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A Multichannel Fluorescent Tongue for Amyloid- β Aggregates Detection. Int J Mol Sci 2022; 23:ijms232314562. [PMID: 36498895 PMCID: PMC9739152 DOI: 10.3390/ijms232314562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/11/2022] [Accepted: 11/21/2022] [Indexed: 11/24/2022] Open
Abstract
Attention has been paid to the early diagnosis of Alzheimer's disease, due to the maximum benefit acquired from the early-stage intervention and treatment. However, the sensing techniques primarily depended upon for neuroimaging and immunological assays for the detection of AD biomarkers are expensive, time-consuming and instrument dependent. Here, we developed a multichannel fluorescent tongue consisting of four fluorescent dyes and GO through electrostatic and π-π interaction. The array distinguished multiple aggregation states of 1 µM Aβ40/Aβ42 with 100% prediction accuracy via 10-channel signal outputs, illustrating the rationality of the array design. Screening vital sensor elements for the simplified sensor array and the optimization of sensing system was achieved by machine learning algorithms. Moreover, our sensing tongue was able to detect the aggregation states of Aβ40/Aβ42 in serum, demonstrating the great potential of multichannel array in diagnosing the Alzheimer's diseases.
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Chen YH, Lin RR, Huang HF, Xue YY, Tao QQ. Microglial Activation, Tau Pathology, and Neurodegeneration Biomarkers Predict Longitudinal Cognitive Decline in Alzheimer's Disease Continuum. Front Aging Neurosci 2022; 14:848180. [PMID: 35847667 PMCID: PMC9280990 DOI: 10.3389/fnagi.2022.848180] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 05/12/2022] [Indexed: 01/02/2023] Open
Abstract
Purpose Biomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Patients and Methods A total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline. Results Baseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline. Conclusion Our study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.
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Affiliation(s)
- Yi-He Chen
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Rong-Rong Lin
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui-Feng Huang
- Department of Neurology, Lishui Hospital, Zhejiang University School of Medicine, Lishui, China
| | - Yan-Yan Xue
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | - Qing-Qing Tao
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
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3
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Leuzy A, Smith R, Cullen NC, Strandberg O, Vogel JW, Binette AP, Borroni E, Janelidze S, Ohlsson T, Jögi J, Ossenkoppele R, Palmqvist S, Mattsson-Carlgren N, Klein G, Stomrud E, Hansson O. Biomarker-Based Prediction of Longitudinal Tau Positron Emission Tomography in Alzheimer Disease. JAMA Neurol 2021; 79:149-158. [PMID: 34928318 PMCID: PMC8689441 DOI: 10.1001/jamaneurol.2021.4654] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Question Which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease? Findings In this cohort study of 343 participants including amyloid-β–positive individuals who were cognitively unimpaired or had mild cognitive impairment, the largest annual increase in [18F]RO948 tau positron emission tomography (PET) was seen across the entorhinal cortex, hippocampus, and amygdala and in temporal cortical regions, respectively. In a power analysis, plasma phosphorylated tau217 with tau PET at baseline in stage I and II, respectively, resulted in sample size reductions. Meaning In trials using tau PET as a main outcome, plasma phosphorylated tau217 with tau PET may prove optimal for enrichment in both preclinical and prodromal Alzheimer disease. Importance There is currently no consensus as to which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease (AD). Objective To describe longitudinal [18F]RO948 tau positron emission tomography (PET) findings across the clinical continuum of AD and determine which biomarker combinations showed the strongest associations with longitudinal tau PET and best optimized clinical trial enrichment. Design, Setting, and Participants This longitudinal cohort study consecutively enrolled amyloid-β (Aβ)–negative cognitively unimpaired (CU) participants, Aβ-positive CU individuals, Aβ-positive individuals with mild cognitive impairment (MCI), and individuals with AD dementia between September 2017 and November 2020 from the Swedish BioFINDER-2 (discovery cohort) and BioFINDER-1 (validation cohort) studies. Exposures Baseline plasma and cerebrospinal fluid Aβ42/Aβ40, tau phosphorylated at threonine-217 (p-tau217), p-tau181 and neurofilament light, magnetic resonance imaging, amyloid PET ([18F]flutemetamol), and tau PET ([18F]RO948 in the BioFINDER-2 study; [18F]flortaucipir in the BioFINDER-1 study). Main Outcomes and Measures Baseline tau PET standardized uptake value ratio (SUVR) and annual percent change in tau PET SUVR across regions of interest derived using a data-driven approach combining clustering and event-based modeling. Regression models were used to examine associations between individual biomarkers and longitudinal tau PET and to identify which combinations best predicted longitudinal tau PET. These combinations were then entered in a power analysis to examine how their use as an enrichment strategy would affect sample size in a simulated clinical trial. Results Of 343 participants, the mean (SD) age was 72.56 (7.24) years, and 157 (51.1%) were female. The clustering/event-based modeling–based approach identified 5 regions of interest (stages). In Aβ-positive CU individuals, the largest annual increase in tau PET SUVR was seen in stage I (entorhinal cortex, hippocampus, and amygdala; 4.04% [95% CI, 2.67%-5.32%]). In Aβ-positive individuals with MCI and with AD dementia, the greatest increases were seen in stages II (temporal cortical regions; 4.45% [95% CI, 3.41%-5.49%]) and IV (certain frontal regions; 5.22% [95% CI, 3.95%-6.49%]), respectively. In Aβ-negative CU individuals and those with MCI, modest change was seen in stage I (1.38% [95% CI, 0.78%-1.99%] and 1.80% [95% CI, 0.76%-2.84%], respectively). When looking at individual predictors and longitudinal tau PET in the stages that showed most change, plasma p-tau217 (R2 = 0.27, P < .005), tau PET (stage I baseline SUVR; R2 = 0.13, P < .05) and amyloid PET (R2 = 0.10, P < .05) were significantly associated with longitudinal tau PET in stage I in Aβ-positive CU individuals. In Aβ-positive individuals with MCI, plasma p-tau217 (R2 = 0.24, P < .005) and tau PET (stage II baseline SUVR; R2 = 0.44, P < .001) were significantly associated with longitudinal tau PET in stage II. Findings were replicated in BioFINDER-1 using longitudinal [18F]flortaucipir. For the power analysis component, plasma p-tau217 with tau PET resulted in sample size reductions of 43% (95% CI, 34%-46%; P < .005) in Aβ-positive CU individuals and of 68% (95% CI, 61%-73%; P < .001) in Aβ-positive individuals with MCI. Conclusions and Relevance In trials using tau PET as the outcome, plasma p-tau217 with tau PET may prove optimal for enrichment in preclinical and prodromal AD. However, plasma p-tau217 was most important in preclinical AD, while tau PET was more important in prodromal AD.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Jacob W Vogel
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia.,Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Tomas Ohlsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
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Verberk IMW, Misdorp EO, Koelewijn J, Ball AJ, Blennow K, Dage JL, Fandos N, Hansson O, Hirtz C, Janelidze S, Kang S, Kirmess K, Kindermans J, Lee R, Meyer MR, Shan D, Shaw LM, Waligorska T, West T, Zetterberg H, Edelmayer RM, Teunissen CE. Characterization of pre-analytical sample handling effects on a panel of Alzheimer's disease-related blood-based biomarkers: Results from the Standardization of Alzheimer's Blood Biomarkers (SABB) working group. Alzheimers Dement 2021; 18:1484-1497. [PMID: 34845818 PMCID: PMC9148379 DOI: 10.1002/alz.12510] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 09/10/2021] [Accepted: 09/15/2021] [Indexed: 12/11/2022]
Abstract
Introduction Pre‐analytical sample handling might affect the results of Alzheimer's disease blood‐based biomarkers. We empirically tested variations of common blood collection and handling procedures. Methods We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze–thawing. We measured amyloid beta (Aβ)42 and 40 peptides with six assays, and Aβ oligomerization‐tendency (OAβ), amyloid precursor protein (APP)699‐711, glial fibrillary acidic protein (GFAP), neurofilament light (NfL), total tau (t‐tau), and phosphorylated tau181. Results Collection tube type resulted in different values of all assessed markers. Delayed plasma centrifugation and storage affected Aβ and t‐tau; t‐tau was additionally affected by centrifugation temperature. The other markers were resistant to handling variations. Discussion We constructed a standardized operating procedure for plasma handling, to facilitate introduction of blood‐based biomarkers into the research and clinical settings.
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Affiliation(s)
- Inge M W Verberk
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Els O Misdorp
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Jannet Koelewijn
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Andrew J Ball
- Quanterix Corporation, Billerica, Massachusetts, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, The Salhgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Christophe Hirtz
- IRMB-LBPC/PPC, INM, Univ Montpellier, CHU Montpellier, INSERM CNRS, Montpellier, France
| | | | | | | | - Jana Kindermans
- IRMB-LBPC/PPC, INM, Univ Montpellier, CHU Montpellier, INSERM CNRS, Montpellier, France
| | - Ryan Lee
- PeopleBio, Seongnam, South Korea
| | | | - Dandan Shan
- Quanterix Corporation, Billerica, Massachusetts, USA
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Teresa Waligorska
- Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Tim West
- C2N Diagnostics, St. Louis, Missouri, USA
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, The Salhgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,UK Dementia Research Institute at UCL, London, UK.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | | | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
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5
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Park S, Kim Y. Bias-generating factors in biofluid amyloid-β measurements for Alzheimer's disease diagnosis. Biomed Eng Lett 2021; 11:287-295. [PMID: 34616582 DOI: 10.1007/s13534-021-00201-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/05/2021] [Accepted: 08/08/2021] [Indexed: 01/03/2023] Open
Abstract
Alzheimer's disease (AD) is the most prevalent cause of dementia worldwide, yet the dearth of readily accessible diagnostic biomarkers is a substantial hindrance towards progressing to effective preventive and therapeutic approaches. Due to a long delay between cerebral amyloid-β (Aβ) accumulation and the onset of cognitive impairments, biomarkers that reflect Aβ pathology and enable routine screening for disease progression are of urgent need for application in the clinical diagnosis of AD. According to accumulating evidences, cerebrospinal fluid (CSF) and plasma offer windows to the brain as they allow monitoring of biochemical changes in the brain. Considering the high availability and accuracy in depicting Aβ deposition in the brain, Aβ levels in CSF and plasma are regarded as promising fluid biomarkers for the diagnosis of AD patients at an early stage. However, clinical data with intra- and interindividual variations in the concentrations of CSF and plasma Aβ implicate the need to reevaluate current Aβ detection methods and establish a standardized operating procedure. Therefore, this review introduces three bias-generating factors in biofluid Aβ measurement that may hamper the accurate Aβ quantification and how such complications can be overcome for the widespread implementation of fluid Aβ detection in clinical practice.
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Affiliation(s)
- Sohui Park
- Department of Pharmacy, Department of Integrative Biotechnology and Translational Medicine, and Yonsei Institute of Pharmaceutical Sciences, College of Pharmacy, Yonsei University, Incheon, 21983 Republic of Korea
| | - YoungSoo Kim
- Department of Pharmacy, Department of Integrative Biotechnology and Translational Medicine, and Yonsei Institute of Pharmaceutical Sciences, College of Pharmacy, Yonsei University, Incheon, 21983 Republic of Korea
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Feinkohl I, Schipke CG, Kruppa J, Menne F, Winterer G, Pischon T, Peters O. Plasma Amyloid Concentration in Alzheimer's Disease: Performance of a High-Throughput Amyloid Assay in Distinguishing Alzheimer's Disease Cases from Controls. J Alzheimers Dis 2021; 74:1285-1294. [PMID: 32176645 PMCID: PMC7242850 DOI: 10.3233/jad-200046] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Background: Collection of cerebrospinal fluid (CSF) for measurement of amyloid-β (Aβ) species is a gold standard in Alzheimer’s disease (AD) diagnosis, but has risks. Thus, establishing a low-risk blood Aβ test with high AD sensitivity and specificity is of outmost interest. Objective: We evaluated the ability of a commercially available plasma Aβ assay to distinguish AD patients from biomarker-healthy controls. Method: In a case-control design, we examined plasma samples from 44 AD patients (A + N+) and 49 controls (A–N–) from a memory clinic. AD was diagnosed using a combination of neuropsychological examination, CSF biomarker analysis and brain imaging. Total Aβ40 and total Aβ42 in plasma were measured through enzyme-linked immunosorbent assay (ELISA) technology using ABtest40 and ABtest42 test kits (Araclon Biotech Ltd.). Receiver operating characteristic (ROC) analyses with outcome AD were performed, and sensitivity and specificity were calculated. Results: Plasma Aβ42/40 was weakly positively correlated with CSF Aβ42/40 (Spearman’s rho 0.22; p = 0.037). Plasma Aβ42/40 alone was not able to statistically significantly distinguish between AD patients and controls (AUC 0.58; 95% CI 0.46, 0.70). At a cut-point of 0.076 maximizing sensitivity and specificity, plasma Aβ42/40 had a sensitivity of 61.2% and a specificity of 63.6%. Conclusion: In this sample, the high-throughput blood Aβ assay was not able to distinguish well between AD patients and controls. Whether or not the assay may be useful in large-scale epidemiological settings remains to be seen.
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Affiliation(s)
- Insa Feinkohl
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany
| | - Carola G Schipke
- Berlin Institute of Health (BIH), Berlin, Germany.,Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Experimental & Clinical Research Center (ECRC), Berlin, Germany
| | - Jochen Kruppa
- Berlin Institute of Health (BIH), Berlin, Germany.,Institut für Biometrie und Klinische Epidemiologie, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany
| | - Felix Menne
- Berlin Institute of Health (BIH), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany
| | - Georg Winterer
- Berlin Institute of Health (BIH), Berlin, Germany.,Pharmaimage Biomarker Solutions GmbH, Berlin, Germany.,Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany
| | - Tobias Pischon
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.,Berlin Institute of Health (BIH), Berlin, Germany.,Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany.,MDC/BIH Biobank, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), and Berlin Institute of Health (BIH), Berlin, Germany
| | - Oliver Peters
- Berlin Institute of Health (BIH), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health (BIH), Berlin, Germany
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7
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Janeiro MH, Ardanaz CG, Sola-Sevilla N, Dong J, Cortés-Erice M, Solas M, Puerta E, Ramírez MJ. Biomarkers in Alzheimer's disease. ADVANCES IN LABORATORY MEDICINE 2021; 2:27-50. [PMID: 37359199 PMCID: PMC10197496 DOI: 10.1515/almed-2020-0090] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 10/19/2020] [Indexed: 06/28/2023]
Abstract
Background Alzheimer's disease (AD) is a progressive neurodegenerative disease. AD is the main cause of dementia worldwide and aging is the main risk factor for developing the illness. AD classical diagnostic criteria rely on clinical data. However, the development of a biological definition of AD using biomarkers that reflect the underling neuropathology is needed. Content The aim of this review is to describe the main outcomes when measuring classical and novel biomarkers in biological fluids or neuroimaging. Summary Nowadays, there are three classical biomarkers for the diagnosis of AD: Aβ42, t-Tau and p-Tau. The diagnostic use of cerebrospinal fluid biomarkers is limited due to invasive collection by lumbar puncture with potential side effects. Plasma/serum measurements are the gold standard in clinics, because they are minimally invasive and, in consequence, easily collected and processed. The two main proteins implicated in the pathological process, Aβ and Tau, can be visualized using neuroimaging techniques, such as positron emission tomography. Outlook As it is currently accepted that AD starts decades before clinical symptoms could be diagnosed, the opportunity to detect biological alterations prior to clinical symptoms would allow early diagnosis or even perhaps change treatment possibilities.
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Affiliation(s)
- Manuel H. Janeiro
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - Carlos G. Ardanaz
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - Noemí Sola-Sevilla
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - Jinya Dong
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - María Cortés-Erice
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - Maite Solas
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - Elena Puerta
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
| | - María J. Ramírez
- Department of Pharmacology and Toxicology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
- IDISNA, Navarra’s Health Research Institute, Pamplona, Spain
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8
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Stylianaki I, Polizopoulou ZS, Theodoridis A, Koutouzidou G, Baka R, Papaioannou NG. Amyloid-beta plasma and cerebrospinal fluid biomarkers in aged dogs with cognitive dysfunction syndrome. J Vet Intern Med 2020; 34:1532-1540. [PMID: 32557873 PMCID: PMC7379053 DOI: 10.1111/jvim.15812] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 05/02/2020] [Accepted: 05/08/2020] [Indexed: 01/03/2023] Open
Abstract
Background Cognitive dysfunction syndrome (CDS) is a common progressive neurodegenerative disease that is poorly defined. Specific multitargeted protocols do not exist for setting the diagnosis and the prognosis of the syndrome. Hypothesis/Objectives To quantify Aβ42 and Aβ40 peptides in blood and cerebrospinal fluid (CSF) and to investigate their contribution to CCDS. Animals A total of 61 dogs from a hospital population. Methods Case‐control study. Six young (YG: 0‐4 years old), 8 middle‐aged (4‐8 years old), 17 cognitively unimpaired and aged (CU: 8‐20 years old), and 30 cognitively impaired and aged (CI: 8‐17 years). From the CI group, 10 dogs exhibited mild impairment (CI‐MCI) and 20 exhibited severe impairment (CI‐SCI). Cognitive status was assessed using a validated owner‐based questionnaire. Direct and indirect Aβ markers were determined in plasma fractions (total‐TP, free‐FP, bound to plasma components‐CP) and CSF using commercial ELISA assays (AΒtest, Araclon Biotech). Results TPAβ42/40 facilitated discrimination between CI‐MCI and CU aged dogs with area under curve ≥ 0.79. CSFAβ42 levels were higher (P = .09) in CU (1.25 ± 0.28 ng/mL) than in MCI (1.04 ± 0.32 ng/mL) dogs. CSF Aβ42 levels were correlated with the CP fragment (CPAβ40: P = .02, CPAβ42: P = .02). CPAβ42 was higher in the CI‐MCI (23.03 ± 11.79 pg/μL) group compared to the other aged dogs (CU: 10.42 ± 7.18 pg/μL, P = .02, SCI: 11.40 ± 12.98 pg/μL, P = .26). Conclusion and Clinical Importance The Aβ should be determined in all of the 3 plasma fractions (TP, FP, CP). In the clinical approach, TPAβ42/40 could be used as an efficient preselection tool for the aged canine population targeting dogs with mild cognitive impairment.
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Affiliation(s)
- Ioanna Stylianaki
- Department of Pathology, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Zoe S Polizopoulou
- Diagnostic Laboratory, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Alexandros Theodoridis
- Laboratory of Animal Production Economics, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Georgia Koutouzidou
- Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
| | - Rania Baka
- Diagnostic Laboratory, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Nikolaos G Papaioannou
- Department of Pathology, Faculty of Veterinary Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
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9
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Sung WH, Hung JT, Lu YJ, Cheng CM. Paper-Based Detection Device for Alzheimer's Disease-Detecting β-amyloid Peptides (1-42) in Human Plasma. Diagnostics (Basel) 2020; 10:E272. [PMID: 32365918 PMCID: PMC7277973 DOI: 10.3390/diagnostics10050272] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 04/24/2020] [Accepted: 04/28/2020] [Indexed: 12/19/2022] Open
Abstract
The diagnosis of Alzheimer's disease (AD) is frequently missed or delayed in clinical practice. To remedy this situation, we developed a screening, paper-based (P-ELISA) platform to detect β-amyloid peptide 1-42 (Aβ42) and provide rapid results using a small volume, easily accessible plasma sample instead of cerebrospinal fluid. The protocol outlined herein only requires 3 μL of sample per well and a short operating time (i.e., only 90 min). The detection limit of Aβ42 is 63.04 pg/mL in a buffer system. This P-ELISA-based approach can be used for early, preclinical stage AD screening, including screening for amnestic mild cognitive impairment (MCI) due to AD. It may also be used for treatment and stage monitoring purposes. The implementation of this approach may provide tremendous impact for an afflicted population and may well prompt additional and expanded efforts in both academic and commercial communities.
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Affiliation(s)
- Wei-Hsuan Sung
- Chang Gung Memorial Hospital Linkou Medical Center, Taoyuan 33305, Taiwan;
- College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
| | - Jung-Tung Hung
- Institute of Stem Cell & Translational Cancer Research, Chang Gung Memorial Hospital Linkuo Medical Center, Taoyuan 33305, Taiwan;
| | - Yu-Jen Lu
- College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital Linkou Medical Center, Taoyuan 33305, Taiwan
| | - Chao-Min Cheng
- Institute of Biomedical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
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10
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Burnham SC, Fandos N, Fowler C, Pérez-Grijalba V, Dore V, Doecke JD, Shishegar R, Cox T, Fripp J, Rowe C, Sarasa M, Masters CL, Pesini P, Villemagne VL. Longitudinal evaluation of the natural history of amyloid-β in plasma and brain. Brain Commun 2020; 2:fcaa041. [PMID: 32954297 PMCID: PMC7425352 DOI: 10.1093/braincomms/fcaa041] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 02/26/2020] [Accepted: 03/04/2020] [Indexed: 01/03/2023] Open
Abstract
Plasma amyloid-β peptide concentration has recently been shown to have high accuracy to predict amyloid-β plaque burden in the brain. These amyloid-β plasma markers will allow wider screening of the population and simplify and reduce screening costs for therapeutic trials in Alzheimer's disease. The aim of this study was to determine how longitudinal changes in blood amyloid-β track with changes in brain amyloid-β. Australian Imaging, Biomarker and Lifestyle study participants with a minimum of two assessments were evaluated (111 cognitively normal, 7 mild cognitively impaired, 15 participants with Alzheimer's disease). Amyloid-β burden in the brain was evaluated through PET and was expressed in Centiloids. Total protein amyloid-β 42/40 plasma ratios were determined using ABtest® assays. We applied our method for obtaining natural history trajectories from short term data to measures of total protein amyloid-β 42/40 plasma ratios and PET amyloid-β. The natural history trajectory of total protein amyloid-β 42/40 plasma ratios appears to approximately mirror that of PET amyloid-β, with both spanning decades. Rates of change of 7.9% and 8.8%, were observed for total protein amyloid-β 42/40 plasma ratios and PET amyloid-β, respectively. The trajectory of plasma amyloid-β preceded that of brain amyloid-β by a median value of 6 years (significant at 88% confidence interval). These findings, showing the tight association between changes in plasma and brain amyloid-β, support the use of plasma total protein amyloid-β 42/40 plasma ratios as a surrogate marker of brain amyloid-β. Also, that plasma total protein amyloid-β 42/40 plasma ratios has potential utility in monitoring trial participants, and as an outcome measure.
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Affiliation(s)
- Samantha C Burnham
- The Australian e-Health Research Centre, CSIRO Health & Biosecurity, Parkville, VIC 3052, Australia
- Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA 6027, Australia
| | | | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC 3010, Australia
| | | | - Vincent Dore
- The Australian e-Health Research Centre, CSIRO Health & Biosecurity, Parkville, VIC 3052, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC 3084, Australia
| | - James D Doecke
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Herston 4029, Australia
| | - Rosita Shishegar
- The Australian e-Health Research Centre, CSIRO Health & Biosecurity, Parkville, VIC 3052, Australia
| | - Timothy Cox
- The Australian e-Health Research Centre, CSIRO Health & Biosecurity, Parkville, VIC 3052, Australia
| | - Jurgen Fripp
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Herston 4029, Australia
| | - Christopher Rowe
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC 3010, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC 3084, Australia
- Department of Medicine, The University of Melbourne, Parkville, VIC 3052, Australia
| | | | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC 3010, Australia
| | | | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC 3084, Australia
- Department of Medicine, The University of Melbourne, Parkville, VIC 3052, Australia
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11
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Doecke JD, Pérez-Grijalba V, Fandos N, Fowler C, Villemagne VL, Masters CL, Pesini P, Sarasa M. Total Aβ 42/Aβ 40 ratio in plasma predicts amyloid-PET status, independent of clinical AD diagnosis. Neurology 2020; 94:e1580-e1591. [PMID: 32179698 PMCID: PMC7251518 DOI: 10.1212/wnl.0000000000009240] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 10/24/2019] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To explore whether the plasma total β-amyloid (Aβ) Aβ42/Aβ40 ratio is a reliable predictor of the amyloid-PET status by exploring the association between these 2 variables in a subset of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging cohort. METHODS Taking plasma samples at 3 separate time points, month 18 (n = 176), month 36 (n = 169), and month 54 (n = 135), we assessed the total Aβ42/Aβ40 ratio in plasma (TP42/40) with regard to neocortical Aβ burden via PET standardized uptake value ratio (SUVR) and investigated both association with Aβ-PET status and correlation (and agreement) with SUVR. RESULTS The TP42/40 plasma ratio was significantly reduced in amyloid-PET-positive participants at all time points (p < 0.0001). Adjusting for covariates age, gender, APOE ε4 allele status, and clinical classification clearly affects the significance, with p values reduced and only comparisons at 54 months retaining significance (p = 0.006). Correlations with SUVR were similar across each time point, with Spearman ρ reaching -0.64 (p < 0.0001). Area under the curve values were highly reproducible over time points, with values ranging from 0.880 at 36 months to 0.913 at 54 months. In assessments of the healthy control group only, the same relationships were found. CONCLUSIONS The current study demonstrates reproducibility of the plasma assay to discriminate between amyloid-PET positive and negative over 3 time points, which can help to substantially reducing the screening rate of failure for clinical trials targeting preclinical or prodromal disease. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that plasma total Aβ42/Aβ40 ratio is associated with neocortical amyloid burden as measured by PET SUVR.
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Affiliation(s)
- James D Doecke
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Virginia Pérez-Grijalba
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Noelia Fandos
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Christopher Fowler
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Victor L Villemagne
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Colin L Masters
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Pedro Pesini
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia.
| | - Manuel Sarasa
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
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12
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Pérez-Grijalba V, Arbizu J, Romero J, Prieto E, Pesini P, Sarasa L, Guillen F, Monleón I, San-José I, Martínez-Lage P, Munuera J, Hernández I, Buendía M, Sotolongo-Grau O, Alegret M, Ruiz A, Tárraga L, Boada M, Sarasa M. Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study. Alzheimers Res Ther 2019; 11:96. [PMID: 31787105 PMCID: PMC6886187 DOI: 10.1186/s13195-019-0549-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/22/2019] [Indexed: 12/30/2022]
Abstract
BACKGROUND To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer's disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. METHODS We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. RESULTS Eighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779-0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden's cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913-0.100). CONCLUSIONS Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer's disease.
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Affiliation(s)
| | - Javier Arbizu
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | - Judith Romero
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Elena Prieto
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | - Pedro Pesini
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain.
| | - Leticia Sarasa
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Fernando Guillen
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | | | - Itziar San-José
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Pablo Martínez-Lage
- Center for Research and Advanced Therapies and Memory Clinic, Fundación CITA-Alzheimer, San Sebastián, Spain
| | - Josep Munuera
- Institut de recerca Sant Joan de Déu, Hospital Infantil Sant Joan de Déu, Barcelona, Spain
| | - Isabel Hernández
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Mar Buendía
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
| | - Montserrat Alegret
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Agustín Ruiz
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Lluis Tárraga
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Manuel Sarasa
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
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13
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Lopez OL, Klunk WE, Mathis CA, Snitz BE, Chang Y, Tracy RP, Kuller LH. Relationship of amyloid-β1-42 in blood and brain amyloid: Ginkgo Evaluation of Memory Study. Brain Commun 2019; 2:fcz038. [PMID: 31998865 PMCID: PMC6976616 DOI: 10.1093/braincomms/fcz038] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 10/24/2019] [Accepted: 11/25/2019] [Indexed: 12/13/2022] Open
Abstract
A blood test that predicts the extent of amyloid plaques in the brain and risk of Alzheimer's disease would have important benefits for the early identification of higher risk of dementia and Alzheimer's disease and the evaluation of new preventative therapies. The goal of this study was to determine whether plasma levels of amyloid-β1-42, 1-40 and the amyloid-β1-42/1-40 ratio among participants in the Pittsburgh centre of the Ginkgo Evaluation of Memory Study were related to the extent of brain fibrillar amyloid plaques measured in 2009 using Pittsburgh compound-B PET imaging, hippocampal volume, cortical thickness in the temporal lobe and white matter lesions. There were 194 participants who had Pittsburgh compound-B measurements in 2009 with the mean age of 85 years; 96% were white and 60% men. Pittsburgh compound-B positivity was defined as a standardized uptake value ratio of ≥1.57. Amyloid-β in blood was measured using a sandwich enzyme-linked immunosorbent assay developed by Eli Lilly and modified at the University of Vermont. All participants were nondemented as of 2008 at the time of study close out. The study sample included 160 with blood samples drawn in 2000-02 and 133 from 2009 and also had brain amyloid measured in 2009. All blood samples were analysed at the same time in 2009. Plasma amyloid-β1-42 was inversely related to the percent Pittsburgh compound-B positive (standardized uptake value ratio ≥1.57), β -0.04, P = 0.005. Practically all participants who were apolipoprotein-E4 positive at older ages were also Pittsburgh compound-B positive for fibrillar amyloid. Among apolipoprotein-E4-negative participants, quartiles of amyloid-β1-42 were inversely related to Pittsburgh compound-B positivity. In multiple regression models, plasma amyloid-β1-42 measured in 2000-02 or 2009 were significantly and inversely related to Pittsburgh compound-B positivity as was the amyloid-β1-42/1-40 ratio. There was a 4-fold increase in the odds ratio for the presence of Pittsburgh compound-B positivity in the brain in 2009 for the first quartile of amyloid-β1-42 as compared with the fourth quartile in the multiple logistic model. This is one of the first longitudinal studies to evaluate the relationship between amyloid-β1-42 in the blood and the extent of brain amyloid deposition measured by PET imaging using Pittsburgh compound-B. Our findings showed that remote and recent low plasma amyloid-β1-42 levels were inversely associated with brain amyloid deposition in cognitively normal individuals. However, changes in plasma amyloid-β1-42 over time (8 years) were small and not related to the amount of Pittsburgh compound-B.
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Affiliation(s)
- Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15261, USA.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Yuefang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15261, USA.,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
| | - Lewis H Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
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14
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Chatterjee P, Elmi M, Goozee K, Shah T, Sohrabi HR, Dias CB, Pedrini S, Shen K, Asih PR, Dave P, Taddei K, Vanderstichele H, Zetterberg H, Blennow K, Martins RN. Ultrasensitive Detection of Plasma Amyloid-β as a Biomarker for Cognitively Normal Elderly Individuals at Risk of Alzheimer’s Disease. J Alzheimers Dis 2019; 71:775-783. [DOI: 10.3233/jad-190533] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Pratishtha Chatterjee
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Mitra Elmi
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
| | - Kathryn Goozee
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
- KaRa Institute of Neurological Disease, Sydney, Macquarie Park, Australia
- Anglicare, Sydney, Castle Hill, NSW, Australia
- School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, WA, Australia
| | - Tejal Shah
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
- Australian Alzheimer’s Research Foundation, Nedlands, WA, Australia
| | - Hamid R. Sohrabi
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
- School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, WA, Australia
- Australian Alzheimer’s Research Foundation, Nedlands, WA, Australia
| | - Cintia B. Dias
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Biomedical Sciences & Pharmacy, University of Newcastle, Callaghan, NSW, Australia
| | - Steve Pedrini
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Kaikai Shen
- Australian eHealth Research Centre, CSIRO, Floreat, Australia
| | - Prita R. Asih
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
| | - Preeti Dave
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- Anglicare, Sydney, Castle Hill, NSW, Australia
- John Curtin School of Medical research, Canberra, Australia
| | - Kevin Taddei
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
- Australian Alzheimer’s Research Foundation, Nedlands, WA, Australia
| | | | - 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, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
| | - 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
| | - Ralph N. Martins
- Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, Australia
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
- KaRa Institute of Neurological Disease, Sydney, Macquarie Park, Australia
- School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, WA, Australia
- Australian Alzheimer’s Research Foundation, Nedlands, WA, Australia
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15
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Risacher SL, Fandos N, Romero J, Sherriff I, Pesini P, Saykin AJ, Apostolova LG. Plasma amyloid beta levels are associated with cerebral amyloid and tau deposition. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:510-519. [PMID: 31384662 PMCID: PMC6661419 DOI: 10.1016/j.dadm.2019.05.007] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction We investigated the relationship of plasma amyloid beta (Aβ) with cerebral deposition of Aβ and tau on positron emission tomography (PET). Methods Forty-four participants (18 cognitively normal older adults [CN], 10 mild cognitive impairment, 16 Alzheimer's disease [AD]) underwent amyloid PET and a blood draw. Free and total plasma Aβ40 and Aβ42 were assessed using a validated assay. Thirty-seven participants (17 CN, 8 mild cognitive impairment, 12 AD) also underwent a [18F]flortaucipir scan. Scans were preprocessed by standard techniques, and mean global and regional amyloid and tau values were extracted. Free Aβ42/Aβ40 (Aβ F42:F40) and total Aβ42/Aβ40 (Aβ T42:T40) were evaluated for differences by diagnosis and relation to PET Aβ positivity. Relationships between these measures and cerebral Aβ and tau on both regional and voxel-wise basis were also evaluated. Results Lower Aβ T42:T40 was associated with diagnosis and PET Aβ positivity. Lower plasma Aβ T42:T40 ratios predicted cerebral Aβ positivity, both across the full sample and in CN only. Finally, lower plasma Aβ T42:T40 ratios were associated with increased cortical Aβ and tau in AD-related regions on both regional and voxel-wise analyses. Discussion Plasma Aβ measures may be useful biomarkers for predicting cerebral Aβ and tau. Additional studies in larger samples are warranted.
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Affiliation(s)
- Shannon L Risacher
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | | | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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16
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Blood amyloid levels and risk of dementia in the Ginkgo Evaluation of Memory Study (GEMS): A longitudinal analysis. Alzheimers Dement 2019; 15:1029-1038. [PMID: 31255494 DOI: 10.1016/j.jalz.2019.04.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 04/01/2019] [Accepted: 04/10/2019] [Indexed: 12/22/2022]
Abstract
INTRODUCTION Both high or low plasma amyloid levels have been associated with risk of dementia in nondemented subjects. METHODS We examined baseline plasma β-amyloid (Aβ) levels in relationship to incident dementia during a period of 8.5 years in 2840 subjects age >75 years; 2381 were cognitively normal (CN) and 450 mild cognitive impairment. RESULTS Increased plasma Aβ1-40 and Aβ1-42 levels were associated with gender (women), age, low education, creatinine levels, history of stroke, and hypertension. CN participants who developed dementia had lower levels of Aβ1-42 and Aβ1-42/Aβ1-40 ratio compared with those who did not. Aβ levels did not predict dementia in mild cognitive impairment participants. DISCUSSION There was an inverse association between Aβ1-42 and Aβ1-42/Aβ1-40 ratio to risk of dementia in CN participants. Cerebral and cardiovascular disease and renal function are important determinants of increased Aβ levels and must be considered in evaluations of relationship of plasma Aβ and subsequent risk of dementia.
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Fernández-Eulate G, Alberro A, Muñoz-Culla M, Zulaica M, Zufiría M, Barandiarán M, Etxeberria I, Yanguas JJ, Gallardo MM, Soberón N, Lacosta AM, Pérez-Grijalba V, Canudas J, Fandos N, Pesini P, Sarasa M, Indakoetxea B, Moreno F, Vergara I, Otaegui D, Blasco M, López de Munain A. Blood Markers in Healthy-Aged Nonagenarians: A Combination of High Telomere Length and Low Amyloidβ Are Strongly Associated With Healthy Aging in the Oldest Old. Front Aging Neurosci 2018; 10:380. [PMID: 30546303 PMCID: PMC6280560 DOI: 10.3389/fnagi.2018.00380] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 10/31/2018] [Indexed: 12/22/2022] Open
Abstract
Many factors may converge in healthy aging in the oldest old, but their association and predictive power on healthy or functionally impaired aging has yet to be demonstrated. By detecting healthy aging and in turn, poor aging, we could take action to prevent chronic diseases associated with age. We conducted a pilot study comparing results of a set of markers (peripheral blood mononuclear cell or PBMC telomere length, circulating Aβ peptides, anti-Aβ antibodies, and ApoE status) previously associated with poor aging or cognitive deterioration, and their combinations, in a cohort of “neurologically healthy” (both motor and cognitive) nonagenarians (n = 20) and functionally impaired, institutionalized nonagenarians (n = 38) recruited between 2014 and 2015. We recruited 58 nonagenarians (41 women, 70.7%; mean age: 92.37 years in the neurologically healthy group vs. 94.13 years in the functionally impaired group). Healthy nonagenarians had significantly higher mean PBMC telomere lengths (mean = 7, p = 0.001), this being inversely correlated with functional impairment, and lower circulating Aβ40 (total in plasma fraction or TP and free in plasma fraction or FP), Aβ42 (TP and FP) and Aβ17 (FP) levels (FP40 131.35, p = 0.004; TP40 299.10, p = 0.007; FP42 6.29, p = 0.009; TP42 22.53, p = 0.019; FP17 1.32 p = 0.001; TP17 4.47, p = 0.3), after adjusting by age. Although healthy nonagenarians had higher anti-Aβ40 antibody levels (net adsorbed signal or NAS ± SD: 0.211 ± 0.107), the number of participants that pass the threshold (NAS > 3) to be considered as positive did not show such a strong association. There was no association with ApoE status. Additionally, we propose a “Composite Neurologically Healthy Aging Score” combining TP40 and mean PBMC telomere length, the strongest correlation of measured biomarkers with neurologically healthy status in nonagenarians (AUC = 0.904).
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Affiliation(s)
- Gorka Fernández-Eulate
- Department of Neurology, Donostia Universitary Hospital, San Sebastián, Spain.,Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Ainhoa Alberro
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Maider Muñoz-Culla
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Miren Zulaica
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Mónica Zufiría
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Myriam Barandiarán
- Department of Neurology, Donostia Universitary Hospital, San Sebastián, Spain.,Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Igone Etxeberria
- Department of Personality, Assessment, and Psychological Treatments, Faculty of Psychology, University of the Basque UPV/EHU, San Sebastián, Spain
| | | | - Maria Mercedes Gallardo
- Telomeres & Telomerase Group, Molecular Oncology Programme, Spanish National Cancer Research Center, Madrid, Spain
| | - Nora Soberón
- Telomeres & Telomerase Group, Molecular Oncology Programme, Spanish National Cancer Research Center, Madrid, Spain
| | | | | | | | | | | | | | - Begoña Indakoetxea
- Department of Neurology, Donostia Universitary Hospital, San Sebastián, Spain
| | - Fermin Moreno
- Department of Neurology, Donostia Universitary Hospital, San Sebastián, Spain
| | - Itziar Vergara
- Primary Health Area, Biodonostia Institute, San Sebastián, Spain.,Health Services Research on Chronic Patients Network, REDISSEC, Bilbao, Spain
| | - David Otaegui
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Maria Blasco
- Telomeres & Telomerase Group, Molecular Oncology Programme, Spanish National Cancer Research Center, Madrid, Spain
| | - Adolfo López de Munain
- Department of Neurology, Donostia Universitary Hospital, San Sebastián, Spain.,Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto Carlos III, Madrid, Spain.,Department of Neurosciences, University of the Basque Country, San Sebastián, Spain
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Lacosta AM, Insua D, Badi H, Pesini P, Sarasa M. Neurofibrillary Tangles of Aβx-40 in Alzheimer's Disease Brains. J Alzheimers Dis 2018; 58:661-667. [PMID: 28453491 DOI: 10.3233/jad-170163] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The two pathognomonic lesions in the brain of AD patients are senile plaques and intraneuronal neurofibrillary tangles (NFT). Previous studies have demonstrated that amyloid-β (Aβ) is a component of both senile plaques and NFTs, and have showed that intracellular accumulation of Aβ is toxic for cells and precedes the appearance of extracellular amyloid deposits. Here we report that there are numerous intraneuronal NFT and extraneuronal NFT immunoreactive for Aβx-40 in which there is no co-localization with tau staining suggesting the existence of two different neurodegenerating populations associated with the intracellular accumulation of either tau protein or Aβx-40 in AD.
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Plasma amyloid β 42/40 ratios as biomarkers for amyloid β cerebral deposition in cognitively normal individuals. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 8:179-187. [PMID: 28948206 PMCID: PMC5602863 DOI: 10.1016/j.dadm.2017.07.004] [Citation(s) in RCA: 98] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Plasma amyloid β (Aβ) peptides have been previously studied as candidate biomarkers to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. METHODS Free and total Aβ42/40 plasma ratios (FP42/40 and TP42/40, respectively) were determined using ABtest assays in cognitively normal subjects from the Australian Imaging, Biomarker and Lifestyle Flagship Study. This population was followed-up for 72 months and their cortical Aβ burden was assessed with positron emission tomography. RESULTS Cross-sectional and longitudinal analyses showed an inverse association of Aβ42/40 plasma ratios and cortical Aβ burden. Optimized as a screening tool, TP42/40 reached 81% positive predictive value of high cortical Aβ burden, which represents 110% increase over the population prevalence of cortical Aβ positivity. DISCUSSION These findings support the use of plasma Aβ42/40 ratios as surrogate biomarkers of cortical Aβ deposition and enrichment tools, reducing the number of subjects submitted to invasive tests and, consequently, recruitment costs in clinical trials targeting cognitively normal individuals.
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