively poor performance, when combined with structural MR, it showed a surprising classification performance which was comparable to MR combined with amyloid PET. These results are consistent with the notion that white matter changes are also important in Alzheimer's Disease.
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Affiliation(s)
- Daniel Agostinho
- Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Francisco Caramelo
- Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Ana Paula Moreira
- Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Isabel Santana
- Department of Neurology, Faculty of Medicine, Coimbra University Hospital (CHUC), University of Coimbra, Coimbra, Portugal
| | - Antero Abrunhosa
- Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- Faculty of Medicine, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
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14
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Jiang C, Wang Q, Xie S, Chen Z, Fu L, Peng Q, Liang Y, Guo H, Guo T. OUP accepted manuscript. Brain Commun 2022; 4:fcac084. [PMID: 35441134 PMCID: PMC9014538 DOI: 10.1093/braincomms/fcac084] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/21/2021] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Chenyang Jiang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen 518107, China
| | - Siwei Xie
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Zhicheng Chen
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, 2 Yinghuayuan Dongjie, Beijing 100029, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Ying Liang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - Hongbo Guo
- Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Correspondence to: Tengfei Guo, PhD Institute of Biomedical Engineering Shenzhen Bay Laboratory, No.5 Kelian Road Shenzhen 518132, China E-mail:
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15
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Lewczuk P, Wiltfang J, Kornhuber J, Verhasselt A. Distributions of Aβ42 and Aβ42/40 in the Cerebrospinal Fluid in View of the Probability Theory. Diagnostics (Basel) 2021; 11:diagnostics11122372. [PMID: 34943609 PMCID: PMC8700661 DOI: 10.3390/diagnostics11122372] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 12/06/2021] [Accepted: 12/08/2021] [Indexed: 12/26/2022] Open
Abstract
Amyloid β 42/40 concentration quotient has been empirically shown to improve accuracy of the neurochemical diagnostics of Alzheimer’s Disease (AD) compared to the Aβ42 concentration alone, but this improvement in diagnostic performance has not been backed up by a theoretical argumentation so far. In this report we show that better accuracy of Aβ42/40 compared to Aβ1-42 is granted by fundamental laws of probability. In particular, it can be shown that the dispersion of a distribution of a quotient of two random variables (Aβ42/40) is smaller than the dispersion of the random variable in the numerator (Aβ42), provided that the two variables are proportional. Further, this concept predicts and explains presence of outlying observations, i.e., AD patients with falsely negatively high Aβ42/40 ratio, and non-AD subjects with extremely low, falsely positive, Aβ42/40 ratio.
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Affiliation(s)
- Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany;
- Department of Neurodegeneration Diagnostics, Medical University of Białystok and Department of Biochemical Diagnostics, University Hospital of Białystok, 15-269 Białystok, Poland
- Correspondence:
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center of Göttingen (UMG), 37075 Göttingen, Germany;
- German Center for Neurodegenerative Diseases (DZNE), 37075 Göttingen, Germany
- Neurosciences and Signaling Group, Department of Medical Sciences, Institute of Biomedicine (iBiMED), University of Aveiro, 3810-193 Aveiro, Portugal
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany;
| | - Anneleen Verhasselt
- Center for Statistics, Data Science Institute, Hasselt University, 3590 Hasselt, Belgium;
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16
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Jang H, Kim JS, Lee HJ, Kim CH, Na DL, Kim HJ, Allué JA, Sarasa L, Castillo S, Pesini P, Gallacher J, Seo SW. Performance of the plasma Aβ42/Aβ40 ratio, measured with a novel HPLC-MS/MS method, as a biomarker of amyloid PET status in a DPUK-KOREAN cohort. Alzheimers Res Ther 2021; 13:179. [PMID: 34686209 PMCID: PMC8540152 DOI: 10.1186/s13195-021-00911-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 10/02/2021] [Indexed: 12/20/2022]
Abstract
Background We assessed the feasibility of plasma Aβ42/Aβ40 determined using a novel liquid chromatography-mass spectrometry method (LC-MS) as a useful biomarker of PET status in a Korean cohort from the DPUK Study. Methods A total of 580 participants belonging to six groups, Alzheimer’s disease dementia (ADD, n = 134), amnestic mild cognitive impairment (aMCI, n = 212), old controls (OC, n = 149), young controls (YC, n = 15), subcortical vascular cognitive impairment (SVCI, n = 58), and cerebral amyloid angiopathy (CAA, n = 12), were included in this study. Plasma Aβ40 and Aβ42 were quantitated using a new antibody-free, LC-MS, which drastically reduced the sample preparation time and cost. We performed receiver operating characteristic (ROC) analysis to develop the cutoff of Aβ42/Aβ40 and investigated its performance predicting centiloid-based PET positivity (PET+). Results Plasma Aβ42/Aβ40 were lower for PET+ individuals in ADD, aMCI, OC, and SVCI (p < 0.001), but not in CAA (p = 0.133). In the group of YC, OC, aMCI, and ADD groups, plasma Aβ42/Aβ40 predicted PET+ with an area under the ROC curve (AUC) of 0.814 at a cutoff of 0.2576. When adding age, APOE4, and diagnosis, the AUC significantly improved to 0.912. Conclusion Plasma Aβ42/Aβ40, as measured by this novel LC-MS method, showed good discriminating performance based on PET positivity. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00911-7.
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Affiliation(s)
- Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Ji Sun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Hye Joo Lee
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Chi-Hun Kim
- Department of Neurology, School of Medicine, Kyungpook National University, Kyungpook National University Chilgok Hospital, Daegu, South Korea.,Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Department of Health Sciences and Technology, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | | | - Leticia Sarasa
- Araclon Biotech-Grifols, Vía Hispanidad, 21, 50009, Zaragoza, Spain
| | - Sergio Castillo
- Araclon Biotech-Grifols, Vía Hispanidad, 21, 50009, Zaragoza, Spain
| | - Pedro Pesini
- Araclon Biotech-Grifols, Vía Hispanidad, 21, 50009, Zaragoza, Spain
| | - John Gallacher
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Neuroscience Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea. .,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
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17
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Lombardi G, Pupi A, Bessi V, Polito C, Padiglioni S, Ferrari C, Lucidi G, Berti V, De Cristofaro MT, Piaceri I, Bagnoli S, Nacmias B, Sorbi S. Challenges in Alzheimer's Disease Diagnostic Work-Up: Amyloid Biomarker Incongruences. J Alzheimers Dis 2021; 77:203-217. [PMID: 32716357 DOI: 10.3233/jad-200119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Discordance among amyloid biomarkers is a challenge to overcome in order to increase diagnostic accuracy in dementia. OBJECTIVES 1) To verify that cerebrospinal fluid (CSF) Aβ42/Aβ40 ratio (AβR) better agrees with Amyloid PET (Amy-PET) results compared to CSF Aβ42; 2) to detect differences among concordant positive, concordant negative, and discordant cases, basing the concordance definition on the agreement between CSF AβR and Amy-PET results; 3) to define the suspected underlying pathology of discordant cases using in vivo biomarkers. METHOD We retrospectively enrolled 39 cognitively impaired participants in which neuropsychological tests, apolipoprotein E genotype determination, TC/MRI, FDG-PET, Amy-PET, and CSF analysis had been performed. In all cases, CSF analysis was repeated using the automated Lumipulse method. In discordant cases, FDG-PET scans were evaluated visually and using automated classifiers. RESULTS CSF AβR better agreed with Amy-PET compared to CSF Aβ42 (Cohen's K 0.431 versus 0.05). Comparisons among groups did not show any difference in clinical characteristics except for age at symptoms onset that was higher in the 6 discordant cases with abnormal CSF AβR values and negative Amy-PET (CSF AβR+/AmyPET-). FDG-PET and all CSF markers (Aβ42, AβR, p-Tau, t-Tau) were suggestive of Alzheimer's disease (AD) in 5 of these 6 cases. CONCLUSION 1) CSF AβR is the CSF amyloid marker that shows the better level of agreement with Amy-PET results; 2) The use of FDG-PET and CSF-Tau markers in CSFAβR+/Amy-PET-discordant cases can support AD diagnosis; 3) Disagreement between positive CSF AβR and negative Amy-PET in symptomatic aged AD patients could be due to the variability in plaques conformation and a negative Amy-PET scan cannot be always sufficient to rule out AD.
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Affiliation(s)
- Gemma Lombardi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione Filippo Turati, Pistoia, Italy
| | | | | | - Cristina Polito
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", Nuclear Medicine Unit, University of Florence, Florence, Italy
| | - Sonia Padiglioni
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Camilla Ferrari
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", Nuclear Medicine Unit, University of Florence, Florence, Italy
| | | | - Irene Piaceri
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione IRCCS Don Carlo Gnocchi, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.,Fondazione IRCCS Don Carlo Gnocchi, Florence, Italy
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18
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Pegueroles J, Montal V, Bejanin A, Vilaplana E, Aranha M, Santos‐Santos MA, Alcolea D, Carrió I, Camacho V, Blesa R, Lleó A, Fortea J. AMYQ: An index to standardize quantitative amyloid load across PET tracers. Alzheimers Dement 2021; 17:1499-1508. [PMID: 33797846 PMCID: PMC8519100 DOI: 10.1002/alz.12317] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/21/2021] [Accepted: 01/31/2021] [Indexed: 12/17/2022]
Abstract
INTRODUCTION Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations. METHODS We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance. RESULTS AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs. DISCUSSION AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.
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Affiliation(s)
- Jordi Pegueroles
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Victor Montal
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Mateus Aranha
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Miguel Angel Santos‐Santos
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Ignasi Carrió
- Department of Nuclear MedicineHospital de la Santa Creu i Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Valle Camacho
- Department of Nuclear MedicineHospital de la Santa Creu i Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED)MadridSpain
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19
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Milà-Alomà M, Shekari M, Salvadó G, Gispert JD, Arenaza-Urquijo EM, Operto G, Falcon C, Vilor-Tejedor N, Grau-Rivera O, Sala-Vila A, Sánchez-Benavides G, González-de-Echávarri JM, Minguillon C, Fauria K, Niñerola-Baizán A, Perissinotti A, Simon M, Kollmorgen G, Zetterberg H, Blennow K, Suárez-Calvet M, Molinuevo JL. Cognitively unimpaired individuals with a low burden of Aβ pathology have a distinct CSF biomarker profile. Alzheimers Res Ther 2021; 13:134. [PMID: 34315519 PMCID: PMC8314554 DOI: 10.1186/s13195-021-00863-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 06/20/2021] [Indexed: 12/25/2022]
Abstract
Background Understanding the changes that occur in the transitional stage between absent and overt amyloid-β (Aβ) pathology within the Alzheimer’s continuum is crucial to develop therapeutic and preventive strategies. The objective of this study is to test whether cognitively unimpaired individuals with a low burden of Aβ pathology have a distinct CSF, structural, and functional neuroimaging biomarker profile. Methods Cross-sectional study of 318 middle-aged, cognitively unimpaired individuals from the ALFA+ cohort. We measured CSF Aβ42/40, phosphorylated tau (p-tau), total tau (t-tau), neurofilament light (NfL), neurogranin, sTREM2, YKL40, GFAP, IL6, S100B, and α-synuclein. Participants also underwent cognitive assessments, APOE genotyping, structural MRI, [18F]-FDG, and [18F]-flutemetamol PET. To ensure the robustness of our results, we used three definitions of low burden of Aβ pathology: (1) positive CSF Aβ42/40 and < 30 Centiloids in Aβ PET, (2) positive CSF Aβ42/40 and negative Aβ PET visual read, and (3) 20–40 Centiloid range in Aβ PET. We tested CSF and neuroimaging biomarker differences between the low burden group and the corresponding Aβ-negative group, adjusted by age and sex. Results The prevalence and demographic characteristics of the low burden group differed between the three definitions. CSF p-tau and t-tau were increased in the low burden group compared to the Aβ-negative in all definitions. CSF neurogranin was increased in the low burden group definitions 1 and 3, while CSF NfL was only increased in the low burden group definition 1. None of the defined low burden groups showed signs of atrophy or glucose hypometabolism. Instead, we found slight increases in cortical thickness and metabolism in definition 2. Conclusions There are biologically meaningful Aβ-downstream effects in individuals with a low burden of Aβ pathology, while structural and functional changes are still subtle or absent. These findings support considering individuals with a low burden of Aβ pathology for clinical trials. Trial registration NCT02485730 Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00863-y.
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Affiliation(s)
- Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Eider M Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Natalia Vilor-Tejedor
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain.,Department of Clinical Genetics, ERASMUS MC, Rotterdam, the Netherlands
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Aleix Sala-Vila
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - José Maria González-de-Echávarri
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aida Niñerola-Baizán
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.,Servei de Medicina Nuclear, Hospital Clínic, Barcelona, Spain
| | - Andrés Perissinotti
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.,Servei de Medicina Nuclear, Hospital Clínic, Barcelona, Spain
| | - Maryline Simon
- Roche Diagnostics International Ltd., Rotkreuz, Switzerland
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, 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
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain. .,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Wellington 30, 08005, Barcelona, Spain. .,Present address: H. Lundbeck A/S, Copenhagen, Denmark.
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20
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Abstract
Alzheimer disease (AD) is biologically defined by the presence of β-amyloid-containing plaques and tau-containing neurofibrillary tangles. AD is a genetic and sporadic neurodegenerative disease that causes an amnestic cognitive impairment in its prototypical presentation and non-amnestic cognitive impairment in its less common variants. AD is a common cause of cognitive impairment acquired in midlife and late-life but its clinical impact is modified by other neurodegenerative and cerebrovascular conditions. This Primer conceives of AD biology as the brain disorder that results from a complex interplay of loss of synaptic homeostasis and dysfunction in the highly interrelated endosomal/lysosomal clearance pathways in which the precursors, aggregated species and post-translationally modified products of Aβ and tau play important roles. Therapeutic endeavours are still struggling to find targets within this framework that substantially change the clinical course in persons with AD.
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Affiliation(s)
| | - Helene Amieva
- Inserm U1219 Bordeaux Population Health Center, University of Bordeaux, Bordeaux, France
| | | | - Gäel Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Ralph A Nixon
- Departments of Psychiatry and Cell Biology, New York University Langone Medical Center, New York University, New York, NY, USA
- NYU Neuroscience Institute, New York University Langone Medical Center, New York University, New York, NY, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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21
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Lopes Alves I, Heeman F, Collij LE, Salvadó G, Tolboom N, Vilor-Tejedor N, Markiewicz P, Yaqub M, Cash D, Mormino EC, Insel PS, Boellaard R, van Berckel BNM, Lammertsma AA, Barkhof F, Gispert JD. Strategies to reduce sample sizes in Alzheimer's disease primary and secondary prevention trials using longitudinal amyloid PET imaging. Alzheimers Res Ther 2021; 13:82. [PMID: 33875021 PMCID: PMC8056524 DOI: 10.1186/s13195-021-00819-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/26/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. METHODS Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. RESULTS Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). CONCLUSION Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.
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Affiliation(s)
- Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Natàlia Vilor-Tejedor
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Pawel Markiewicz
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - David Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Philip S Insel
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.
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22
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Silva D, Cardoso S, Guerreiro M, Maroco J, Mendes T, Alves L, Nogueira J, Baldeiras I, Santana I, de Mendonça A. Neuropsychological Contribution to Predict Conversion to Dementia in Patients with Mild Cognitive Impairment Due to Alzheimer's Disease. J Alzheimers Dis 2021; 74:785-796. [PMID: 32083585 DOI: 10.3233/jad-191133] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Diagnosis of Alzheimer's disease (AD) confirmed by biomarkers allows the patient to make important life decisions. However, doubt about the fleetness of symptoms progression and future cognitive decline remains. Neuropsychological measures were extensively studied in prediction of time to conversion to dementia for mild cognitive impairment (MCI) patients in the absence of biomarker information. Similar neuropsychological measures might also be useful to predict the progression to dementia in patients with MCI due to AD. OBJECTIVE To study the contribution of neuropsychological measures to predict time to conversion to dementia in patients with MCI due to AD. METHODS Patients with MCI due to AD were enrolled from a clinical cohort and the effect of neuropsychological performance on time to conversion to dementia was analyzed. RESULTS At baseline, converters scored lower than non-converters at measures of verbal initiative, non-verbal reasoning, and episodic memory. The test of non-verbal reasoning was the only statistically significant predictor in a multivariate Cox regression model. A decrease of one standard deviation was associated with 29% of increase in the risk of conversion to dementia. Approximately 50% of patients with more than one standard deviation below the mean in the z score of that test had converted to dementia after 3 years of follow-up. CONCLUSION In MCI due to AD, lower performance in a test of non-verbal reasoning was associated with time to conversion to dementia. This test, that reveals little decline in the earlier phases of AD, appears to convey important information concerning conversion to dementia.
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Affiliation(s)
- Dina Silva
- Cognitive Neuroscience Research Group, Department of Psychology and Educational Sciences and Centre for Biomedical Research (CBMR), Universidade do Algarve, Faro, Portugal.,Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Sandra Cardoso
- Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | | | - João Maroco
- Instituto Superior de Psicologia Aplicada, Lisbon, Portugal
| | - Tiago Mendes
- Faculty of Medicine, University of Lisbon, Lisbon, Portugal.,Psychiatry and Mental Health Department, Santa Maria Hospital, Lisbon, Portugal
| | - Luísa Alves
- Chronic Diseases Research Centre, NOVA Medical School, NOVA University of Lisbon, Portugal
| | - Joana Nogueira
- Department of Neurology, Dementia Clinic, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Inês Baldeiras
- Department of Neurology, Laboratory of Neurochemistry, Centro Hospitalar e Universitário de Coimbra.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Isabel Santana
- Department of Neurology, Dementia Clinic, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Department of Neurology, Laboratory of Neurochemistry, Centro Hospitalar e Universitário de Coimbra.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
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Stiffel M, Bergeron D, Mourabit Amari K, Poulin É, Roberge X, Meilleur-Durand S, Sellami L, Molin P, Nadeau Y, Fortin MP, Caron S, Poulin S, Verret L, Bouchard RW, Teunissen C, Laforce RJ. Use of Alzheimer's Disease Cerebrospinal Fluid Biomarkers in A Tertiary Care Memory Clinic. Can J Neurol Sci 2021;:1-7. [PMID: 33845924 DOI: 10.1017/cjn.2021.67] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers are promising tools to help identify the underlying pathology of neurocognitive disorders. In this manuscript, we report our experience with AD CSF biomarkers in 262 consecutive patients in a tertiary care memory clinic. METHODS We retrospectively reviewed 262 consecutive patients who underwent lumbar puncture (LP) and CSF measurement of AD biomarkers (Aβ1-42, total tau or t-tau, and p-tau181). We studied the safety of the procedure and its impact on patient's diagnosis and management. RESULTS The LP allowed to identify underlying AD pathology in 72 of the 121 patients (59%) with early onset amnestic mild cognitive impairment (aMCI) with a high probability of progression to AD; to distinguish the behavioral/dysexecutive variant of AD from the behavioral variant of frontotemporal dementia (bvFTD) in 25 of the 45 patients (55%) with an atypical neurobehavioral profile; to identify AD as the underlying pathology in 15 of the 27 patients (55%) with atypical or unclassifiable primary progressive aphasia (PPA); and to distinguish AD from other disorders in 9 of the 29 patients (31%) with psychiatric differential diagnoses and 19 of the 40 patients (47%) with lesional differential diagnoses (normal pressure hydrocephalus, encephalitis, prion disease, etc.). No major complications occurred following the LP. INTERPRETATION Our results suggest that CSF analysis is a safe and effective diagnostic tool in select patients with neurocognitive disorders. We advocate for a wider use of this biomarker in tertiary care memory clinics in Canada.
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Collij LE, Salvadó G, Shekari M, Lopes Alves I, Reimand J, Wink AM, Zwan M, Niñerola-Baizán A, Perissinotti A, Scheltens P, Ikonomovic MD, Smith APL, Farrar G, Molinuevo JL, Barkhof F, Buckley CJ, van Berckel BNM, Gispert JD. Visual assessment of [ 18F]flutemetamol PET images can detect early amyloid pathology and grade its extent. Eur J Nucl Med Mol Imaging 2021; 48:2169-2182. [PMID: 33615397 PMCID: PMC8175297 DOI: 10.1007/s00259-020-05174-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 12/20/2020] [Indexed: 11/08/2022]
Abstract
Purpose To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR. Methods [18F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [18F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density. Results VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERADSOT-based classification (i.e., any region mCERADSOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density. Conclusion VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-020-05174-2.
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Affiliation(s)
- Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Juhan Reimand
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.,Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia.,Radiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Marissa Zwan
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Aida Niñerola-Baizán
- Nuclear Medicine Department, Hospital Clínic Barcelona & Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Andrés Perissinotti
- Nuclear Medicine Department, Hospital Clínic Barcelona & Biomedical Research Networking Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Philip Scheltens
- Alzheimer Center and department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Universitat Pompeu Fabra, Barcelona, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands.,Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, UK
| | | | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands. .,Department of Radiology and Nuclear Medicine, VU University Medical Center, De Boelelaan 1117, 1108 HV, Amsterdam, The Netherlands.
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA. .,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain. .,Alzheimer Prevention Program, BarcelonaBeta Brain Research Center (BBRC), C/ Wellington, 30, 08005, Barcelona, Spain.
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van Oostveen WM, de Lange ECM. Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring. Int J Mol Sci 2021; 22:ijms22042110. [PMID: 33672696 PMCID: PMC7924338 DOI: 10.3390/ijms22042110] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/15/2021] [Accepted: 02/16/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death. INTRODUCTION In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD. AIM In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed. FINDINGS Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure. CONCLUSIONS Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.
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Affiliation(s)
- Wieke M. van Oostveen
- Faculty of Science, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands;
| | - Elizabeth C. M. de Lange
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre of Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands
- Correspondence: ; Tel.: +31-71-527-6330
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Si Z, Wang X. Stem Cell Therapies in Alzheimer's Disease: Applications for Disease Modeling. J Pharmacol Exp Ther 2021; 377:207-217. [PMID: 33558427 DOI: 10.1124/jpet.120.000324] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 02/03/2021] [Indexed: 12/19/2022] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with complex pathologic and biologic characteristics. Extracellular β-amyloid deposits, such as senile plaques, and intracellular aggregation of hyperphosphorylated tau, such as neurofibrillary tangles, remain the main neuropathological criteria for the diagnosis of AD. There is currently no effective treatment of the disease, and many clinical trials have failed to prove any benefits of new therapeutics. More recently, there has been increasing interest in harnessing the potential of stem cell technologies for drug discovery, disease modeling, and cell therapies, which have been used to study an array of human conditions, including AD. The recently developed and optimized induced pluripotent stem cell (iPSC) technology is a critical platform for screening anti-AD drugs and understanding mutations that modify AD. Neural stem cell (NSC) transplantation has been investigated as a new therapeutic approach to treat neurodegenerative diseases. Mesenchymal stem cells (MSCs) also exhibit considerable potential to treat neurodegenerative diseases by secreting growth factors and exosomes, attenuating neuroinflammation. This review highlights recent progress in stem cell research and the translational applications and challenges of iPSCs, NSCs, and MSCs as treatment strategies for AD. Even though these treatments are still in relative infancy, these developing stem cell technologies hold considerable promise to combat AD and other neurodegenerative disorders. SIGNIFICANCE STATEMENT: Alzheimer's disease (AD) is a neurodegenerative disease that results in learning and memory defects. Although some drugs have been approved for AD treatment, fewer than 20% of patients with AD benefit from these drugs. Therapies based on stem cells, including induced pluripotent stem cells, neural stem cells, and mesenchymal stem cells, provide promising therapeutic strategies for AD.
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Affiliation(s)
- Zizhen Si
- Department of Physiology and Pharmacology, School of Medicine, Ningbo University, Ningbo, China (Z.S.) and Department of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, China (X.W.)
| | - Xidi Wang
- Department of Physiology and Pharmacology, School of Medicine, Ningbo University, Ningbo, China (Z.S.) and Department of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, China (X.W.)
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Giacomucci G, Mazzeo S, Bagnoli S, Casini M, Padiglioni S, Polito C, Berti V, Balestrini J, Ferrari C, Lombardi G, Ingannato A, Sorbi S, Nacmias B, Bessi V. Matching Clinical Diagnosis and Amyloid Biomarkers in Alzheimer's Disease and Frontotemporal Dementia. J Pers Med 2021; 11:jpm11010047. [PMID: 33466854 PMCID: PMC7830228 DOI: 10.3390/jpm11010047] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/08/2021] [Accepted: 01/09/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND The aims of this study were to compare the diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values (PPV, NPV) of different cerebrospinal fluid (CSF) amyloid biomarkers and amyloid-Positron Emission Tomography (PET) in patients with a clinical diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD); to compare concordance between biomarkers; and to provide an indication of their use and interpretation. METHODS We included 148 patients (95 AD and 53 FTD), who underwent clinical evaluation, neuropsychological assessment, and at least one amyloid biomarker (CSF analysis or amyloid-PET). Thirty-six patients underwent both analyses. One-hundred-thirteen patients underwent Apolipoprotein E (ApoE) genotyping. RESULTS Amyloid-PET presented higher diagnostic accuracy, sensitivity, and NPV than CSF Aβ1-42 but not Aβ42/40 ratio. Concordance between CSF biomarkers and amyloid-PET was higher in FTD patients compared to AD cases. None of the AD patients presented both negative Aβ biomarkers. CONCLUSIONS CSF Aβ42/40 ratio significantly increased the diagnostic accuracy of CSF biomarkers. On the basis of our current and previous data, we suggest a flowchart to guide the use of biomarkers according to clinical suspicion: due to the high PPV of both amyloid-PET and CSF analysis including Aβ42/40, in cases of concordance between at least one biomarker and clinical diagnosis, performance of the other analysis could be avoided. A combination of both biomarkers should be performed to better characterize unclear cases. If the two amyloid biomarkers are both negative, an underlying AD pathology can most probably be excluded.
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Affiliation(s)
- Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
- IRCCS Fondazione Don Carlo Gnocchi, Via Scandicci 269, 50143 Florence, Italy;
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Matteo Casini
- Faculty of Medicine and Surgery, University of Florence, Largo Brambilla 3, 50134 Florence, Italy;
| | - Sonia Padiglioni
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Cristina Polito
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
- IRCCS Fondazione Don Carlo Gnocchi, Via Scandicci 269, 50143 Florence, Italy;
| | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, Via Giovanni Battista Morgagni 50, 50134 Florence, Italy;
- Nuclear Medicine Unit, Azienda Ospedaliero-Universitaria Careggi, Largo Piero Palagi 1, 50139 Florence, Italy
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Camilla Ferrari
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Gemma Lombardi
- IRCCS Fondazione Don Carlo Gnocchi, Via Scandicci 269, 50143 Florence, Italy;
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
- IRCCS Fondazione Don Carlo Gnocchi, Via Scandicci 269, 50143 Florence, Italy;
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
- IRCCS Fondazione Don Carlo Gnocchi, Via Scandicci 269, 50143 Florence, Italy;
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence (NEUROFARBA), Azienda Ospedaliera-Universitaria Careggi, Largo Brambilla 3, 50134 Florence, Italy; (G.G.); (S.M.); (S.B.); (S.P.); (C.P.); (J.B.); (C.F.); (A.I.); (S.S.); (B.N.)
- Correspondence: ; Tel.: +39-05-7948660; Fax: +39-05-7947484
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Sala A, Nordberg A, Rodriguez-Vieitez E. Longitudinal pathways of cerebrospinal fluid and positron emission tomography biomarkers of amyloid-β positivity. Mol Psychiatry 2021; 26:5864-5874. [PMID: 33303945 PMCID: PMC8758501 DOI: 10.1038/s41380-020-00950-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 10/09/2020] [Accepted: 11/02/2020] [Indexed: 01/20/2023]
Abstract
Mismatch between CSF and PET amyloid-β biomarkers occurs in up to ≈20% of preclinical/prodromal Alzheimer's disease individuals. Factors underlying mismatching results remain unclear. In this study we hypothesized that CSF/PET discordance provides unique biological/clinical information. To test this hypothesis, we investigated non-demented and demented participants with CSF amyloid-β42 and [18F]Florbetapir PET assessments at baseline (n = 867) and at 2-year follow-up (n = 289). Longitudinal trajectories of amyloid-β positivity were tracked simultaneously for CSF and PET biomarkers. In the longitudinal cohort (n = 289), we found that participants with normal CSF/PET amyloid-β biomarkers progressed more frequently toward CSF/PET discordance than to full CSF/PET positivity (χ2(1) = 5.40; p < 0.05). Progression to CSF+/PET+ status was ten times more frequent in cases with discordant biomarkers, as compared to csf-/pet- cases (χ2(1) = 18.86; p < 0.001). Compared to the CSF+/pet- group, the csf-/PET+ group had lower APOE-ε4ε4 prevalence (χ2(6) = 197; p < 0.001; n = 867) and slower rate of brain amyloid-β accumulation (F(3,600) = 12.76; p < 0.001; n = 608). These results demonstrate that biomarker discordance is a typical stage in the natural history of amyloid-β accumulation, with CSF or PET becoming abnormal first and not concurrently. Therefore, biomarker discordance allows for identification of individuals with elevated risk of progression toward fully abnormal amyloid-β biomarkers, with subsequent risk of neurodegeneration and cognitive decline. Our results also suggest that there are two alternative pathways ("CSF-first" vs. "PET-first") toward established amyloid-β pathology, characterized by different genetic profiles and rates of amyloid-β accumulation. In conclusion, CSF and PET amyloid-β biomarkers provide distinct information, with potential implications for their use as biomarkers in clinical trials.
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Affiliation(s)
- Arianna Sala
- grid.4714.60000 0004 1937 0626Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.15496.3f0000 0001 0439 0892Vita-Salute San Raffaele University, Milan, Italy ,grid.18887.3e0000000417581884In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Agneta Nordberg
- grid.4714.60000 0004 1937 0626Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Theme Aging, The Aging Brain, Karolinska University Hospital, Stockholm, Sweden
| | - Elena Rodriguez-Vieitez
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
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Chiotis K, Savitcheva I, Poulakis K, Saint-Aubert L, Wall A, Antoni G, Nordberg A. [ 18F]THK5317 imaging as a tool for predicting prospective cognitive decline in Alzheimer's disease. Mol Psychiatry 2021; 26:5875-5887. [PMID: 32616831 PMCID: PMC8758479 DOI: 10.1038/s41380-020-0815-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 05/09/2020] [Accepted: 06/08/2020] [Indexed: 11/09/2022]
Abstract
Cross-sectional studies have indicated potential for positron emission tomography (PET) in imaging tau pathology in Alzheimer's disease (AD); however, its prognostic utility remains unproven. In a longitudinal, multi-modal, prognostic study of cognitive decline, 20 patients with a clinical biomarker-based diagnosis in the AD spectrum (mild cognitive impairment or dementia and a positive amyloid-beta PET scan) were recruited from the Cognitive Clinic at Karolinska University Hospital. The participants underwent baseline neuropsychological assessment, PET imaging with [18F]THK5317, [11C]PIB and [18F]FDG, magnetic resonance imaging, and in a subgroup cerebrospinal fluid (CSF) sampling, with clinical follow-up after a median 48 months (interquartile range = 32:56). In total, 11 patients declined cognitively over time, while 9 remained cognitively stable. The accuracy of baseline [18F]THK5317 binding in temporal areas was excellent at predicting future cognitive decline (area under the receiver operating curve 0.84-1.00) and the biomarker levels were strongly associated with the rate of cognitive decline (β estimate -33.67 to -31.02, p < 0.05). The predictive accuracy of the other baseline biomarkers was poor (area under the receiver operating curve 0.58-0.77) and their levels were not associated with the rate of cognitive decline (β estimate -4.64 to 15.78, p > 0.05). Baseline [18F]THK5317 binding and CSF tau levels were more strongly associated with the MMSE score at follow-up than at baseline (p < 0.05). These findings support a temporal dissociation between tau deposition and cognitive impairment, and suggest that [18F]THK5317 predicts future cognitive decline better than other biomarkers. The use of imaging markers for tau pathology could prove useful for clinical prognostic assessment and screening before inclusion in relevant clinical trials.
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Affiliation(s)
- Konstantinos Chiotis
- grid.4714.60000 0004 1937 0626Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.24381.3c0000 0000 9241 5705Theme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- grid.24381.3c0000 0000 9241 5705Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Poulakis
- grid.4714.60000 0004 1937 0626Westman neuroimaging group, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Laure Saint-Aubert
- grid.4714.60000 0004 1937 0626Nordberg Translational Molecular Imaging Lab, Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden ,grid.15781.3a0000 0001 0723 035XToulouse NeuroImaging Center, University of Toulouse, Inserm, UPS, Toulouse, France
| | - Anders Wall
- grid.8993.b0000 0004 1936 9457Section for Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Gunnar Antoni
- grid.8993.b0000 0004 1936 9457Department of Medicinal Chemistry, Uppsala University, Uppsala, Sweden
| | - Agneta Nordberg
- Nordberg Translational Molecular Imaging Lab, 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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Sörensen A, Blazhenets G, Schiller F, Meyer PT, Frings L. Amyloid biomarkers as predictors of conversion from mild cognitive impairment to Alzheimer's dementia: a comparison of methods. Alzheimers Res Ther 2020; 12:155. [PMID: 33213489 PMCID: PMC7678323 DOI: 10.1186/s13195-020-00721-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 11/05/2020] [Indexed: 11/30/2022]
Abstract
Background Amyloid-β (Aβ) PET is an established predictor of conversion from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). We compared three PET (including an approach based on voxel-wise Cox regression) and one cerebrospinal fluid (CSF) outcome measures in their predictive power. Methods Datasets were retrieved from the ADNI database. In a training dataset (N = 159), voxel-wise Cox regression and principal component analyses were used to identify conversion-related regions (Cox-VOI and AD conversion-related pattern (ADCRP), respectively). In a test dataset (N = 129), the predictive value of mean normalized 18F-florbetapir uptake (SUVR) in AD-typical brain regions (composite SUVR) or the Cox-VOI and the pattern expression score (PES) of ADCRP and CSF Aβ42/Aβ40 as predictors were compared by Cox models (corrected for age and sex). Results All four Aβ measures were significant predictors (p < 0.001). Prediction accuracies (Harrell’s c) showed step-wise significant increases from Cox-SUVR (c = 0.71; HR = 1.84 per Z-score increase), composite SUVR (c = 0.73; HR = 2.18), CSF Aβ42/Aβ40 (c = 0.75; HR = 3.89) to PES (c = 0.77; HR = 2.71). Conclusion The PES of ADCRP is the most predictive Aβ PET outcome measure, comparable to CSF Aβ42/Aβ40, with a slight but statistically significant advantage.
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Affiliation(s)
- Arnd Sörensen
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany.
| | - Ganna Blazhenets
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany
| | - Florian Schiller
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany
| | - Philipp Tobias Meyer
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany
| | - Lars Frings
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany
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31
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Farrell ME, Jiang S, Schultz AP, Properzi MJ, Price JC, Becker JA, Jacobs HIL, Hanseeuw BJ, Rentz DM, Villemagne VL, Papp KV, Mormino EC, Betensky RA, Johnson KA, Sperling RA, Buckley RF. Defining the Lowest Threshold for Amyloid-PET to Predict Future Cognitive Decline and Amyloid Accumulation. Neurology 2020; 96:e619-e631. [PMID: 33199430 DOI: 10.1212/wnl.0000000000011214] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 09/21/2020] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION As clinical trials move toward earlier intervention, we sought to redefine the β-amyloid (Aβ)-PET threshold based on the lowest point in a baseline distribution that robustly predicts future Aβ accumulation and cognitive decline in 3 independent samples of clinically normal individuals. METHODS Sequential Aβ cutoffs were tested to identify the lowest cutoff associated with future change in cognition (Preclinical Alzheimer Cognitive Composite [PACC]) and Aβ-PET in clinically normal participants from the Harvard Aging Brain Study (n = 342), Australian Imaging, Biomarker and Lifestyle study of aging (n = 157), and Alzheimer's Disease Neuroimaging Initiative (n = 356). RESULTS Within samples, cutoffs derived from future Aβ-PET accumulation and PACC decline converged on the same inflection point, beyond which trajectories diverged from normal. Across samples, optimal cutoffs fell within a short range (Centiloid 15-18.5). DISCUSSION These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. Threshold convergence raises the possibility of contemporaneous early changes in Aβ and cognition. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that among clinically normal individuals a specific Aβ-PET threshold is predictive of cognitive decline.
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Affiliation(s)
- Michelle E Farrell
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Shu Jiang
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Aaron P Schultz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Michael J Properzi
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Julie C Price
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - J Alex Becker
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Heidi I L Jacobs
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Bernard J Hanseeuw
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Dorene M Rentz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Kathryn V Papp
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Elizabeth C Mormino
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rebecca A Betensky
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Keith A Johnson
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Reisa A Sperling
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rachel F Buckley
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia.
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Del Prete E, Beatino MF, Campese N, Giampietri L, Siciliano G, Ceravolo R, Baldacci F. Fluid Candidate Biomarkers for Alzheimer's Disease: A Precision Medicine Approach. J Pers Med 2020; 10:E221. [PMID: 33187336 DOI: 10.3390/jpm10040221] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/04/2020] [Accepted: 11/05/2020] [Indexed: 12/11/2022] Open
Abstract
A plethora of dynamic pathophysiological mechanisms underpins highly heterogeneous phenotypes in the field of dementia, particularly in Alzheimer's disease (AD). In such a faceted scenario, a biomarker-guided approach, through the implementation of specific fluid biomarkers individually reflecting distinct molecular pathways in the brain, may help establish a proper clinical diagnosis, even in its preclinical stages. Recently, ultrasensitive assays may detect different neurodegenerative mechanisms in blood earlier. ß-amyloid (Aß) peptides, phosphorylated-tau (p-tau), and neurofilament light chain (NFL) measured in blood are gaining momentum as candidate biomarkers for AD. P-tau is currently the more convincing plasma biomarker for the diagnostic workup of AD. The clinical role of plasma Aβ peptides should be better elucidated with further studies that also compare the accuracy of the different ultrasensitive techniques. Blood NFL is promising as a proxy of neurodegeneration process tout court. Protein misfolding amplification assays can accurately detect α-synuclein in cerebrospinal fluid (CSF), thus representing advancement in the pathologic stratification of AD. In CSF, neurogranin and YKL-40 are further candidate biomarkers tracking synaptic disruption and neuroinflammation, which are additional key pathophysiological pathways related to AD genesis. Advanced statistical analysis using clinical scores and biomarker data to bring together individuals with AD from large heterogeneous cohorts into consistent clusters may promote the discovery of pathophysiological causes and detection of tailored treatments.
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Suárez-Calvet M, Karikari TK, Ashton NJ, Lantero Rodríguez J, Milà-Alomà M, Gispert JD, Salvadó G, Minguillon C, Fauria K, Shekari M, Grau-Rivera O, Arenaza-Urquijo EM, Sala-Vila A, Sánchez-Benavides G, González-de-Echávarri JM, Kollmorgen G, Stoops E, Vanmechelen E, Zetterberg H, Blennow K, Molinuevo JL. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer's continuum when only subtle changes in Aβ pathology are detected. EMBO Mol Med 2020; 12:e12921. [PMID: 33169916 PMCID: PMC7721364 DOI: 10.15252/emmm.202012921] [Citation(s) in RCA: 174] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 09/09/2020] [Accepted: 09/09/2020] [Indexed: 01/01/2023] Open
Abstract
In Alzheimer's disease (AD), tau phosphorylation in the brain and its subsequent release into cerebrospinal fluid (CSF) and blood is a dynamic process that changes during disease evolution. The main aim of our study was to characterize the pattern of changes in phosphorylated tau (p-tau) in the preclinical stage of the Alzheimer's continuum. We measured three novel CSF p-tau biomarkers, phosphorylated at threonine-181 and threonine-217 with an N-terminal partner antibody and at threonine-231 with a mid-region partner antibody. These were compared with an automated mid-region p-tau181 assay (Elecsys) as the gold standard p-tau measure. We demonstrate that these novel p-tau biomarkers increase more prominently in preclinical Alzheimer, when only subtle changes of amyloid-β (Aβ) pathology are detected, and can accurately differentiate Aβ-positive from Aβ-negative cognitively unimpaired individuals. Moreover, we show that the novel plasma N-terminal p-tau181 biomarker is mildly but significantly increased in the preclinical stage. Our results support the idea that early changes in neuronal tau metabolism in preclinical Alzheimer, likely in response to Aβ exposure, can be detected with these novel p-tau assays.
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Affiliation(s)
- Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Wallenberg Centre for Molecular and Translational Medicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK.,NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Juan Lantero Rodríguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Eider M Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aleix Sala-Vila
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - José Maria González-de-Echávarri
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
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Abstract
Alzheimer's disease (AD) is a neurodegenerative disease characterized by complex pathological and biological features. Notably, extracellular amyloid-β deposits as senile plaques and intracellular aggregation of hyperphosphorylated tau as neurofibrillary tangles remain the primary premortem criterion for the diagnosis of AD. Currently, there exist no disease-modifying therapies for AD, and many clinical trials have failed to show its benefits for patients. Heme oxygenase 1 (HO-1) is a 32 kDa enzyme, which catalyzes the degradation of cellular heme to free ferrous iron, biliverdin, and carbon monoxide under stressful conditions. Several studies highlight the crucial pathological roles of HO-1 in the molecular processes of AD. The beneficial roles of HO-1 overexpression in AD brains are widely accepted due to its ability to convert pro-oxidant heme to biliverdin and bilirubin (antioxidants), which promote restoration of a suitable tissue redox microenvironment. However, the intracellular oxidative stress might be amplified by metabolites of HO-1 and exacerbate the progression of AD under certain circumstances. Several lines of evidence have demonstrated that upregulated HO-1 is linked to tauopathies, neuronal damage, and synapse aberrations in AD. Here, we review the aspects of the molecular mechanisms by which HO-1 regulates AD and the latest information on the pathobiology of AD. We further highlight the neuroprotective and neurodystrophic actions of HO-1 and the feasibility of HO-1 as a therapeutic target for AD.
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Affiliation(s)
- Zizhen Si
- Department of Physiology and Pharmacology, Ningbo University School of Medicine, Ningbo, China
| | - Xidi Wang
- Department of Biochemistry and Molecular Biology, Harbin Medical University, Harbin, China
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Bjorkli C, Sandvig A, Sandvig I. Bridging the Gap Between Fluid Biomarkers for Alzheimer's Disease, Model Systems, and Patients. Front Aging Neurosci 2020; 12:272. [PMID: 32982716 PMCID: PMC7492751 DOI: 10.3389/fnagi.2020.00272] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 08/06/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer’s disease (AD) is a debilitating neurodegenerative disease characterized by the accumulation of two proteins in fibrillar form: amyloid-β (Aβ) and tau. Despite decades of intensive research, we cannot yet pinpoint the exact cause of the disease or unequivocally determine the exact mechanism(s) underlying its progression. This confounds early diagnosis and treatment of the disease. Cerebrospinal fluid (CSF) biomarkers, which can reveal ongoing biochemical changes in the brain, can help monitor developing AD pathology prior to clinical diagnosis. Here we review preclinical and clinical investigations of commonly used biomarkers in animals and patients with AD, which can bridge translation from model systems into the clinic. The core AD biomarkers have been found to translate well across species, whereas biomarkers of neuroinflammation translate to a lesser extent. Nevertheless, there is no absolute equivalence between biomarkers in human AD patients and those examined in preclinical models in terms of revealing key pathological hallmarks of the disease. In this review, we provide an overview of current but also novel AD biomarkers and how they relate to key constituents of the pathological cascade, highlighting confounding factors and pitfalls in interpretation, and also provide recommendations for standardized procedures during sample collection to enhance the translational validity of preclinical AD models.
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Affiliation(s)
- Christiana Bjorkli
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Axel Sandvig
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.,Institute of Neuromedicine and Movement Science, Department of Neurology, St. Olavs Hospital, Trondheim, Norway.,Department of Pharmacology and Clinical Neurosciences, Division of Neuro, Head, and Neck, University Hospital of Umeå, Umeå, Sweden
| | - Ioanna Sandvig
- Sandvig Group, Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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Guo T, Korman D, La Joie R, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Normalization of CSF pTau measurement by Aβ 40 improves its performance as a biomarker of Alzheimer's disease. Alzheimers Res Ther 2020; 12:97. [PMID: 32799929 PMCID: PMC7429887 DOI: 10.1186/s13195-020-00665-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/04/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alzheimer's disease (AD)-related tauopathy can be measured with CSF phosphorylated tau (pTau) and tau PET. We aim to investigate the associations between these measurements and their relative ability to predict subsequent disease progression. METHODS In 219 cognitively unimpaired and 122 impaired Alzheimer's Disease Neuroimaging Initiative participants with concurrent amyloid-β (Aβ) PET (18F-florbetapir or 18F-florbetaben), 18F-flortaucipir (FTP) PET, CSF measurements, structural MRI, and cognition, we examined inter-relationships between these biomarkers and their predictions of subsequent FTP and cognition changes. RESULTS The use of a CSF pTau/Aβ40 ratio eliminated positive associations we observed between CSF pTau alone and CSF Aβ42 in the normal Aβ range likely reflecting individual differences in CSF production rather than pathology. Use of the CSF pTau/Aβ40 ratio also increased expected associations with Aβ PET, FTP PET, hippocampal volume, and cognitive decline compared to pTau alone. In Aβ+ individuals, abnormal CSF pTau/Aβ40 only individuals (26.7%) were 4 times more prevalent (p < 0.001) than abnormal FTP only individuals (6.8%). Furthermore, among individuals on the AD pathway, CSF pTau/Aβ40 mediates the association between Aβ PET and FTP PET accumulation, but FTP PET is more closely linked to subsequent cognitive decline than CSF pTau/Aβ40. CONCLUSIONS Together, these findings suggest that CSF pTau/Aβ40 may be a superior measure of tauopathy compared to CSF pTau alone, and CSF pTau/Aβ40 enables detection of tau accumulation at an earlier stage than FTP among Aβ+ individuals.
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Affiliation(s)
- Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA.
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
| | - Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Guo T, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Association of CSF Aβ, amyloid PET, and cognition in cognitively unimpaired elderly adults. Neurology 2020; 95:e2075-e2085. [PMID: 32759202 DOI: 10.1212/wnl.0000000000010596] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 04/28/2020] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE To compare CSF β-amyloid (Aβ) and florbetapir PET measurements in cognitively unimpaired (CU) elderly adults in order to detect the earliest abnormalities and compare their predictive effect for cognitive decline. METHODS A total of 259 CU individuals were categorized as abnormal (+) or normal (-) on CSF Aβ1-42/Aβ1-40 analyzed with mass spectrometry and Aβ PET measured with 18F-florbetapir. Simultaneous longitudinal measurements of CSF and PET were compared for 39 individuals who were unambiguously Aβ-negative at baseline (CSF-/PET-). We also examined the relationship between baseline CSF/PET group membership and longitudinal changes in CSF Aβ, Aβ PET, and cognition. RESULTS The proportions of individuals in each discordant group were similar (8.1% CSF+/PET- and 7.7% CSF-/PET+). Among baseline Aβ-negative (CSF-/PET-) individuals with longitudinal CSF and PET measurements, a larger proportion subsequently worsened on CSF Aβ (odds ratio 4 [95% confidence interval (CI) 1.1, 22.1], p = 0.035) than Aβ PET over 3.5 ± 1.0 years. Compared to CSF-/PET- individuals, CSF+/PET- individuals had faster (estimate 0.009 [95% CI 0.005, 0.013], p < 0.001) rates of Aβ PET accumulation over 4.4 ± 1.7 years, while CSF-/PET+ individuals had faster (estimate -0.492 [95% CI -0.861, -0.123], p = 0.01) rates of cognitive decline over 4.5 ± 1.9 years. CONCLUSIONS The proportions of discordant PET and CSF Aβ-positive individuals were similar cross-sectionally. However, unambiguously Aβ-negative (CSF-/PET-) individuals are more likely to show subsequent worsening on CSF than PET, supporting the idea that CSF detects the earliest Aβ changes. In discordant cases, only PET abnormality predicted cognitive decline, suggesting that abnormal Aβ PET changes are a later phenomenon in cognitively normal individuals.
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Affiliation(s)
- Tengfei Guo
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia.
| | - Leslie M Shaw
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - John Q Trojanowski
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - William J Jagust
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Susan M Landau
- From the Helen Wills Neuroscience Institute (T.G., W.J.J., S.M.L.), University of California; Molecular Biophysics and Integrated Bioimaging (T.G., W.J.J., S.M.L.), Lawrence Berkeley National Laboratory, Berkeley, CA; and Department of Pathology and Laboratory Medicine (L.M.S., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Venkataraman I, Naides SJ. The Development of New Diagnostic Tests for Neurologic Disorders in the Commercial Laboratory Environment. Clin Lab Med 2020; 40:331-339. [PMID: 32718503 DOI: 10.1016/j.cll.2020.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Development of new diagnostic tests in a commercial laboratory for neurologic disorders is challenging. Development occurs in a highly regulated environment. Relevant research infrastructure may not be readily available in-house and may require outsourcing with additional management and costs. Clinically characterized specimens for validation of biomarkers for esoteric diseases may be difficult to acquire, and market size may be difficult to predict. More common diseases with heterogeneous subsets may require better clinical definition. Absence of guidelines may delay health provider acceptance of novel testing. Regulatory agency approval and categorization of tests affects validation requirements and impacts market acceptance and reimbursement.
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Affiliation(s)
- Iswariya Venkataraman
- Scientific Affairs, EUROIMMUN US, 1 Bloomfield Avenue, Mountain Lakes, New Jersey 07046, USA
| | - Stanley J Naides
- Scientific Affairs, EUROIMMUN US, 1 Bloomfield Avenue, Mountain Lakes, New Jersey 07046, USA.
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Alves L, Cardoso S, Silva D, Mendes T, Marôco J, Nogueira J, Lima M, Tábuas-Pereira M, Baldeiras I, Santana I, de Mendonça A, Guerreiro M. Neuropsychological profile of amyloid-positive versus amyloid-negative amnestic Mild Cognitive Impairment. J Neuropsychol 2020; 15 Suppl 1:41-52. [PMID: 32588984 DOI: 10.1111/jnp.12218] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/19/2020] [Indexed: 12/11/2022]
Abstract
INTRODUCTION Patients diagnosed with amnestic mild cognitive impairment (aMCI) are at high risk of progressing to dementia. It became possible, through the use of biomarkers, to diagnose those patients with aMCI who have Alzheimer's disease. However, it is presently unfeasible that all patients undergo biomarker testing. Since neuropsychological testing is required to make a formal diagnosis of aMCI, it would be interesting if it could be used to predict the amyloid status of patients with aMCI. METHODS Participants with aMCI, known amyloid status (Aβ+ or Aβ-) and a comprehensive neuropsychological evaluation, were selected from the Cognitive Complaints Cohort database for this study. Neuropsychological tests were compared in Aβ+ and Aβ- aMCI patients. A binary logistic regression analysis was conducted to model the probability of being amyloid positive. RESULTS Of the 216 aMCI patients studied, 117 were Aβ+ and 99 were Aβ-. Aβ+ aMCI patients performed worse on several memory tests, namely Word Total Recall, Logical Memory Immediate and Delayed Free Recall, and Verbal Paired Associate Learning, as well as on Trail Making Test B, an executive function test. In a binary logistic regression model, only Logical Memory Delayed Free Recall retained significance, so that for each additional score point in this test, the probability of being amyloid positive decreased by 30.6%. The resulting model correctly classified 64.6% of the aMCI cases regarding their amyloid status. CONCLUSIONS The neuropsychological assessment remains an essential step to diagnose and characterize patients with aMCI; however, neuropsychological tests have limited value to distinguish the aMCI patients who have amyloid pathology from those who might suffer from other clinical conditions.
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Affiliation(s)
- Luísa Alves
- Chronic Diseases Research Centre, NOVA Medical School, NOVA University of Lisbon, Portugal
| | | | - Dina Silva
- Faculty of Medicine, University of Lisbon, Portugal.,Cognitive Neuroscience Research Group, Department of Psychology and Educational Sciences and Center for Biomedical Research (CBMR), Universidade do Algarve, Faro, Portugal
| | - Tiago Mendes
- Faculty of Medicine, University of Lisbon, Portugal.,Psychiatry and Mental Health Department, Santa Maria Hospital, Lisbon, Portugal
| | - João Marôco
- Instituto Superior de Psicologia Aplicada, Lisbon, Portugal
| | - Joana Nogueira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal.,Faculdade de Medicina da Universidade de Coimbra, Portugal
| | - Marisa Lima
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal.,Faculdade de Medicina da Universidade de Coimbra, Portugal
| | - Miguel Tábuas-Pereira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal.,Faculdade de Medicina da Universidade de Coimbra, Portugal
| | - Inês Baldeiras
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal.,Faculdade de Medicina da Universidade de Coimbra, Portugal
| | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Portugal.,Faculdade de Medicina da Universidade de Coimbra, Portugal
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Cai J, Yi P, Miao Y, Liu J, Hu Y, Liu Q, Feng Y, Chen H, Li L. Ultrasmall T1- T2 Magnetic Resonance Multimodal Imaging Nanoprobes for the Detection of β-amyloid Aggregates in Alzheimer's Disease Mice. ACS Appl Mater Interfaces 2020; 12:26812-26821. [PMID: 32427456 DOI: 10.1021/acsami.0c01597] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Alzheimer's disease (AD) is an irreversible brain disorder and imposes a severe burden upon patients and the public health system. Most research efforts have focused on the search for effective therapeutic drugs, but it is time to pursue efficient early diagnosis based on the reasonable assumption that AD may be easier to prevent than reverse. Recent studies have shown that there are several probes for detecting amyloid-β (Aβ) plaques, one of the neuropathological hallmarks found in AD brain. However, it is still a great challenge for nonradioactive, sensitive detection and location of Aβ plaques by brain imaging with high spatial resolution. Herein, phenothiazine derivative (PZD)-conjugated sub-5 nm ultrasmall ferrite nanoprobes (UFNPs@PEG/PZD) are designed and prepared for efficient T1-T2 magnetic resonance multimodal imaging of Aβ plaques. UFNPs@PEG/PZD not only possess high binding affinity to Aβ plaques but also exhibit excellent properties of r1 and r2 relaxivities. This study thus provides a promising ultrasmall nanoplatform as an Aβ-targeting multimodal imaging probe for the application of early diagnosis of AD.
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Affiliation(s)
- Jing Cai
- Imaging Diagnosis and Interventional Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
- CNRS, UMR8601, Laboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, CBNIT, Université Paris Descartes, PRES Sorbonne Paris Cité, UFR, Biomédicale, 75006 Paris, France
| | - Peiwei Yi
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 510515 Guangzhou, China
- CNRS, UMR8601, Laboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, CBNIT, Université Paris Descartes, PRES Sorbonne Paris Cité, UFR, Biomédicale, 75006 Paris, France
| | - Yuqing Miao
- Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, 710072 Xi'an, China
| | - Jinbo Liu
- Imaging Diagnosis and Interventional Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Yaofang Hu
- Department of Oncology, The Air Force Hospital of Southern Theater Command, 510000 Guangzhou, China
| | - Qicai Liu
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Laboratory of Heart Center, Zhujiang Hospital, Southern Medical University, 510515 Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, 510515 Guangzhou, China
- CNRS, UMR8601, Laboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, CBNIT, Université Paris Descartes, PRES Sorbonne Paris Cité, UFR, Biomédicale, 75006 Paris, France
| | - Huixiong Chen
- CNRS, UMR8601, Laboratoire de Chimie et Biochimie Pharmacologiques et Toxicologiques, CBNIT, Université Paris Descartes, PRES Sorbonne Paris Cité, UFR, Biomédicale, 75006 Paris, France
| | - Li Li
- Imaging Diagnosis and Interventional Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
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Lewczuk P, Łukaszewicz-Zając M, Mroczko P, Kornhuber J. Clinical significance of fluid biomarkers in Alzheimer's Disease. Pharmacol Rep 2020; 72:528-542. [PMID: 32385624 PMCID: PMC7329803 DOI: 10.1007/s43440-020-00107-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 04/21/2020] [Accepted: 04/21/2020] [Indexed: 12/23/2022]
Abstract
The number of patients with Alzheimer's Disease (AD) and other types of dementia disorders has drastically increased over the last decades. AD is a complex progressive neurodegenerative disease affecting about 14 million patients in Europe and the United States. The hallmarks of this disease are neurotic plaques consist of the Amyloid-β peptide (Aβ) and neurofibrillary tangles (NFTs) formed of hyperphosphorylated Tau protein (pTau). Currently, four CSF biomarkers: Amyloid beta 42 (Aβ42), Aβ42/40 ratio, Tau protein, and Tau phosphorylated at threonine 181 (pTau181) have been indicated as core neurochemical AD biomarkers. However, the identification of additional fluid biomarkers, useful in the prognosis, risk stratification, and monitoring of drug response is sorely needed to better understand the complex heterogeneity of AD pathology as well as to improve diagnosis of patients with the disease. Several novel biomarkers have been extensively investigated, and their utility must be proved and eventually integrated into guidelines for use in clinical practice. This paper presents the research and development of CSF and blood biomarkers for AD as well as their potential clinical significance. Upper panel: Aβ peptides are released from transmembrane Amyloid Precursor Protein (APP) under physiological conditions (blue arrow). In AD, however, pathologic accumulation of Aβ monomers leads to their accumulation in plaques (red arrow). This is reflected in decreased concentration of Aβ1-42 and decreased Aβ42/40 concentration ratio in the CSF. Lower panel: Phosphorylated Tau molecules maintain axonal structures; hyperphosphorylation of Tau (red arrow) in AD leads to degeneration of axons, and release of pTau molecules, which then accumulate in neurofibrillary tangles. This process is reflected by increased concentrations of Tau and pTau in the CSF.
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Affiliation(s)
- Piotr Lewczuk
- Lab for Clinical Neurochemistry and Neurochemical Dementia Diagnostics, Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany.
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, Białystok, Poland.
| | | | - Piotr Mroczko
- Department of Criminal Law and Criminology, Faculty of Law, University of Białystok, Białystok, Poland
| | - Johannes Kornhuber
- Lab for Clinical Neurochemistry and Neurochemical Dementia Diagnostics, Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
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Spallazzi M, Barocco F, Michelini G, Morelli N, Scarlattei M, Baldari G, Ruffini L, Caffarra P. The Incremental Diagnostic Value of [18F]Florbetaben PET and the Pivotal Role of the Neuropsychological Assessment in Clinical Practice. J Alzheimers Dis 2020; 67:1235-1244. [PMID: 30689568 DOI: 10.3233/jad-180646] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Amyloid pathology is a key feature of Alzheimer's disease (AD) and can be assessed in vivo with amyloid positron emission tomography (PET) imaging. OBJECTIVE The objective of this study was to evaluate the incremental value of a PET scan with [18F]florbetaben, in terms of changes of diagnosis, diagnostic confidence, and treatment plan when added to a standardized diagnostic workup for cognitive disorders, with particular focus on the role of the neuropsychological assessment, including the Free and Cued Selective Reminding Test (FCSRT). METHODS A total of 104 patients (69 mild cognitive impairment, 35 dementia), with diagnostic uncertainty after diagnostic workup, were recruited from our memory clinic. [18F]florbetaben PET scans were interpreted as amyloid negative or positive on the basis of a semi-quantitative visual rating. Clinical diagnosis and diagnostic confidence for AD or non-AD dementia were rated before and after PET result disclosure, as was the impact of PET on the patient management plan. RESULTS There were 69/104 (66%) [18F]florbetaben positive scans, 51/62 (82%) patients were suspected as having AD before the PET scan and 18/42 (43%) were not. Overall, the data obtained at PET changed 18/104 diagnoses (17%) and increased diagnostic confidence from 69.1±8.1% to 83.5±9.1 (p < 0.001), with the greatest impact on diagnosis and confidence in PET negative patients with an initial diagnosis of AD (p < 0.01) and in early-onset patients (p = 0.01). CONCLUSION Amyloid PET represents a source of added value in dementia diagnosis, with a significant effect on diagnosis and diagnostic confidence. However, the use of a complete neuropsychological assessment has an add-on value on limiting the amyloid PET influence on change of diagnosis, and the real impact of amyloid PET should always be weighed up together with an accurate standardized diagnostic workup.
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Affiliation(s)
- Marco Spallazzi
- Department of Neurology, G. da Saliceto Hospital, Piacenza, Italy
| | | | | | - Nicola Morelli
- Department of Neurology, G. da Saliceto Hospital, Piacenza, Italy
| | - Maura Scarlattei
- Department of Nuclear Medicine, Azienda Ospedaliero-Universitaria, Parma, Italy
| | - Giorgio Baldari
- Department of Nuclear Medicine, Azienda Ospedaliero-Universitaria, Parma, Italy
| | - Livia Ruffini
- Department of Nuclear Medicine, Azienda Ospedaliero-Universitaria, Parma, Italy
| | - Paolo Caffarra
- Alzheimer Center, Briolini Hospital, Gazzaniga, Bergamo, Italy.,Department of Medicine and Surgery, Section of Neuroscience, University of Parma, Parma, Italy
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Doecke JD, Ward L, Burnham SC, Villemagne VL, Li QX, Collins S, Fowler CJ, Manuilova E, Widmann M, Rainey-Smith SR, Martins RN, Masters CL. Elecsys CSF biomarker immunoassays demonstrate concordance with amyloid-PET imaging. Alzheimers Res Ther 2020; 12:36. [PMID: 32234072 PMCID: PMC7110644 DOI: 10.1186/s13195-020-00595-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 03/09/2020] [Indexed: 12/17/2022]
Abstract
Background β-amyloid (Aβ) positron emission tomography (PET) imaging is currently the only Food and Drug Administration-approved method to support clinical diagnosis of Alzheimer’s disease (AD). However, numerous research studies support the use of cerebrospinal fluid (CSF) biomarkers, as a cost-efficient, quick and equally valid method to define AD pathology. Methods Using automated Elecsys® assays (Roche Diagnostics) for Aβ (1–42) (Aβ42), Aβ (1–40) (Aβ40), total tau (tTau) and phosphorylated tau (181P) (pTau), we examined CSF samples from 202 participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing cohort, to demonstrate the concordance with pathological AD via PET imaging. Results Ratios Aβ42/Aβ40, tTau/Aβ42 and pTau/Aβ42 had higher receiver operator characteristic—area under the curve (all 0.94), and greater concordance with Aβ-PET (overall percentage agreement ~ 90%), compared with individual biomarkers. Conclusion Strong concordance between CSF biomarkers and Aβ-PET status was observed overall, including for cognitively normal participants, further strengthening the association between these markers of AD neuropathological burden for both developmental research studies and for use in clinical trials. Supplementary information The online version of this article (10.1186/s13195-020-00595-5).
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Affiliation(s)
- James D Doecke
- Cooperative Research Council for Mental Health, Melbourne, Victoria, 3052, Australia. .,Australian E-Health Research Centre, CSIRO Health & Biosecurity, Level 5, 901/16 Royal Brisbane & Women's Hospital, Brisbane, Queensland, 4029, Australia.
| | - Larry Ward
- Cooperative Research Council for Mental Health, Melbourne, Victoria, 3052, Australia
| | - Samantha C Burnham
- Australian E-Health Research Centre, CSIRO, Parkville, Melbourne, Victoria, 3052, Australia
| | - Victor L Villemagne
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia.,Department of Molecular Imaging and Therapy, Center for PET, Austin Health, Heidelberg, Victoria, 3084, Australia
| | - Qiao-Xin Li
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
| | - Steven Collins
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia.,Department of Medicine (RMH), The University of Melbourne, Parkville, Melbourne, Victoria, 3052, Australia
| | - Christopher J Fowler
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
| | | | - Monika Widmann
- Roche Diagnostics GmbH, Sandhoferstrasse 116, 68305, Mannheim, Germany
| | - Stephanie R Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
| | - Ralph N Martins
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, 2113, Australia.,School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, Western Australia, 6009, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
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Amadoru S, Doré V, McLean CA, Hinton F, Shepherd CE, Halliday GM, Leyton CE, Yates PA, Hodges JR, Masters CL, Villemagne VL, Rowe CC. Comparison of amyloid PET measured in Centiloid units with neuropathological findings in Alzheimer's disease. Alzheimers Res Ther 2020; 12:22. [PMID: 32131891 PMCID: PMC7057642 DOI: 10.1186/s13195-020-00587-5] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/13/2020] [Indexed: 12/14/2022]
Abstract
Background The Centiloid scale was developed to standardise the results of beta-amyloid (Aβ) PET. We aimed to determine the Centiloid unit (CL) thresholds for CERAD sparse and moderate-density neuritic plaques, Alzheimer’s disease neuropathologic change (ADNC) score of intermediate or high probability of Alzheimer’s Disease (AD), final clinicopathological diagnosis of AD, and expert visual read of a positive Aβ PET scan. Methods Aβ PET results in CL for 49 subjects were compared with post-mortem findings, visual read, and final clinicopathological diagnosis. The Youden Index was used to determine the optimal CL thresholds from receiver operator characteristic (ROC) curves. Results A threshold of 20.1 CL (21.3 CL when corrected for time to death, AUC 0.97) yielded highest accuracy in detecting moderate or frequent plaque density while < 10 CL was optimal for excluding neuritic plaque. The threshold for ADNC intermediate or high likelihood AD was 49.4 CL (AUC 0.98). Those cases with a final clinicopathological diagnosis of AD yielded a median CL result of 87.7 (IQR ± 42.2) with 94% > 45 CL. Positive visual read agreed highly with results > 26 CL. Conclusions Centiloid values < 10 accurately reflected the absence of any neuritic plaque and > 20 CL indicated the presence of at least moderate plaque density, but approximately 50 CL or more best confirmed both neuropathological and clinicopathological diagnosis of Alzheimer’s disease. Supplementary information Supplementary information accompanies this paper at 10.1186/s13195-020-00587-5.
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Affiliation(s)
- Sanka Amadoru
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia.
| | - Vincent Doré
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia.,CSIRO Health and Biosecurity, Parkville, Victoria, 3052, Australia
| | - Catriona A McLean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Fairlie Hinton
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Claire E Shepherd
- Sydney Brain Bank, Neuroscience Research Australia and Faculty of Medicine, University of NSW, Sydney, Australia
| | - Glenda M Halliday
- Sydney Brain Bank, Neuroscience Research Australia and Faculty of Medicine, University of NSW, Sydney, Australia.,The Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Cristian E Leyton
- The Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Paul A Yates
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia
| | - John R Hodges
- The Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Colin L Masters
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Road, Heidelberg, Vic. 3084, Australia
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Coutinho AM, Busatto GF, de Gobbi Porto FH, de Paula Faria D, Ono CR, Garcez AT, Squarzoni P, de Souza Duran FL, de Oliveira MO, Tres ES, Brucki SMD, Forlenza OV, Nitrini R, Buchpiguel CA. Brain PET amyloid and neurodegeneration biomarkers in the context of the 2018 NIA-AA research framework: an individual approach exploring clinical-biomarker mismatches and sociodemographic parameters. Eur J Nucl Med Mol Imaging 2020; 47:2666-2680. [PMID: 32055966 DOI: 10.1007/s00259-020-04714-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 02/03/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE [18F]FDG-PET and [11C]PIB-PET are validated as neurodegeneration and amyloid biomarkers of Alzheimer's disease (AD). We used a PET staging system based on the 2018 NIA-AA research framework to compare the proportion of amyloid positivity (A+) and hypometabolism ((N)+) in cases of mild probable AD, amnestic mild cognitive impairment (aMCI), and healthy controls, incorporating an additional classification of abnormal [18F]FDG-PET patterns and investigating the co-occurrence of such with A+, exploring [18F]FDG-PET to generate hypotheses in cases presenting with clinical-biomarker "mismatches." METHODS Elderly individuals (N = 108) clinically classified as controls (N = 27), aMCI (N = 43) or mild probable AD (N = 38) were included. Authors assessed their A(N) profiles and classified [18F]FDG-PET neurodegenerative patterns as typical or non-typical of AD, performing re-assessments of images whenever clinical classification was in disagreement with the PET staging (clinical-biomarker "mismatches"). We also investigated associations between "mismatches" and sociodemographic and educational characteristics. RESULTS AD presented with higher rates of A+ and (N)+. There was also a higher proportion of A+ and (N)+ individuals in the aMCI group in comparison to controls, however without statistical significance regarding the A staging. There was a significant association between amyloid positivity and AD (N)+ hypometabolic patterns typical of AD. Non-AD (N)+ hypometabolism was seen in all A- (N)+ cases in the mild probable AD and control groups and [18F]FDG-PET patterns classified such individuals as "SNAP" and one as probable frontotemporal lobar degeneration. All A- (N)- cases in the probable AD group had less than 4 years of formal education and lower socioeconomic status (SES). CONCLUSION The PET-based staging system unveiled significant A(N) differences between AD and the other groups, whereas aMCI and controls had different (N) staging, explaining the cognitive impairment in aMCI. [18F]FDG-PET could be used beyond simple (N) staging, since it provided alternative hypotheses to cases with clinical-biomarker "mismatches." An AD hypometabolic pattern correlated with amyloid positivity. Low education and SES were related to dementia in the absence of biomarker changes.
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Affiliation(s)
- Artur Martins Coutinho
- Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil. .,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil. .,Centro de Medicina Nuclear do Instituto de Radiologia, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, 2° andar, Rua Doutor Ovídio Pires de Campos, 872, Cerqueira Cesar, São Paulo, SP, Brazil.
| | - Geraldo F Busatto
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Psychiatric Neuroimaging (LIM 21), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Fábio Henrique de Gobbi Porto
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Psychiatric Neuroimaging (LIM 21), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Daniele de Paula Faria
- Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Carla Rachel Ono
- Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Centro de Medicina Nuclear do Instituto de Radiologia, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, 2° andar, Rua Doutor Ovídio Pires de Campos, 872, Cerqueira Cesar, São Paulo, SP, Brazil
| | - Alexandre Teles Garcez
- Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Paula Squarzoni
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Psychiatric Neuroimaging (LIM 21), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Fábio Luiz de Souza Duran
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Psychiatric Neuroimaging (LIM 21), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Maira Okada de Oliveira
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Eduardo Sturzeneker Tres
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Orestes Vicente Forlenza
- Laboratory of Neuroscience (LIM 27), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Ricardo Nitrini
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Carlos Alberto Buchpiguel
- Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Centro de Medicina Nuclear do Instituto de Radiologia, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, 2° andar, Rua Doutor Ovídio Pires de Campos, 872, Cerqueira Cesar, São Paulo, SP, Brazil
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Illán-Gala I, Pegueroles J, Montal V, Alcolea D, Vilaplana E, Bejanin A, Borrego-Écija S, Sampedro F, Subirana A, Sánchez-Saudinós MB, Rojas-García R, Vanderstichele H, Blesa R, Clarimón J, Antonell A, Lladó A, Sánchez-Valle R, Fortea J, Lleó A. APP-derived peptides reflect neurodegeneration in frontotemporal dementia. Ann Clin Transl Neurol 2019; 6:2518-2530. [PMID: 31789459 PMCID: PMC6917306 DOI: 10.1002/acn3.50948] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 10/25/2019] [Indexed: 12/12/2022] Open
Abstract
Objective We aimed to investigate the relationship between cerebrospinal fluid levels (CSF) of amyloid precursor protein (APP)‐derived peptides related to the amyloidogenic pathway, cortical thickness, neuropsychological performance, and cortical gene expression profiles in frontotemporal lobar degeneration (FTLD)‐related syndromes, Alzheimer’s disease (AD), and healthy controls. Methods We included 214 participants with CSF available recruited at two centers: 93 with FTLD‐related syndromes, 57 patients with AD, and 64 healthy controls. CSF levels of amyloid β (Aβ)1‐42, Aβ1‐40, Aβ1‐38, and soluble β fragment of APP (sAPPβ) were centrally analyzed. We compared CSF levels of APP‐derived peptides between groups and, we studied the correlation between CSF biomarkers, cortical thickness, and domain‐specific cognitive composites in each group. Then, we explored the relationship between cortical thickness, CSF levels of APP‐derived peptides, and regional gene expression profile using a brain‐wide regional gene expression data in combination with gene set enrichment analysis. Results The CSF levels of Aβ1‐40, Aβ1‐38, and sAPPβ were lower in the FTLD‐related syndromes group than in the AD and healthy controls group. CSF levels of all APP‐derived peptides showed a positive correlation with cortical thickness and the executive cognitive composite in the FTLD‐related syndromes group but not in the healthy control or AD groups. In the cortical regions where we observed a significant association between cortical thickness and CSF levels of APP‐derived peptides, we found a reduced expression of genes related to synaptic function. Interpretation APP‐derived peptides in CSF may reflect FTLD‐related neurodegeneration. This observation has important implications as Aβ1‐42 levels are considered an indirect biomarker of cerebral amyloidosis.
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Affiliation(s)
- Ignacio Illán-Gala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Pegueroles
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Eduard Vilaplana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alexandre Bejanin
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Frederic Sampedro
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Andrea Subirana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - María-Belén Sánchez-Saudinós
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ricard Rojas-García
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Rafael Blesa
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Clarimón
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain.,Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
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Alcolea D, Clarimón J, Carmona-Iragui M, Illán-Gala I, Morenas-Rodríguez E, Barroeta I, Ribosa-Nogué R, Sala I, Sánchez-Saudinós MB, Videla L, Subirana A, Benejam B, Valldeneu S, Fernández S, Estellés T, Altuna M, Santos-Santos M, García-Losada L, Bejanin A, Pegueroles J, Montal V, Vilaplana E, Belbin O, Dols-Icardo O, Sirisi S, Querol-Vilaseca M, Cervera-Carles L, Muñoz L, Núñez R, Torres S, Camacho MV, Carrió I, Giménez S, Delaby C, Rojas-Garcia R, Turon-Sans J, Pagonabarraga J, Jiménez A, Blesa R, Fortea J, Lleó A. The Sant Pau Initiative on Neurodegeneration (SPIN) cohort: A data set for biomarker discovery and validation in neurodegenerative disorders. Alzheimers Dement (N Y) 2019; 5:597-609. [PMID: 31650016 PMCID: PMC6804606 DOI: 10.1016/j.trci.2019.09.005] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction The SPIN (Sant Pau Initiative on Neurodegeneration) cohort is a multimodal biomarker platform designed for neurodegenerative disease research following an integrative approach. Methods Participants of the SPIN cohort provide informed consent to donate blood and cerebrospinal fluid samples, receive detailed neurological and neuropsychological evaluations, and undergo a structural 3T brain MRI scan. A subset also undergoes other functional or imaging studies (video-polysomnogram, 18F-fluorodeoxyglucose PET, amyloid PET, Tau PET). Participants are followed annually for a minimum of 4 years, with repeated cerebrospinal fluid collection and imaging studies performed every other year, and brain donation is encouraged. Results The integration of clinical, neuropsychological, genetic, biochemical, imaging, and neuropathological information and the harmonization of protocols under the same umbrella allows the discovery and validation of key biomarkers across several neurodegenerative diseases. Discussion We describe our particular 10-year experience and how different research projects were unified under an umbrella biomarker program, which might be of help to other research teams pursuing similar approaches. The SPIN cohort is a multimodal biomarker program for research in neurodegeneration. We describe how research projects were unified under an umbrella biomarker program. Integrating clinical and biological data allows discovery and validation of markers. As a clinical group, we keep the SPIN cohort focused in patient-oriented research.
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Affiliation(s)
- Daniel Alcolea
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Jordi Clarimón
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - María Carmona-Iragui
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Ignacio Illán-Gala
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Estrella Morenas-Rodríguez
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Isabel Barroeta
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Roser Ribosa-Nogué
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Isabel Sala
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - M Belén Sánchez-Saudinós
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Laura Videla
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Andrea Subirana
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Bessy Benejam
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Sílvia Valldeneu
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Susana Fernández
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Teresa Estellés
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Miren Altuna
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Miguel Santos-Santos
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Lídia García-Losada
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Alexandre Bejanin
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Jordi Pegueroles
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Víctor Montal
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Eduard Vilaplana
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Olivia Belbin
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Oriol Dols-Icardo
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Sònia Sirisi
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Marta Querol-Vilaseca
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Laura Cervera-Carles
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Laia Muñoz
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Raúl Núñez
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Soraya Torres
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - M Valle Camacho
- Nuclear Medicine Department, Institut d'Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ignasi Carrió
- Nuclear Medicine Department, Institut d'Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sandra Giménez
- Respiratory Department, Multidisciplinary Sleep Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain
| | - Constance Delaby
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Université de Montpellier, CHU de Montpellier, Laboratoire de Biochimie-Protéomique clinique, INSERM U1183, Montpellier, France
| | - Ricard Rojas-Garcia
- Department of Neurology, Neuromuscular Diseases Unit, MND Clinic, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Raras, Ciberer, Spain
| | - Janina Turon-Sans
- Department of Neurology, Neuromuscular Diseases Unit, MND Clinic, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Raras, Ciberer, Spain
| | - Javier Pagonabarraga
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Department of Neurology, Movement Disorders Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain
| | - Amanda Jiménez
- Endocrinology and Diabetes Department, Obesity Unit, Hospital Clinic de Barcelona - IDIBAPS, Barcelona, Spain
| | - Rafael Blesa
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
| | - Juan Fortea
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain.,Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Alberto Lleó
- Department of Neurology, Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - IIB Sant Pau, Barcelona, Spain.,Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, Ciberned, Spain
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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 Res Ther 2019; 11:78. [PMID: 31511058 PMCID: PMC6739952 DOI: 10.1186/s13195-019-0532-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Palmqvist S, Janelidze S, Stomrud E, Zetterberg H, Karl J, Zink K, Bittner T, Mattsson N, Eichenlaub U, Blennow K, Hansson O. Performance of Fully Automated Plasma Assays as Screening Tests for Alzheimer Disease-Related β-Amyloid Status. JAMA Neurol 2019; 76:1060-1069. [PMID: 31233127 PMCID: PMC6593637 DOI: 10.1001/jamaneurol.2019.1632] [Citation(s) in RCA: 250] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Accurate blood-based biomarkers for Alzheimer disease (AD) might improve the diagnostic accuracy in primary care, referrals to memory clinics, and screenings for AD trials. Objective To examine the accuracy of plasma β-amyloid (Aβ) and tau measured using fully automated assays together with other blood-based biomarkers to detect cerebral Aβ. Design, Setting, and Participants Two prospective, cross-sectional, multicenter studies. Study participants were consecutively enrolled between July 6, 2009, and February 11, 2015 (cohort 1), and between January 29, 2000, and October 11, 2006 (cohort 2). Data were analyzed in 2018. The first cohort comprised 842 participants (513 cognitively unimpaired [CU], 265 with mild cognitive impairment [MCI], and 64 with AD dementia) from the Swedish BioFINDER study. The validation cohort comprised 237 participants (34 CU, 109 MCI, and 94 AD dementia) from a German biomarker study. Main Outcome and Measures The cerebrospinal fluid (CSF) Aβ42/Aβ40 ratio was used as the reference standard for brain Aβ status. Plasma Aβ42, Aβ40 and tau were measured using Elecsys immunoassays (Roche Diagnostics) and examined as predictors of Aβ status in logistic regression models in cohort 1 and replicated in cohort 2. Plasma neurofilament light chain (NFL) and heavy chain (NFH) and APOE genotype were also examined in cohort 1. Results The mean (SD) age of the 842 participants in cohort 1 was 72 (5.6) years, with a range of 59 to 88 years, and 446 (52.5%) were female. For the 237 in cohort 2, mean (SD) age was 66 (10) years with a range of 23 to 85 years, and 120 (50.6%) were female. In cohort 1, plasma Aβ42 and Aβ40 predicted Aβ status with an area under the receiver operating characteristic curve (AUC) of 0.80 (95% CI, 0.77-0.83). When adding APOE, the AUC increased significantly to 0.85 (95% CI, 0.82-0.88). Slight improvements were seen when adding plasma tau (AUC, 0.86; 95% CI, 0.83-0.88) or tau and NFL (AUC, 0.87; 95% CI, 0.84-0.89) to Aβ42, Aβ40 and APOE. The results were similar in CU and cognitively impaired participants, and in younger and older participants. Applying the plasma Aβ42 and Aβ40 model from cohort 1 in cohort 2 resulted in slightly higher AUC (0.86; 95% CI, 0.81-0.91), but plasma tau did not contribute. Using plasma Aβ42, Aβ40, and APOE in an AD trial screening scenario reduced positron emission tomography costs up to 30% to 50% depending on cutoff. Conclusions and Relevance Plasma Aβ42 and Aβ40 measured using Elecsys immunoassays predict Aβ status in all stages of AD with similar accuracy in a validation cohort. Their accuracy can be further increased by analyzing APOE genotype. Potential future applications of these blood tests include prescreening of Aβ positivity in clinical AD trials to lower the costs and number of positron emission tomography scans or lumbar punctures.
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Affiliation(s)
- Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom.,UK Dementia Research Institute at UCL, London, United Kingdom
| | | | | | - Tobias Bittner
- Genentech, a Member of the Roche Group, Basel, Switzerland
| | - Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Malmö, Sweden
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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50
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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: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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