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Kang JH, Korecka M, Lee EB, Cousins KAQ, Tropea TF, Chen-Plotkin AA, Irwin DJ, Wolk D, Brylska M, Wan Y, Shaw LM. Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology. Clin Chem 2023; 69:1247-1259. [PMID: 37725909 PMCID: PMC10895336 DOI: 10.1093/clinchem/hvad139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 07/07/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway. CONTENT Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers. SUMMARY CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.
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Affiliation(s)
- Ju Hee Kang
- Department of Pharmacology and Clinical Pharmacology, Research Center for Controlling Intercellular Communication, Inha University, Incheon, South Korea
| | - Magdalena Korecka
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Alice A Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Magdalena Brylska
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Yang Wan
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Wang ZB, Tan L, Gao PY, Ma YH, Fu Y, Sun Y, Yu JT. Associations of the A/T/N profiles in PET, CSF, and plasma biomarkers with Alzheimer's disease neuropathology at autopsy. Alzheimers Dement 2023; 19:4421-4435. [PMID: 37506291 DOI: 10.1002/alz.13413] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/03/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023]
Abstract
INTRODUCTION To examine the extent to which positron emission tomography (PET)-, cerebrospinal fluid (CSF)-, and plasma-related amyloid-β/tau/neurodegeneration (A/T/N) biomarkers are associated with Alzheimer's disease (AD) neuropathology at autopsy. METHODS A total of 100 participants who respectively underwent antemortem biomarker measurements and postmortem neuropathology were included in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We examined the associations of PET-, CSF-, and plasma-related A/T/N biomarkers in combinations or alone with AD neuropathological changes (ADNC). RESULTS PET- and CSF-related A/T/N biomarkers in combination showed high concordance with the ADNC stage and alone showed high accuracy in discriminating autopsy-confirmed AD. However, the plasma-related A/T/N biomarkers alone showed better discriminative performance only when combined with apolipoprotein E (APO)E ε4 genotype. DISCUSSION This study supports that PET- and CSF-related A/T/N profiles can be used to predict accurately the stages of AD neuropathology. For diagnostic settings, PET-, CSF-, and plasma-related A/T/N biomarkers are all useful diagnostic tools to detect the presence of AD neuropathology. HIGHLIGHTS PET- and CSF-related A/T/N biomarkers in combination can accurately predict the specific stages of AD neuropathology. PET- and CSF-related A/T/N biomarkers alone may serve as a precise diagnostic tool for detecting AD neuropathology at autopsy. Plasma-related A/T/N biomarkers may need combined risk factors when used as a diagnostic tool. Aβ PET and CSF p-tau181/Aβ42 were most consistent with Aβ pathology, while tau PET and CSF p-tau181/Aβ42 were most consistent with tau pathology.
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Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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Wang ZB, Tan L, Wang HF, Chen SD, Fu Y, Gao PY, Ma YH, Guo Y, Hou JH, Zhang DD, Yu JT. Differences between ante mortem Alzheimer's disease biomarkers in predicting neuropathology at autopsy. Alzheimers Dement 2023; 19:3613-3624. [PMID: 36840620 DOI: 10.1002/alz.12997] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION This study aimed to assess whether biomarkers related to amyloid, tau, and neurodegeneration can accurately predict Alzheimer's disease (AD) neuropathology at autopsy in early and late clinical stages. METHODS We included 100 participants who had ante mortem biomarker measurements and underwent post mortem neuropathological examination. Based on ante mortem clinical diagnosis, participants were divided into non-dementia and dementia, as early or late clinical stages. RESULTS Amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) amyloid beta (Aβ)42/phosphorylated tau (p-tau)181 showed excellent performance in differentiating autopsy-confirmed AD and predicting the risk of neuropathological changes in early and late clinical stages. However, CSF Aβ42 performed better in the early clinical stage, while CSF p-tau181, CSF t-tau, and plasma p-tau181 performed better in the late clinical stage. DISCUSSION Our findings provide important clinical information that, if using PET, CSF, and plasma biomarkers to detect AD pathology, researchers must consider their differential performances at different clinical stages of AD. HIGHLIGHTS Amyloid PET and CSF Aβ42/p-tau181 were the most promising candidate biomarkers for predicting AD pathology. CSF Aβ42 can serve as a candidate predictive biomarker in the early clinical stage of AD. CSF p-tau181, CSF t-tau, and plasma p-tau181 can serve as candidate predictive biomarkers in the late clinical stage of AD. Combining APOE ε4 genotypes can significantly improve the predictive accuracy of AD-related biomarkers for AD pathology.
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Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hui-Fu Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia-Hui Hou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Dan-Dan Zhang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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de Kort AM, Kuiperij HB, Jäkel L, Kersten I, Rasing I, van Etten ES, van Rooden S, van Osch MJP, Wermer MJH, Terwindt GM, Schreuder FHBM, Klijn CJM, Verbeek MM. Plasma amyloid beta 42 is a biomarker for patients with hereditary, but not sporadic, cerebral amyloid angiopathy. Alzheimers Res Ther 2023; 15:102. [PMID: 37270536 PMCID: PMC10239174 DOI: 10.1186/s13195-023-01245-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 05/18/2023] [Indexed: 06/05/2023]
Abstract
BACKGROUND The diagnosis of probable cerebral amyloid angiopathy (CAA) is currently mostly based on characteristics of brain MRI. Blood biomarkers would be a cost-effective, easily accessible diagnostic method that may complement diagnosis by MRI and aid in monitoring disease progression. We studied the diagnostic potential of plasma Aβ38, Aβ40, and Aβ42 in patients with hereditary Dutch-type CAA (D-CAA) and sporadic CAA (sCAA). METHODS All Aβ peptides were quantified in the plasma by immunoassays in a discovery cohort (11 patients with presymptomatic D-CAA and 24 patients with symptomatic D-CAA, and 16 and 24 matched controls, respectively) and an independent validation cohort (54 patients with D-CAA, 26 presymptomatic and 28 symptomatic, and 39 and 46 matched controls, respectively). In addition, peptides were quantified in the plasma in a group of 61 patients with sCAA and 42 matched controls. We compared Aβ peptide levels between patients and controls using linear regression adjusting for age and sex. RESULTS In the discovery cohort, we found significantly decreased levels of all Aβ peptides in patients with presymptomatic D-CAA (Aβ38: p < 0.001; Aβ40: p = 0.009; Aβ42: p < 0.001) and patients with symptomatic D-CAA (Aβ38: p < 0.001; Aβ40: p = 0.01; Aβ42: p < 0.001) compared with controls. In contrast, in the validation cohort, plasma Aβ38, Aβ40, and Aβ42 were similar in patients with presymptomatic D-CAA and controls (Aβ38: p = 0.18; Aβ40: p = 0.28; Aβ42: p = 0.63). In patients with symptomatic D-CAA and controls, plasma Aβ38 and Aβ40 were similar (Aβ38: p = 0.14; Aβ40: p = 0.38), whereas plasma Aβ42 was significantly decreased in patients with symptomatic D-CAA (p = 0.033). Plasma Aβ38, Aβ40, and Aβ42 levels were similar in patients with sCAA and controls (Aβ38: p = 0.092; Aβ40: p = 0.64. Aβ42: p = 0.68). CONCLUSIONS Plasma Aβ42 levels, but not plasma Aβ38 and Aβ40, may be used as a biomarker for patients with symptomatic D-CAA. In contrast, plasma Aβ38, Aβ40, and Aβ42 levels do not appear to be applicable as a biomarker in patients with sCAA.
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Affiliation(s)
- Anna M de Kort
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - H Bea Kuiperij
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - Lieke Jäkel
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - Iris Kersten
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - Ingeborg Rasing
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Ellis S van Etten
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sanneke van Rooden
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marieke J H Wermer
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Floris H B M Schreuder
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - Catharina J M Klijn
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands
| | - Marcel M Verbeek
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, P.O. Box 9101, Nijmegen, 6500 HB, The Netherlands.
- Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
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Mankhong S, Kim S, Lee S, Kwak HB, Park DH, Joa KL, Kang JH. Development of Alzheimer’s Disease Biomarkers: From CSF- to Blood-Based Biomarkers. Biomedicines 2022; 10:biomedicines10040850. [PMID: 35453600 PMCID: PMC9025524 DOI: 10.3390/biomedicines10040850] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/25/2022] [Accepted: 03/31/2022] [Indexed: 02/05/2023] Open
Abstract
In the 115 years since the discovery of Alzheimer’s disease (AD), our knowledge, diagnosis, and therapeutics have significantly improved. Biomarkers are the primary tools for clinical research, diagnostics, and therapeutic monitoring in clinical trials. They provide much insightful information, and while they are not clinically used routinely, they help us to understand the mechanisms of this disease. This review charts the journey of AD biomarker discovery and development from cerebrospinal fluid (CSF) amyloid-beta 1-42 (Aβ42), total tau (T-tau), and phosphorylated tau (p-tau) biomarkers and imaging technologies to the next generation of biomarkers. We also discuss advanced high-sensitivity assay platforms for CSF Aβ42, T-tau, p-tau, and blood analysis. The recently proposed Aβ deposition/tau biomarker/neurodegeneration or neuronal injury (ATN) scheme might facilitate the definition of the biological status underpinning AD and offer a common language among researchers across biochemical biomarkers and imaging. Moreover, we highlight blood-based biomarkers for AD that offer a scalable alternative to CSF biomarkers through cost-saving and reduced invasiveness, and may provide an understanding of disease initiation and development. We discuss different groups of blood-based biomarker candidates, their advantages and limitations, and paths forward, from identification and analysis to clinical validation. The development of valid blood-based biomarkers may facilitate the implementation of future AD therapeutics and diagnostics.
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Affiliation(s)
- Sakulrat Mankhong
- Department of Pharmacology, Research Center for Controlling Intercellular Communication, College of Medicine, Inha University, Incheon 22212, Korea; (S.M.); (S.K.)
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (H.-B.K.); (D.-H.P.)
| | - Sujin Kim
- Department of Pharmacology, Research Center for Controlling Intercellular Communication, College of Medicine, Inha University, Incheon 22212, Korea; (S.M.); (S.K.)
| | - Seongju Lee
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (H.-B.K.); (D.-H.P.)
- Department of Anatomy, College of Medicine, Inha University, Incheon 22212, Korea
| | - Hyo-Bum Kwak
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (H.-B.K.); (D.-H.P.)
- Department of Kinesiology, Inha University, Incheon 22212, Korea
| | - Dong-Ho Park
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (H.-B.K.); (D.-H.P.)
- Department of Kinesiology, Inha University, Incheon 22212, Korea
| | - Kyung-Lim Joa
- Department of Physical & Rehabilitation Medicine, College of Medicine, Inha University, Incheon 22212, Korea;
| | - Ju-Hee Kang
- Department of Pharmacology, Research Center for Controlling Intercellular Communication, College of Medicine, Inha University, Incheon 22212, Korea; (S.M.); (S.K.)
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (H.-B.K.); (D.-H.P.)
- Correspondence: ; Tel.: +82-32-860-9872
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Li TR, Yang Q, Hu X, Han Y. Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage. Curr Neuropharmacol 2022; 20:713-737. [PMID: 34030620 PMCID: PMC9878962 DOI: 10.2174/1570159x19666210524153901] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/27/2021] [Accepted: 05/08/2021] [Indexed: 11/22/2022] Open
Abstract
Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.
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Affiliation(s)
- Tao-Ran Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Qin Yang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Xiaochen Hu
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, 50924, Germany
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China;,Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China;,National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China;,School of Biomedical Engineering, Hainan University, Haikou, 570228, China;,Address correspondence to this author at the Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China; Tel: +86 13621011941; E-mail:
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Fully automated chemiluminescence enzyme immunoassays showing high correlation with immunoprecipitation mass spectrometry assays for β-amyloid (1-40) and (1-42) in plasma samples. Biochem Biophys Res Commun 2021; 576:22-26. [PMID: 34478915 DOI: 10.1016/j.bbrc.2021.08.066] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 08/16/2021] [Accepted: 08/23/2021] [Indexed: 11/24/2022]
Abstract
Blood based β-amyloid (Aβ) assays that can predict amyloid positivity in the brain are in high demand. Current studies that utilize immunoprecipitation mass spectrometry assay (IP-MS), which has high specificity for measuring analytes, have revealed that precise plasma Aβ assays have the potential to detect amyloid positivity in the brain. In this study, we developed plasma Aβ40 and Aβ42 immunoassays using a fully automated immunoassay platform that is used in routine clinical practice. Our assays showed high sensitivity (limit of quantification: 2.46 pg/mL [Aβ40] and 0.16 pg/mL [Aβ42]) and high reproducibility within-run (coefficients of variation [CVs]: <3.7% [Aβ40] and <2.0% [Aβ42]) and within-laboratory (CVs: <4.6% [Aβ40] and <5.3% [Aβ42]). The interference from plasma components was less than 10%, and the cross-reactivity with various lengths of Aβ peptides was less than 0.5%. In addition, we found a significant correlation between the IP-MS method and our immunoassay (correlation coefficients of Pearson's r: 0.91 [Aβ40] and 0.82 [Aβ42]). Our new method to quantify plasma Aβ40 and Aβ42 provides clinicians and patients with a way to continuously monitor disease progression.
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Damotte V, van der Lee SJ, Chouraki V, Grenier‐Boley B, Simino J, Adams H, Tosto G, White C, Terzikhan N, Cruchaga C, Knol MJ, Li S, Schraen S, Grove ML, Satizabal C, Amin N, Berr C, Younkin S, Gottesman RF, Buée L, Beiser A, Knopman DS, Uitterlinden A, DeCarli C, Bressler J, DeStefano A, Dartigues J, Yang Q, Boerwinkle E, Tzourio C, Fornage M, Ikram MA, Amouyel P, de Jager P, Reitz C, Mosley TH, Lambert J, Seshadri S, van Duijn CM. Plasma amyloid β levels are driven by genetic variants near APOE, BACE1, APP, PSEN2: A genome-wide association study in over 12,000 non-demented participants. Alzheimers Dement 2021; 17:1663-1674. [PMID: 34002480 PMCID: PMC8597077 DOI: 10.1002/alz.12333] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 12/17/2020] [Accepted: 02/18/2021] [Indexed: 01/02/2023]
Abstract
INTRODUCTION There is increasing interest in plasma amyloid beta (Aβ) as an endophenotype of Alzheimer's disease (AD). Identifying the genetic determinants of plasma Aβ levels may elucidate important biological processes that determine plasma Aβ measures. METHODS We included 12,369 non-demented participants from eight population-based studies. Imputed genetic data and measured plasma Aβ1-40, Aβ1-42 levels and Aβ1-42/Aβ1-40 ratio were used to perform genome-wide association studies, and gene-based and pathway analyses. Significant variants and genes were followed up for their association with brain positron emission tomography Aβ deposition and AD risk. RESULTS Single-variant analysis identified associations with apolipoprotein E (APOE) for Aβ1-42 and Aβ1-42/Aβ1-40 ratio, and BACE1 for Aβ1-40. Gene-based analysis of Aβ1-40 additionally identified associations for APP, PSEN2, CCK, and ZNF397. There was suggestive evidence for interaction between a BACE1 variant and APOE ε4 on brain Aβ deposition. DISCUSSION Identification of variants near/in known major Aβ-processing genes strengthens the relevance of plasma-Aβ levels as an endophenotype of AD.
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Affiliation(s)
- Vincent Damotte
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de LilleLilleFrance
| | - Sven J. van der Lee
- Alzheimer Center Amsterdam, Department of NeurologyAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamthe Netherlands
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
| | - Vincent Chouraki
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de LilleLilleFrance
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | | | - Jeannette Simino
- Gertrude C. Ford MIND CenterDepartment of Data ScienceJohn D. Bower School of Population HealthUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Hieab Adams
- Departments of EpidemiologyNeurologyand Radiology and Nuclear MedicineErasmus Medical CenterRotterdamthe Netherlands
| | - Giuseppe Tosto
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
- Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
| | - Charles White
- Program in Translational NeuroPsychiatric GenomicsInstitute for the NeurosciencesDepartments of Neurology and PsychiatryBrigham and Women's HospitalBostonMassachusettsUSA
- Program in Medical and Population GeneticsBroad InstituteCambridgeMassachusettsUSA
| | - Natalie Terzikhan
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
- Department of Respiratory MedicineGhent University HospitalGhentBelgium
| | - Carlos Cruchaga
- Department of PsychiatryWashington University in St. LouisSaint LouisMissouriUSA
| | - Maria J. Knol
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
| | - Shuo Li
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Susanna Schraen
- Université Lille, CHU‐Lille, InsermUF de Neurobiologie, CBPGLilleFrance
| | - Megan L. Grove
- Human Genetics Center, Department of EpidemiologyHuman Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Claudia Satizabal
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Najaf Amin
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
| | - Claudine Berr
- INSERM U1061University of MontpellierMontpellierFrance
| | - Steven Younkin
- Department of NeuroscienceMayo Clinic, JacksonvilleFloridaUSA
| | | | - Rebecca F. Gottesman
- Department of NeurologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Luc Buée
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de LilleLilleFrance
- Institut National de la Santé et de la Recherche Medicale (INSERMUniversité de LilleLilleFrance
| | - Alexa Beiser
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - David S. Knopman
- Department of NeurologyMayo Clinic College of MedicineRochesterMinnesotaUSA
| | - Andre Uitterlinden
- Department of Internal MedicineErasmus Medical CenterRotterdamthe Netherlands
| | - Charles DeCarli
- Department of NeurologyUniversity of California at DavisDavisCaliforniaUSA
| | - Jan Bressler
- Human Genetics Center, Department of EpidemiologyHuman Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Anita DeStefano
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | | | - Qiong Yang
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
| | - Eric Boerwinkle
- Human Genetics Center, Department of EpidemiologyHuman Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonHoustonTexasUSA
- Human Genome Sequencing CenterBaylor College of MedicineHoustonTexasUSA
| | - Christophe Tzourio
- Bordeaux Population Health Research CenterINSERM, UMR1219Bordeaux UniversityBordeauxFrance
| | - Myriam Fornage
- Human Genetics Center, Department of EpidemiologyHuman Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at HoustonHoustonTexasUSA
- Brown Foundation Institute of Molecular MedicineMcGovern Medical SchoolThe University of Texas Health Science Center at HoustonHoustonTexasUSA
| | - M. Arfan Ikram
- Departments of EpidemiologyNeurologyand Radiology and Nuclear MedicineErasmus Medical CenterRotterdamthe Netherlands
| | - Philippe Amouyel
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de LilleLilleFrance
| | - Phil de Jager
- Program in Translational NeuroPsychiatric GenomicsInstitute for the NeurosciencesDepartments of Neurology and PsychiatryBrigham and Women's HospitalBostonMassachusettsUSA
- Program in Medical and Population GeneticsBroad InstituteCambridgeMassachusettsUSA
- Center for Translational & Systems NeuroimmunologyDepartment of NeurologyColumbia University Medical Center, New YorkNew YorkNew YorkUSA
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
- Gertrude H. Sergievsky CenterColumbia UniversityNew YorkNew YorkUSA
- Department of NeurologyColumbia UniversityNew YorkNew YorkUSA
- Department of EpidemiologyColumbia UniversityNew YorkNew YorkUSA
| | - Thomas H. Mosley
- Department of MedicineGertrude C. Ford MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | | | - Sudha Seshadri
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUT Health San AntonioSan AntonioTexasUSA
| | - Cornelia M. van Duijn
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
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9
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Koychev I, Jansen K, Dette A, Shi L, Holling H. Blood-Based ATN Biomarkers of Alzheimer's Disease: A Meta-Analysis. J Alzheimers Dis 2021; 79:177-195. [PMID: 33252080 DOI: 10.3233/jad-200900] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND The Amyloid Tau Neurodegeneration (ATN) framework was proposed to define the biological state underpinning Alzheimer's disease (AD). Blood-based biomarkers offer a scalable alternative to the costly and invasive currently available biomarkers. OBJECTIVE In this meta-analysis we sought to assess the diagnostic performance of plasma amyloid (Aβ40, Aβ42, Aβ42/40 ratio), tangle (p-tau181), and neurodegeneration (total tau [t-tau], neurofilament light [NfL]) biomarkers. METHODS Electronic databases were screened for studies reporting biomarker concentrations for AD and control cohorts. Biomarker performance was examined by random-effect meta-analyses based on the ratio between biomarker concentrations in patients and controls. RESULTS 83 studies published between 1996 and 2020 were included in the analyses. Aβ42/40 ratio as well as Aβ42 discriminated AD patients from controls when using novel platforms such as immunomagnetic reduction (IMR). We found significant differences in ptau-181 concentration for studies based on single molecule array (Simoa), but not for studies based on IMR or ELISA. T-tau was significantly different between AD patients and control in IMR and Simoa but not in ELISA-based studies. In contrast, NfL differentiated between groups across platforms. Exosome studies showed strong separation between patients and controls for Aβ42, t-tau, and p-tau181. CONCLUSION Currently available assays for sampling plasma ATN biomarkers appear to differentiate between AD patients and controls. Novel assay methodologies have given the field a significant boost for testing these biomarkers, such as IMR for Aβ, Simoa for p-tau181. Enriching samples through extracellular vesicles shows promise but requires further validation.
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Affiliation(s)
- Ivan Koychev
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Katrin Jansen
- Department of Psychology, University of Münster, Münster, Germany
| | - Alina Dette
- Department of Psychology, University of Münster, Münster, Germany
| | - Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Heinz Holling
- Department of Psychology, University of Münster, Münster, Germany
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10
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Gallo A, Pillet LE, Verpillot R. New frontiers in Alzheimer's disease diagnostic: Monoamines and their derivatives in biological fluids. Exp Gerontol 2021; 152:111452. [PMID: 34182050 DOI: 10.1016/j.exger.2021.111452] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/29/2021] [Accepted: 06/08/2021] [Indexed: 10/21/2022]
Abstract
Current diagnosis of Alzheimer's disease (AD) relies on a combination of neuropsychological evaluations, biomarker measurements and brain imaging. Nevertheless, these approaches are either expensive, invasive or lack sensitivity to early AD stages. The main challenge of ongoing research is therefore to identify early non-invasive biomarkers to diagnose AD at preclinical stage. Accumulating evidence support the hypothesis that initial degeneration of profound monoaminergic nuclei may trigger a transneuronal spread of AD pathology towards hippocampus and cortex. These studies aroused great interest on monoamines, i.e. noradrenaline (NA), dopamine (D) ad serotonin (5-HT), as early hallmarks of AD pathology. The present work reviews current literature on the potential role of monoamines and related metabolites as biomarkers of AD. First, morphological changes in the monoaminergic systems during AD are briefly described. Second, we focus on concentration changes of these molecules and their derivatives in biological fluids, including cerebrospinal fluid, obtained by lumbar puncture, and blood or urine, sampled via less invasive procedures. Starting from initial observations, we then discuss recent insights on metabolomics-based analysis, highlighting the promising clinical utility of monoamines for the identification of a molecular AD signature, aimed at improving early diagnosis and discrimination from other dementia.
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11
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Natarajan K, Ullgren A, Khoshnood B, Johansson C, Laffita-Mesa JM, Pannee J, Zetterberg H, Blennow K, Graff C. Plasma metabolomics of presymptomatic PSEN1-H163Y mutation carriers: a pilot study. Ann Clin Transl Neurol 2021; 8:579-591. [PMID: 33476461 PMCID: PMC7951103 DOI: 10.1002/acn3.51296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 12/04/2020] [Accepted: 12/10/2020] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND AND OBJECTIVE PSEN1-H163Y carriers, at the presymptomatic stage, have reduced 18 FDG-PET binding in the cerebrum of the brain (Scholl et al., Neurobiol Aging 32:1388-1399, 2011). This could imply dysfunctional energy metabolism in the brain. In this study, plasma of presymptomatic PSEN1 mutation carriers was analyzed to understand associated metabolic changes. METHODS We analyzed plasma from noncarriers (NC, n = 8) and presymptomatic PSEN1-H163Y mutation carriers (MC, n = 6) via untargeted metabolomics using gas and liquid chromatography coupled with mass spectrometry, which identified 1199 metabolites. All the metabolites were compared between MC and NC using univariate analysis, as well as correlated with the ratio of Aβ1-42/A β 1-40 , using Spearman's correlation. Altered metabolites were subjected to Ingenuity Pathway Analysis (IPA). RESULTS Based on principal component analysis the plasma metabolite profiles were divided into dataset A and dataset B. In dataset A, when comparing between presymptomatic MC and NC, the levels of 79 different metabolites were altered. Out of 79, only 14 were annotated metabolites. In dataset B, 37 metabolites were significantly altered between presymptomatic MC and NC and nine metabolites were annotated. In both datasets, annotated metabolites represent amino acids, fatty acyls, bile acids, hexoses, purine nucleosides, carboxylic acids, and glycerophosphatidylcholine species. 1-docosapentaenoyl-GPC was positively correlated, uric acid and glucose were negatively correlated with the ratio of plasma Aβ1-42 /Aβ1-40 (P < 0.05). INTERPRETATION This study finds dysregulated metabolite classes, which are changed before the disease symptom onset. Also, it provides an opportunity to compare with sporadic Alzheimer's Disease. Observed findings in this study need to be validated in a larger and independent Familial Alzheimer's Disease (FAD) cohort.
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Affiliation(s)
- Karthick Natarajan
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Abbe Ullgren
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Behzad Khoshnood
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Charlotte Johansson
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - José M Laffita-Mesa
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
| | - Josef Pannee
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Department of Molecular Neuroscience, UCL Institute of Neurology, London, WC1N 3BG, England
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Caroline Graff
- Division for Neurogeriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Unit for Hereditary Dementias, Theme Aging, QA12, Karolinska University Hospital-Solna, Stockholm, Sweden
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12
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Oliveira Monteiro MPA, Salheb Oliveira DSM, Manzine PR, Crispim Nascimento CM, Dos Santos Orlandi AA, de Oliveira Gomes GA, Dos Santos Orlandi F, Zazzetta MS, Pott-Junior H, Cominetti MR. ADAM10 plasma levels predict worsening in cognition of older adults: a 3-year follow-up study. ALZHEIMERS RESEARCH & THERAPY 2021; 13:18. [PMID: 33419480 PMCID: PMC7792035 DOI: 10.1186/s13195-020-00750-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/14/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Blood-based biomarkers for Alzheimer's disease (AD) are highly needed in clinic practice. So far, the gold standards for AD diagnosis are brain neuroimaging and beta-amyloid peptide, total tau, and phosphorylated tau in cerebrospinal fluid (CSF); however, they are not attractive for large-scale screening. Blood-based biomarkers allow an initial large-scale screening of patients under suspicion that could later be tested for the already established CSF biomarkers. To this regard, in this study, we evaluated whether plasma ADAM10 levels would be predictors of declines in cognition in community-dwelling older adults after a 3-year period follow-up. METHODS This was a 3-year longitudinal cohort study that included 219 community-dwelling older adults. Sociodemographic, clinical, lifestyle, depressive symptoms (GDS), and cognitive data (Mini-Mental State Examination, MMSE; Clock Drawing test, CDT) were gathered. The measurement of ADAM10 plasma levels was performed using a sandwich ELISA kit. Bivariate comparisons between groups were performed using Wilcoxon-Mann-Whitney for continuous data and Pearson's chi-square tests with Yates continuity correction for categorical data. Longitudinal analyzes of changes in the MMSE scores were performed using linear mixed-effects modeling. RESULTS Baseline MMSE scores and ADAM10 levels were significantly associated with MMSE scores on the follow-up assessment. When analyzing the interaction with time, normal MMSE scores and the ADAM10 plasma levels at baseline presented a significant and independent negative association with MMSE score values on the follow-up assessment. The analyses also showed that the predictive effect of ADAM10 plasma levels on decreasing MMSE scores on follow-up seems to be more pronounced in participants with normal MMSE, when compared with those with altered MMSE scores at baseline. CONCLUSIONS Considering that ADAM10 increase in plasma is detected as soon as in mild cognitive impairment (MCI) patients, the results presented here may support the complementary clinical use of this biomarker, in addition to the classical AD biomarkers. Taken together, these results provide the first direct evidence that changes in ADAM10 plasma levels are predictors of cognitive worsening in older adults. Moreover, this work can shed light on the study of blood biomarkers for AD and contribute to the advancement of the area.
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Affiliation(s)
- Maria Patrícia A Oliveira Monteiro
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Danielle S M Salheb Oliveira
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Patrícia R Manzine
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Carla M Crispim Nascimento
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | | | - Grace A de Oliveira Gomes
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Fabiana Dos Santos Orlandi
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Marisa S Zazzetta
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil
| | - Henrique Pott-Junior
- Department of Medicine, Federal University of São Carlos (UFSCar), São Carlos, Brazil
| | - Marcia R Cominetti
- Department of Gerontology, Federal University of São Carlos (UFSCar), Rodovia Washington Luís, km 235, São Carlos, SP, 13565-905, Brazil.
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13
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Albani D, Marizzoni M, Ferrari C, Fusco F, Boeri L, Raimondi I, Jovicich J, Babiloni C, Soricelli A, Lizio R, Galluzzi S, Cavaliere L, Didic M, Schönknecht P, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Bocchio L, Salvatore M, Rossini PM, Tsolaki M, Visser PJ, Richardson JC, Wiltfang J, Bordet R, Blin O, Forloni G, Frisoni GB. Plasma Aβ42 as a Biomarker of Prodromal Alzheimer's Disease Progression in Patients with Amnestic Mild Cognitive Impairment: Evidence from the PharmaCog/E-ADNI Study. J Alzheimers Dis 2020; 69:37-48. [PMID: 30149449 DOI: 10.3233/jad-180321] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
It is an open issue whether blood biomarkers serve to diagnose Alzheimer's disease (AD) or monitor its progression over time from prodromal stages. Here, we addressed this question starting from data of the European FP7 IMI-PharmaCog/E-ADNI longitudinal study in amnesic mild cognitive impairment (aMCI) patients including biological, clinical, neuropsychological (e.g., ADAS-Cog13), neuroimaging, and electroencephalographic measures. PharmaCog/E-ADNI patients were classified as "positive" (i.e., "prodromal AD" n = 76) or "negative" (n = 52) based on a diagnostic cut-off of Aβ42/P-tau in cerebrospinal fluid as well as APOE ε 4 genotype. Blood was sampled at baseline and at two follow-ups (12 and 18 months), when plasma amyloid peptide 42 and 40 (Aβ42, Aβ40) and apolipoprotein J (clusterin, CLU) were assessed. Linear Mixed Models found no significant differences in plasma molecules between the "positive" (i.e., prodromal AD) and "negative" groups at baseline. In contrast, plasma Aβ42 showed a greater reduction over time in the prodromal AD than the "negative" aMCI group (p = 0.048), while CLU and Aβ40 increased, but similarly in the two groups. Furthermore, plasma Aβ42 correlated with the ADAS-Cog13 score both in aMCI patients as a whole and the prodromal AD group alone. Finally, CLU correlated with the ADAS-Cog13 only in the whole aMCI group, and no association with ADAS-Cog13 was found for Aβ40. In conclusion, plasma Aβ42 showed disease progression-related features in aMCI patients with prodromal AD.
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Affiliation(s)
- Diego Albani
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Federica Fusco
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Lucia Boeri
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Ilaria Raimondi
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Jorge Jovicich
- MR Lab Head, Center for Mind/Brain Sciences, University of Trento, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy.,Department of Neuroscience, IRCCS San Raffaele Pisana of Rome and Cassino, Rome and Cassino, Italy
| | - Andrea Soricelli
- IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | - Roberta Lizio
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, INSERM, INS UMR_S 1106, Marseille, France.,APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany, Germany
| | - José Luis Molinuevo
- Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM, Imagerie cérébrale et handicaps neurologiques UMR 825, Toulouse, France
| | - Luisella Bocchio
- Genetic Unit, IRCCS Centro Giovanni di Dio, Fatebenefratelli, Brescia, Italy; Faculty of Psychology, University eCampus, Novedrate (Como), Italy
| | - Marco Salvatore
- IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | - Paolo Maria Rossini
- Department of Gerontology, Neurosciences and Orthopedics, Catholic University, Rome, Italy.,Policlinic A. Gemelli Foundation
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | - Jens Wiltfang
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany.,iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Gianluigi Forloni
- Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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14
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Correlation between cognition and plasma noradrenaline level in Alzheimer's disease: a potential new blood marker of disease evolution. Transl Psychiatry 2020; 10:213. [PMID: 32620743 PMCID: PMC7335170 DOI: 10.1038/s41398-020-0841-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 04/17/2020] [Accepted: 04/22/2020] [Indexed: 12/31/2022] Open
Abstract
Recent evidence showing degeneration of the noradrenergic system in the locus coeruleus (LC) in Alzheimer's disease (AD) has motivated great interest in noradrenaline (NA) as a potential brain hallmark of the disease. Despite the current exploration of blood markers for AD, the deregulation of the plasma NA concentration ([NA]plasma) in AD is currently not well understood. This retrospective study includes a cohort of 71 patients (32 AD patients, 22 with other dementia and 17 without dementia) who were given consultations for memory complaints in the Cognitive Neurology Center of Lariboisière (Paris) between 2009 and 2014. As previously described in brain tissue, we show for the first time a linear correlation between [NA]plasma and Mini Mental State Examination (MMSE) score in AD patients. We observed that high [NA]plasma in AD patients was associated with higher [Aβ1-42]CSF than in other AD patients with [NA]plasma similar to NC patients. In parallel, we observed a lower (p-Tau/Tau)CSF in AD patients with low [NA]plasma than in non-AD patients with [NA]plasma similar to [NA]plasma in NC patients. Our data suggest that [NA]plasma could be a potential biomarker of disease evolution in the context of AD and could possibly improve early diagnosis.
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15
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Liu HC, Chiu MJ, Lin CH, Yang SY. Stability of Plasma Amyloid-β 1-40, Amyloid-β 1-42, and Total Tau Protein over Repeated Freeze/Thaw Cycles. Dement Geriatr Cogn Dis Extra 2020; 10:46-55. [PMID: 32308667 PMCID: PMC7154287 DOI: 10.1159/000506278] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 01/29/2020] [Indexed: 12/31/2022] Open
Abstract
Introduction Blood biomarkers of Alzheimer's disease (AD) have attracted much attention of researchers in recent years. In clinical studies, repeated freeze/thaw cycles often occur and may influence the stability of biomarkers. This study aims to investigate the stability of amyloid-β 1–40 (Aβ<sub>1–40</sub>), amyloid-β 1–42 (Aβ<sub>1–42</sub>), and total tau protein (T-tau) in plasma over freeze/thaw cycles. Methods Plasma samples from healthy controls (n = 2), AD patients (AD, n =3) and Parkinson's disease patients (PD, n = 3) were collected by standardized procedure and immediately frozen at −80°C. Samples underwent 5 freeze/thaw (−80°C/room temperature) cycles. The concentrations of Aβ<sub>1–40</sub>, Aβ<sub>1–42</sub>, and T-tau were monitored during the freeze/thaw tests using an immunomagnetic reduction (IMR) assay. The relative percentage of concentrations after every freeze/thaw cycle was calculated for each biomarker. Results A tendency of decrease in the averaged relative percentages over samples through the freeze and thaw cycles for Aβ<sub>1–40</sub> (100 to 97.11%), Aβ<sub>1–42</sub> (100 to 94.99%), and T-tau (100 to 95.65%) was found. However, the decreases were less than 6%. For all three biomarkers, no statistical significance was found between the levels of fresh plasma and those of the plasma experiencing 5 freeze/thaw cycles (p > 0.1). Conclusions Plasma Aβ<sub>1–40</sub>, Aβ<sub>1–42</sub>, and T-tau are stable through 5 freeze/thaw cycles measured with IMR.
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Affiliation(s)
| | - Ming-Jang Chiu
- Neurology, National Taiwan University Hospital, Taipei, Taiwan.,Neurology, College of Medicine, National Taiwan University, Taipei, Taiwan.,Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chin-Hsien Lin
- Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Shieh-Yueh Yang
- MagQu Co., Ltd., New Taipei City, Taiwan.,MagQu LLC, Surprise, Arizona, USA
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16
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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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17
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Giannini LAA, Xie SX, Peterson C, Zhou C, Lee EB, Wolk DA, Grossman M, Trojanowski JQ, McMillan CT, Irwin DJ. Empiric Methods to Account for Pre-analytical Variability in Digital Histopathology in Frontotemporal Lobar Degeneration. Front Neurosci 2019; 13:682. [PMID: 31333403 PMCID: PMC6616086 DOI: 10.3389/fnins.2019.00682] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 06/14/2019] [Indexed: 12/12/2022] Open
Abstract
Digital pathology is increasingly prominent in neurodegenerative disease research, but variability in immunohistochemical staining intensity between staining batches prevents large-scale comparative studies. Here we provide a statistically rigorous method to account for staining batch effects in a large sample of brain tissue with frontotemporal lobar degeneration with tau inclusions (FTLD-Tau, N = 39) or TDP-43 inclusions (FTLD-TDP, N = 53). We analyzed the relationship between duplicate measurements of digital pathology, i.e., percent area occupied by pathology (%AO) for grey matter (GM) and white matter (WM), from two distinct staining batches. We found a significant difference in duplicate measurements from distinct staining batches in FTLD-Tau (mean difference: GM = 1.13 ± 0.44, WM = 1.28 ± 0.56; p < 0.001) and FTLD-TDP (GM = 0.95 ± 0.66, WM = 0.90 ± 0.77; p < 0.001), and these measurements were linearly related (R-squared [Rsq]: FTLD-Tau GM = 0.92, WM = 0.92; FTLD-TDP GM = 0.75, WM = 0.78; p < 0.001 all). We therefore used linear regression to transform %AO from distinct staining batches into equivalent values. Using a train-test set design, we examined transformation prerequisites (i.e., Rsq) from linear-modeling in training sets, and we applied equivalence factors (i.e., beta, intercept) to independent testing sets to determine transformation outcomes (i.e., intraclass correlation coefficient [ICC]). First, random iterations (×100) of linear regression showed that smaller training sets (N = 12–24), feasible for prospective use, have acceptable transformation prerequisites (mean Rsq: FTLD-Tau ≥0.9; FTLD-TDP ≥0.7). When cross-validated on independent complementary testing sets, in FTLD-Tau, N = 12 training sets resulted in 100% of GM and WM transformations with optimal transformation outcomes (ICC ≥ 0.8), while in FTLD-TDP N = 24 training sets resulted in optimal ICC in testing sets (GM = 72%, WM = 98%). We therefore propose training sets of N = 12 in FTLD-Tau and N = 24 in FTLD-TDP for prospective transformations. Finally, the transformation enabled us to significantly reduce batch-related difference in duplicate measurements in FTLD-Tau (GM/WM: p < 0.001 both) and FTLD-TDP (GM/WM: p < 0.001 both), and to decrease the necessary sample size estimated in a power analysis in FTLD-Tau (GM:-40%; WM: -34%) and FTLD-TDP (GM: -20%; WM: -30%). Finally, we tested generalizability of our approach using a second, open-source, image analysis platform and found similar results. We concluded that a small sample of tissue stained in duplicate can be used to account for pre-analytical variability such as staining batch effects, thereby improving methods for future studies.
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Affiliation(s)
- Lucia A A Giannini
- Penn Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Department of Neurology, University Medical Center Groningen - University of Groningen, Groningen, Netherlands
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Claire Peterson
- Penn Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Cecilia Zhou
- Penn Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B Lee
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Alzheimer's Disease Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David A Wolk
- Alzheimer's Disease Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - John Q Trojanowski
- Alzheimer's Disease Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J Irwin
- Penn Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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18
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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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19
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Plasma β-amyloid 1–42 reference values in cognitively normal subjects. J Neurol Sci 2018; 391:120-126. [DOI: 10.1016/j.jns.2018.06.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/18/2018] [Accepted: 06/12/2018] [Indexed: 12/17/2022]
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20
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Williams SM, Schulz P, Rosenberry TL, Caselli RJ, Sierks MR. Blood-Based Oligomeric and Other Protein Variant Biomarkers to Facilitate Pre-Symptomatic Diagnosis and Staging of Alzheimer's Disease. J Alzheimers Dis 2018; 58:23-35. [PMID: 28372328 DOI: 10.3233/jad-161116] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Oligomeric forms of amyloid-β (Aβ), tau, and TDP-43 play important roles in Alzheimer's disease (AD), and therefore are promising biomarkers. We previously generated single chain antibody fragments (scFvs) that selectively bind disease-related variants of these proteins including A4, C6T, and E1, which bind different oligomeric Aβ variants; D11C, which binds oligomeric tau; and AD-TDP1 and AD-TDP2, which bind disease related TDP-43 variants. To determine the utility of these disease-related variants as early biomarkers, we first analyzed 11 human sera samples obtained ∼2 years prior to an initial mild cognitive impairment (MCI) diagnosis. While the subsequent diagnoses for the cases covered several different conditions, all samples had elevated protein variant levels relative to the plasma controls although with different individual biomarker profiles. We then analyzed a set of longitudinal human plasma samples from four AD (encompassing time points prior to MCI diagnosis and continuing until after conversion to AD) and two control cases. Pre-MCI samples were characterized by high TDP-43 variant levels, MCI samples by high Aβ variant levels, and AD samples by high Aβ and tau variant levels. Sample time points ranged from ∼7 years pre-MCI to ∼9 years after AD conversion. Bivariate correlations showed a negative correlation with TDP-43 levels and positive correlations with cumulative Aβ and oligomeric tau levels indicating an increase in neurodegenerative processes with time in AD. Detection of disease related protein variants not only readily selects AD cases from controls, but also stages progression of AD and holds promise for a pre-symptomatic blood-based biomarker profile for AD.
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Affiliation(s)
- Stephanie M Williams
- Chemical Engineering, The School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
| | - Philip Schulz
- Chemical Engineering, The School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
| | - Terrone L Rosenberry
- Department of Neuroscience, Mayo Clinic College of Medicine, Jacksonville, FL, USA
| | | | - Michael R Sierks
- Chemical Engineering, The School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
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21
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The application of control charts in regulated bioanalysis for monitoring long-term reproducibility. Bioanalysis 2017; 9:1955-1965. [DOI: 10.4155/bio-2017-0163] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
In regulated bioanalysis, the acceptance of results is batch-wise. When during clinical development derived pharmacokinetic or pharmacodynamic results from different studies will be combined or compared, it is recommendable to monitor the long-term reproducibility of bioanalytical assays. Long-term reproducibility can be evaluated by control charts generated from control samples included in each batch. We present a methodology for the implementation, construction and evaluation of control charts next to the regular batch acceptance of bioanalytical results. Decision rules can be set up for a statistical evaluation of the results. Violation of a decision rule may lead to a root-cause investigation and corrective actions to improve assay robustness. Three examples of control charts, for pharmacokinetic and pharmacodynamic analytes are presented.
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22
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Hsu JL, Lee WJ, Liao YC, Wang SJ, Fuh JL. The clinical significance of plasma clusterin and Aβ in the longitudinal follow-up of patients with Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2017; 9:91. [PMID: 29169407 PMCID: PMC5701424 DOI: 10.1186/s13195-017-0319-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Accepted: 11/06/2017] [Indexed: 12/29/2022]
Abstract
Background Clusterin and beta-amyloid (Aβ) are involved in the pathogenesis of Alzheimer’s disease (AD). The clinical significance of plasma clusterin and Aβ in AD progression remains controversial. Methods We recruited 322 patients with AD and 88 controls between August 2012 and June 2013. All participants were evaluated at baseline with a clinical assessment, Mini-Mental State Examination (MMSE), and Clinical Dementia Rating (CDR) scales. Patients with AD were evaluated annually with the MMSE and Neuropsychiatric Inventory (NPI) scale during the 2-year follow-up period. The levels of plasma clusterin, Aβ1–40, and Aβ1–42 at baseline were analyzed to study the longitudinal changes in the patient scores on the MMSE and NPI during the follow-up period. Results Patients in the highest tertile of plasma clusterin levels showed significantly lower MMSE scores than those in the lowest tertile (p = 0.04). After adjustment for multiple covariates using the generalized estimating equation analysis, there was a significant decrease in the MMSE scores over the 2-year follow-up period among AD patients in the highest tertile of plasma clusterin levels compared with those in the lowest tertile (−2.09, 95% confidence interval (CI) = −3.67 to −0.51, p = 0.01). In apolipoprotein E (ApoE)4-positive AD patients, baseline measurements of the ratio of plasma Aβ1–42/Aβ1–40 in the highest tertile predicted an increase in NPI agitation/aggression scores over the 2-year follow-up period (6.06, 95% CI = 1.20–10.62, p = 0.02). Conclusions Plasma clusterin could serve as a biomarker for the severity of cognitive decline. Plasma Aβ in ApoE4-positive AD could predict long-term agitation/aggression symptoms.
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Affiliation(s)
- Jung-Lung Hsu
- Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan.,Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center and College of Medicine, Chang-Gung University, Taoyuan, Taiwan.,Taipei Medical University Research Center for Brain and Consciousness, Shuang-Ho Hospital, New Taipei City, Taiwan
| | - Wei-Ju Lee
- Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,Faculty of Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan.,Institute of Clinical Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Yi-Chu Liao
- Faculty of Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University School of Medicine, Taipei, Taiwan.,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, 112, Taiwan
| | - Shuu-Jiun Wang
- Faculty of Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan. .,Brain Research Center, National Yang-Ming University School of Medicine, Taipei, Taiwan. .,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, 112, Taiwan.
| | - Jong-Ling Fuh
- Faculty of Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan. .,Brain Research Center, National Yang-Ming University School of Medicine, Taipei, Taiwan. .,Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, 112, Taiwan.
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23
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Gong YH, Hua N, Zang X, Huang T, He L. Melatonin ameliorates Aβ1-42-induced Alzheimer's cognitive deficits in mouse model. J Pharm Pharmacol 2017; 70:70-80. [DOI: 10.1111/jphp.12830] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 09/16/2017] [Indexed: 01/09/2023]
Abstract
Abstract
Objectives
The objective of this study was to evaluate whether melatonin could ameliorate cognitive function in Aβ1-42-induced mouse model and its underlying mechanisms.
Methods
Series behaviour tests were performed to demonstrate the amelioration of cognitive function of the Alzheimer's disease (AD) mice induced by Aβ1-42. Additionally, enzyme-linked immunosorbent assay was applied to detect the expression of Aβ1-42, BACE1 and p-tau protein in the brain of the AD mice. JC-1 was performed to investigate the role in alleviating mitochondrial damage by melatonin in vitro. Western blot was used to detect the expression of melatonin on apoptosis-related factors caspase-3 and Bcl-2, as well as the expressions of GSK-3β and PP2A to further determine the mechanisms of melatonin on the expression of p-tau protein.
Key findings
Melatonin significantly ameliorated the cognitive function and mitochondrial damage in AD mice, reduced the expression levels of GSK-3β, caspase-3, Aβ1-42, BACE1, p-tau protein and increased the expressions of PP2A and Bcl-2.
Conclusion
From the overall results, we concluded that melatonin alleviated the mitochondrial damage effectively and decreased the expressions of the p-tau and some key proteins of apoptosis, leading to the improvement of cognitive function of the mice induced by Aβ1-42.
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Affiliation(s)
- Yu-Hang Gong
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Nan Hua
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Xuan Zang
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Tao Huang
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
| | - Ling He
- Department of Pharmacology, China Pharmaceutical University, Nanjing, China
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24
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Abstract
The utility of the levels of amyloid beta (Aβ) peptide and tau in blood for diagnosis, drug development, and assessment of clinical trials for Alzheimer's disease (AD) has not been established. The lack of availability of ultra-sensitive assays is one critical issue that has impeded progress. The levels of Aβ species and tau in plasma and serum are much lower than levels in cerebrospinal fluid. Furthermore, plasma or serum contain high levels of assay-interfering factors, resulting in difficulties in the commonly used singulex or multiplex ELISA platforms. In this review, we focus on two modern immune-complex-based technologies that show promise to advance this field. These innovative technologies are immunomagnetic reduction technology and single molecule array technology. We describe the technologies and discuss the published studies using these technologies. Currently, the potential of utilizing these technologies to advance Aβ and tau as blood-based biomarkers for AD requires further validation using already collected large sets of samples, as well as new cohorts and population-based longitudinal studies.
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25
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Sabbagh MN. Editorial Introduction to the Special Issue from the International Symposium on Biomarkers for Alzheimer's Disease and Related Disorders. Neurol Ther 2017; 6:1-4. [PMID: 28733962 PMCID: PMC5520814 DOI: 10.1007/s40120-017-0068-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Indexed: 11/17/2022] Open
Affiliation(s)
- Marwan N Sabbagh
- Department of Neurology, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, USA.
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26
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Vinothkumar G, Kedharnath C, Krishnakumar S, Sreedhar S, Preethikrishnan K, Dinesh S, Sundaram A, Balakrishnan D, Shivashekar G, Sureshkumar, Venkataraman P. Abnormal amyloid β 42 expression and increased oxidative stress in plasma of CKD patients with cognitive dysfunction: A small scale case control study comparison with Alzheimer's disease. BBA CLINICAL 2017; 8:20-27. [PMID: 28702365 PMCID: PMC5491400 DOI: 10.1016/j.bbacli.2017.06.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Revised: 06/02/2017] [Accepted: 06/20/2017] [Indexed: 01/31/2023]
Abstract
Background Cognitive dysfunction has been increasingly recognized in chronic kidney disease (CKD) patients. Senile plaques are important pathophysiological characteristic of cognitive dysfunction. The major component of plaques is the amyloid β (Aβ) peptide released from proteolytic cleavage of amyloid precursor protein (APP). Plasma Aβ has been a focus of the growing literature on blood based biomarkers for cognitive dysfunction. Oxidative stress is prevalent in CKD and it plays an important role in cognitive dysfunction. Increased oxidative stress leads to cause cleavage of APP and Aβ production. The aim of this study is to assess the antioxidant status and Aβ42 levels in plasma of CKD patients with cognitive dysfunction compared to CKD without cognitive dysfunction. Methods A total of 60 subjects divided into 30 CKD without cognitive dysfunction and 30 CKD with cognitive dysfunction based on neuropsychological assessment tests. To compare antioxidant status and Aβ42 levels in plasma, the following groups such as healthy subjects (n = 30), normocytic normochromic anemia (n = 30) and Alzheimer's disease (AD, n = 10) patients were also maintained. Plasma Superoxide dismutase (SOD), Catalase (CAT), Glutathione peroxidase (GPx), Reduced glutathione (GSH) and lipid peroxidation (LPO) were determined by spectrophotometrically. Aβ level was determined by immunoblotting method. The parameters were statistically compared with healthy, normocytic normochromic anemia and AD subjects. Results Like AD subjects, significantly increased Aβ and LPO level while decreased SOD, CAT, GPx and GSH levels were observed in plasma of CKD patients with cognitive dysfunction when compared to healthy, CKD without cognitive dysfunction and normocytic normochromic anemic subjects. Conclusion Results suggest that elevated plasma oxidative stress and Aβ were seen in CKD patients with cognitive dysfunction may be attributed to pathological changes within the brain. Cognitive dysfunction has been increasingly recognized in chronic kidney disease (CKD) patients. The major component of plaques is the amyloid β peptide released from proteolytic cleavage of amyloid precursor protein. Plasma Aβ has been a focus of the growing literature on blood based biomarkers for cognitive dysfunction. Oxidative stress is prevalent in CKD and it plays an important role in cognitive dysfunction. Increased oxidative stress leads to cause cleavage of APP and Aβ production.
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Affiliation(s)
- G Vinothkumar
- Department of Medical Research, SRM Medical College Hospital, SRM University, Chennai, India
| | - C Kedharnath
- Department of Nephrology, SRM Medical College Hospital, SRM University, Chennai, India
| | - S Krishnakumar
- Department of Nephrology, SRM Medical College Hospital, SRM University, Chennai, India
| | - S Sreedhar
- Department of Nephrology, SRM Medical College Hospital, SRM University, Chennai, India
| | - K Preethikrishnan
- Department of Clinical Psychology, SRM Medical College Hospital, SRM University, Chennai, India
| | - S Dinesh
- Department of Clinical Psychology, SRM Medical College Hospital, SRM University, Chennai, India
| | - A Sundaram
- Department of Medical Research, SRM Medical College Hospital, SRM University, Chennai, India
| | - D Balakrishnan
- Department of Medical Research, SRM Medical College Hospital, SRM University, Chennai, India
| | - G Shivashekar
- Department of Pathology, SRM Medical College Hospital, SRM University, Chennai, India
| | - Sureshkumar
- Department of Neurology, Balaji Medical College Hospital, Chrompet, Chennai, India
| | - P Venkataraman
- Department of Medical Research, SRM Medical College Hospital, SRM University, Chennai, India
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27
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Keshavan A, Heslegrave A, Zetterberg H, Schott JM. Blood Biomarkers for Alzheimer's Disease: Much Promise, Cautious Progress. Mol Diagn Ther 2017; 21:13-22. [PMID: 27738910 DOI: 10.1007/s40291-016-0241-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Biomarkers in Alzheimer's disease (AD) have the potential to allow early and more accurate diagnosis, predict disease progression, stratify individuals and track response to candidate therapies in drug trials. The first fluid biomarkers reflecting aspects of AD neuropathology were identified in cerebrospinal fluid (CSF) in the 1990s. Three CSF biomarkers (amyloid-β 1-42, total tau and phospho-tau) have consistently been shown to have diagnostic utility and are incorporated into the new diagnostic criteria for AD. These markers have also been shown in longitudinal studies to predict conversion of mild cognitive impairment to AD. However, a key issue with the use of CSF biomarkers as a screening test is the invasiveness of lumbar puncture. Over the last 20 years there has been an active quest for blood biomarkers, which could be easily acquired and tested repeatedly throughout the disease course. One approach to identifying such markers is to attempt to measure candidates that have already been identified in CSF. Until recently, this approach has been limited by assay sensitivity, but newer platforms now allow single molecule-level detection. Another approach is identification of candidates in large multiplex panels that allow for multiple analytes to be quantified in parallel. While both approaches show promise, to date no blood-based biomarker or combination of biomarkers has sufficient predictive value to have utility in clinical practice. In this review, an overview of promising blood protein candidates is provided, and the challenges of validating and converting these into practicable tests are discussed.
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Affiliation(s)
- Ashvini Keshavan
- Dementia Research Centre, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, Box 16, Queen Square, London, WC1N 3BG, UK
| | - Amanda Heslegrave
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, Box 16, Queen Square, London, WC1N 3BG, UK.
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28
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Song L, Lachno DR, Hanlon D, Shepro A, Jeromin A, Gemani D, Talbot JA, Racke MM, Dage JL, Dean RA. A digital enzyme-linked immunosorbent assay for ultrasensitive measurement of amyloid-β 1-42 peptide in human plasma with utility for studies of Alzheimer's disease therapeutics. ALZHEIMERS RESEARCH & THERAPY 2016; 8:58. [PMID: 27978855 PMCID: PMC5160015 DOI: 10.1186/s13195-016-0225-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Accepted: 11/18/2016] [Indexed: 12/18/2022]
Abstract
Background Amyloid-β 1–42 peptide (Aβ1–42) is associated with plaque formation in the brain of patients with Alzheimer’s disease (AD). Pharmacodynamic studies of AD therapeutics that lower the concentrations of Aβ1–42 in peripheral blood require highly sensitive assays for its measurement. A digital enzyme-linked immunosorbent assay (ELISA) using single molecule array (Simoa) technology has been developed that provides improved sensitivity compared with conventional ELISA methods using the same antibody reagents. Methods A sensitive digital ELISA for measurement of Aβ1–42 using antibodies 3D6 and 21F12 was developed. Assay performance was evaluated by repeated testing of pooled human plasma and buffer diluent quality control samples to determine relative accuracy, intra- and inter-assay precision, limit of detection (LOD), lower limit of quantification (LLOQ), dilutional linearity, and spike recovery. The optimized assay was used to quantify Aβ1–42 in clinical samples from patients treated with the β-site amyloid precursor protein cleaving enzyme 1 inhibitor LY2886721. Results The prototype assay measured Aβ1–42 with an LOD of 0.3 pg/ml and an LLOQ of 2.8 pg/ml in plasma, calibrated using an Aβ1–42 peptide standard from Fujirebio. Assay precision was acceptable with intra- and inter-assay coefficients of variation both being ≤10%. Dilutional linearity was demonstrated in sample diluent and immunodepleted human plasma. Analyte spike recovery ranged from 51% to 93% with a mean of 80%. This assay was able to quantify Aβ1–42 in all of the 84 clinical samples tested. A rapid reduction in levels of Aβ1–42 was detected within 1 h after drug treatment, and a dose-dependent decrease of Aβ1–42 levels was also observed over the time course of sample collection. Conclusions This digital ELISA has potential utility in clinical applications for quantification of Aβ1–42 in plasma where high sensitivity and precision are required.
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Affiliation(s)
- Linan Song
- Quanterix Corporation, Lexington, MA, USA
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The Alzheimer's Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans. Alzheimers Dement 2016; 11:772-91. [PMID: 26194312 DOI: 10.1016/j.jalz.2015.05.003] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 05/04/2015] [Accepted: 05/05/2015] [Indexed: 11/20/2022]
Abstract
INTRODUCTION We describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. METHODS Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data. RESULTS CSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. DISCUSSION Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.
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30
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Conti E, Nacinovich R, Bomba M, Raggi ME, Neri F, Ferrarese C, Tremolizzo L. Beta-amyloid plasma levels in adolescents with anorexia nervosa of the restrictive type. Neuropsychobiology 2016; 71:154-7. [PMID: 25998413 DOI: 10.1159/000381399] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Accepted: 03/04/2015] [Indexed: 11/19/2022]
Abstract
BACKGROUND Reduced plasma leptin and elevated homocysteine (Hcy) are known to lead to increased β-amyloid (Aβ) production, besides being hallmarks of anorexia nervosa (AN) of the restrictive type. AN subjects display several neuropsychiatric manifestations, which may entail Aβ-mediated altered synaptic functions. The aim of this study consisted in assessing Aβ plasma levels in AN patients. METHODS A total of 24 adolescent female AN outpatients were recruited together with 12 age-comparable healthy controls. For each subject we assessed Aβ40 and leptin plasma levels, as well as APOE genotype. Hcy plasma levels were also determined in AN patients who underwent clinical characterization, including the Eating Disorder Inventory-3 (EDI-3), the Children's Depression Inventory (CDI) and the estimation of the speed of BMI loss (DPI, disease progression index). RESULTS Plasma Aβ40 levels were similar between patients and controls, while a marked reduction was observed for leptin (∼80%) in AN patients. Aβ40 plasma levels failed to correlate with leptin, while a linear correlation was present with Hcy (r = 0.50, p < 0.03). Examined clinical features were not related with Aβ40 plasma levels, with the only exception of the DPI (r = 0.47, p < 0.03). CONCLUSION This exploratory study does not support a significant role for altered Aβ production in AN-associated dysfunctions. Further studies are required to clarify whether exceptions to this conclusion can be drawn for those patients expressing significantly elevated Hcy plasma levels or for those progressing more rapidly.
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Affiliation(s)
- Elisa Conti
- Neurology Unit, Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, Monza, Italy
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Donohue MC, Moghadam SH, Roe AD, Sun CK, Edland SD, Thomas RG, Petersen RC, Sano M, Galasko D, Aisen PS, Rissman RA. Longitudinal plasma amyloid beta in Alzheimer's disease clinical trials. Alzheimers Dement 2015; 11:1069-79. [PMID: 25301682 PMCID: PMC4387108 DOI: 10.1016/j.jalz.2014.07.156] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Revised: 06/13/2014] [Accepted: 07/05/2014] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Little is known about the utility of plasma amyloid beta (Aβ) in clinical trials of Alzheimer's disease (AD). METHODS We analyzed longitudinal plasma samples from two large multicenter clinical trials: (1) donezepil and vitamin E in mild cognitive impairment (n = 405, 24 months) and (2) simvastatin in mild to moderate AD (n = 225, 18 months). RESULTS Baseline plasma Aβ was not related to cognitive or clinical progression. We observed a decrease in plasma Aβ40 and 42 among apolipoprotein E epsilon 4 (APOE ε4) carriers relative to noncarriers in the mild cognitive impairment trial. Patients treated with simvastatin showed a significant increase in Aβ compared with placebo. We found significant storage time effects and considerable plate-to-plate variation. DISCUSSION We found no support for the utility of plasma Aβ as a prognostic factor or correlate of cognitive change. Analysis of stored specimens requires careful standardization and experimental design, but plasma Aβ may prove useful in pharmacodynamic studies of antiamyloid drugs.
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Affiliation(s)
- Michael C Donohue
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA; Department of Family Preventive Medicine, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Setareh H Moghadam
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Allyson D Roe
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Chung-Kai Sun
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Steven D Edland
- Department of Family Preventive Medicine, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Ronald G Thomas
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA; Department of Family Preventive Medicine, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Ronald C Petersen
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA; Department of Neurology, Mayo Clinic Alzheimer's Disease Research Center, Department of Health Sciences Mayo Clinic College of Medicine, Research, Rochester, MN, USA
| | - Mary Sano
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA; Mount Sinai School of Medicine and James J. Peters Veterans Association Medical Center, Bronx, NY, USA
| | - Douglas Galasko
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Paul S Aisen
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Robert A Rissman
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, University of California San Diego, School of Medicine, San Diego, CA, USA.
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Cedarbaum J, Green RC, Harvey D, Jack CR, Jagust W, Luthman J, Morris JC, Petersen RC, Saykin AJ, Shaw L, Shen L, Schwarz A, Toga AW, Trojanowski JQ. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception. Alzheimers Dement 2015; 11:e1-120. [PMID: 26073027 PMCID: PMC5469297 DOI: 10.1016/j.jalz.2014.11.001] [Citation(s) in RCA: 208] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/18/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Paul S Aisen
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jesse Cedarbaum
- Neurology Early Clinical Development, Biogen Idec, Cambridge, MA, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Johan Luthman
- Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
| | - John C Morris
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li Shen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam Schwarz
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Ortiz-Martin L, Benavente F, Medina-Casanellas S, Giménez E, Sanz-Nebot V. Study of immobilized metal affinity chromatography sorbents for the analysis of peptides by on-line solid-phase extraction capillary electrophoresis-mass spectrometry. Electrophoresis 2015; 36:962-70. [DOI: 10.1002/elps.201400374] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Revised: 12/12/2014] [Accepted: 12/12/2014] [Indexed: 11/12/2022]
Affiliation(s)
- Lorena Ortiz-Martin
- Department of Analytical Chemistry; University of Barcelona; Barcelona Spain
| | - Fernando Benavente
- Department of Analytical Chemistry; University of Barcelona; Barcelona Spain
| | | | - Estela Giménez
- Department of Analytical Chemistry; University of Barcelona; Barcelona Spain
| | - Victoria Sanz-Nebot
- Department of Analytical Chemistry; University of Barcelona; Barcelona Spain
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Chouraki V, De Bruijn RFAG, Chapuis J, Bis JC, Reitz C, Schraen S, Ibrahim-Verbaas CA, Grenier-Boley B, Delay C, Rogers R, Demiautte F, Mounier A, Fitzpatrick AL, Berr C, Dartigues JF, Uitterlinden AG, Hofman A, Breteler M, Becker JT, Lathrop M, Schupf N, Alpérovitch A, Mayeux R, van Duijn CM, Buée L, Amouyel P, Lopez OL, Ikram MA, Tzourio C, Lambert JC. A genome-wide association meta-analysis of plasma Aβ peptides concentrations in the elderly. Mol Psychiatry 2014; 19:1326-35. [PMID: 24535457 PMCID: PMC4418478 DOI: 10.1038/mp.2013.185] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Revised: 10/08/2013] [Accepted: 10/31/2013] [Indexed: 11/09/2022]
Abstract
Amyloid beta (Aβ) peptides are the major components of senile plaques, one of the main pathological hallmarks of Alzheimer disease (AD). However, Aβ peptides' functions are not fully understood and seem to be highly pleiotropic. We hypothesized that plasma Aβ peptides concentrations could be a suitable endophenotype for a genome-wide association study (GWAS) designed to (i) identify novel genetic factors involved in amyloid precursor protein metabolism and (ii) highlight relevant Aβ-related physiological and pathophysiological processes. Hence, we performed a genome-wide association meta-analysis of four studies totaling 3 528 healthy individuals of European descent and for whom plasma Aβ1-40 and Aβ1-42 peptides levels had been quantified. Although we did not observe any genome-wide significant locus, we identified 18 suggestive loci (P<1 × 10(-)(5)). Enrichment-pathway analyses revealed canonical pathways mainly involved in neuronal functions, for example, axonal guidance signaling. We also assessed the biological impact of the gene most strongly associated with plasma Aβ1-42 levels (cortexin 3, CTXN3) on APP metabolism in vitro and found that the gene protein was able to modulate Aβ1-42 secretion. In conclusion, our study results suggest that plasma Aβ peptides levels are valid endophenotypes in GWASs and can be used to characterize the metabolism and functions of APP and its metabolites.
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Affiliation(s)
- V Chouraki
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - RFAG De Bruijn
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - J Chapuis
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - JC Bis
- Cardiovascular Health Resarch Unit and Department of Medicine,
University of Washington, Seattle, WA, USA
| | - C Reitz
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA,The Gertrude H. Sergievsky Center, Columbia University, New York,
NY, USA,The Department of Neurology, College of Physicians and Surgeons,
Columbia University, New York, NY, USA
| | - S Schraen
- Université Lille-Nord de France, Lille, France,Inserm U837, Jean-Pierre Aubert Research Centre, Lille,
France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - CA Ibrahim-Verbaas
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands
| | - B Grenier-Boley
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - C Delay
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - R Rogers
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA
| | - F Demiautte
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - A Mounier
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
| | - AL Fitzpatrick
- Cardiovascular Health Resarch Unit and Department of Medicine,
University of Washington, Seattle, WA, USA
| | | | - C Berr
- INSERM U888, Hôpital La Colombière, Montpellier,
France
| | - J-F Dartigues
- INSERM U593, Victor Segalen University, Bordeaux, France
| | - AG Uitterlinden
- Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands,Department of Internal medicine, Leiden, Erasmus MC University
Medical Center, Rotterdam, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - M Breteler
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,DZNE, German Center for Neurodegenerative Diseases, Bonn,
Germany
| | - JT Becker
- Alzheimer’s Disease Research Center, Departments of
Neurology, Psychiatry and Psychology, University of Pittsburgh School of Medicine,
Pittsburgh, PA, USA
| | - M Lathrop
- Fondation Jean Dausset—Centre d’Etude du
Polymorphisme Humain, Paris, France,Centre National de Genotypage, Institut Genomique, Commissariat
à l’énergie Atomique, Evry, France
| | - N Schupf
- The Gertrude H. Sergievsky Center, Columbia University, New York,
NY, USA
| | | | - R Mayeux
- The Taub Institute for Research on Alzheimer’s Disease and
the Aging Brain, Columbia University, New York, NY, USA,The Department of Psychiatry, College of Physicians and Surgeons,
Columbia University, New York, NY, USA
| | - CM van Duijn
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands
| | - L Buée
- Université Lille-Nord de France, Lille, France,Inserm U837, Jean-Pierre Aubert Research Centre, Lille,
France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - P Amouyel
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France,Centre Hospitalier Régional Universitaire de Lille, Lille,
France
| | - OL Lopez
- Alzheimer’s Disease Research Center, Departments of
Neurology, Psychiatry and Psychology, University of Pittsburgh School of Medicine,
Pittsburgh, PA, USA
| | - MA Ikram
- Department of Epidemiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Aging, Leiden, The
Netherlands,Department of Radiology, Erasmus MC University Medical Center,
Rotterdam, The Netherlands
| | - C Tzourio
- INSERM U593, Victor Segalen University, Bordeaux, France,INSERM U708, Paris, France
| | - J-C Lambert
- INSERM U744, Lille, France,Institut pasteur de Lille, Lille, France,Université Lille-Nord de France, Lille, France
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Paterson RW, Toombs J, Slattery CF, Schott JM, Zetterberg H. Biomarker modelling of early molecular changes in Alzheimer's disease. Mol Diagn Ther 2014; 18:213-27. [PMID: 24281842 DOI: 10.1007/s40291-013-0069-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The preclinical phase of Alzheimer's disease (AD) occurs years, possibly decades, before the onset of clinical symptoms. Being able to detect the very earliest stages of AD is critical to improving understanding of AD biology, and identifying individuals at greatest risk of developing clinical symptoms with a view to treating AD pathophysiology before irreversible neurodegeneration occurs. Studies of dominantly inherited AD families and longitudinal studies of sporadic AD have contributed to knowledge of the earliest AD biomarkers. Here we appraise this evidence before reviewing novel, particularly fluid, biomarkers that may provide insights into AD pathogenesis and relate these to existing hypothetical disease models.
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Affiliation(s)
- Ross W Paterson
- Dementia Research Centre, Department of Neurodegeneration, UCL Institute of Neurology, London, UK,
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36
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Sotolongo-Grau O, Pesini P, Valero S, Lafuente A, Buendía M, Pérez-Grijalba V, José IS, Ibarria M, Tejero MA, Giménez J, Hernández I, Tárraga L, Ruiz A, Boada M, Sarasa M. Association between cell-bound blood amyloid-β(1-40) levels and hippocampus volume. ALZHEIMERS RESEARCH & THERAPY 2014; 6:56. [PMID: 25484928 PMCID: PMC4255526 DOI: 10.1186/s13195-014-0056-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2014] [Accepted: 08/04/2014] [Indexed: 12/22/2022]
Abstract
INTRODUCTION The identification of early, preferably presymptomatic, biomarkers and true etiologic factors for Alzheimer's disease (AD) is the first step toward establishing effective primary and secondary prevention programs. Consequently, the search for a relatively inexpensive and harmless biomarker for AD continues. Despite intensive research worldwide, to date there is no definitive plasma or blood biomarker indicating high or low risk of conversion to AD. METHODS Magnetic resonance imaging and β-amyloid (Aβ) levels in three blood compartments (diluted in plasma, undiluted in plasma and cell-bound) were measured in 96 subjects (33 with mild cognitive impairment, 14 with AD and 49 healthy controls). Pearson correlations were completed between 113 regions of interest (ROIs) (45 subcortical and 68 cortical) and Aβ levels. Pearson correlation analyses adjusted for the covariates age, sex, apolipoprotein E (ApoE), education and creatinine levels showed neuroimaging ROIs were associated with Aβ levels. Two statistical methods were applied to study the major relationships identified: (1) Pearson correlation with phenotype added as a covariate and (2) a meta-analysis stratified by phenotype. Neuroimaging data and plasma Aβ measurements were taken from 630 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects to be compared with our results. RESULTS The left hippocampus was the brain region most correlated with Aβ(1-40) bound to blood cell pellets (partial correlation (pcor) = -0.37, P = 0.0007) after adjustment for the covariates age, gender and education, ApoE and creatinine levels. The correlation remained almost the same (pcor = -0.35, P = 0.002) if phenotype is also added as a covariate. The association between both measurements was independent of cognitive status. The left hemisphere entorhinal cortex also correlated with Aβ(1-40) cell-bound fraction. AB128 and ADNI plasma Aβ measurements were not related to any brain morphometric measurement. CONCLUSIONS Association of cell-bound Aβ(1-40) in blood with left hippocampal volume was much stronger than previously observed in Aβ plasma fractions. If confirmed, this observation will require careful interpretation and must be taken into account for blood amyloid-based biomarker development.
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Affiliation(s)
- Oscar Sotolongo-Grau
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Pedro Pesini
- Araclon Biotech Ltd, Via Hispanidad 21, Zaragoza, 50009, Spain
| | - Sergi Valero
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain ; Department of Psychiatry, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Passeig Vall d'Hebron, 119-129, Barcelona, 08035, Spain
| | - Asunción Lafuente
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Mar Buendía
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | | | - Itziar San José
- Araclon Biotech Ltd, Via Hispanidad 21, Zaragoza, 50009, Spain
| | - Marta Ibarria
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Miguel A Tejero
- Department of Diagnostic Imaging, Clínica Corachan, Buïgas, 19, Barcelona, 08017, Spain
| | - Joan Giménez
- Department of Diagnostic Imaging, Clínica Corachan, Buïgas, 19, Barcelona, 08017, Spain
| | - Isabel Hernández
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Lluís Tárraga
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Agustín Ruiz
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Mercé Boada
- Alzheimer Research Center and Memory Clinic, Fundació ACE Memory Clinic, Institut Català de Neurociències Aplicades, Marquès de Sentmenat, 57, Barcelona, 08029, Spain
| | - Manuel Sarasa
- Araclon Biotech Ltd, Via Hispanidad 21, Zaragoza, 50009, Spain
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Watt AD, Crespi GAN, Down RA, Ascher DB, Gunn A, Perez KA, McLean CA, Villemagne VL, Parker MW, Barnham KJ, Miles LA. Anti-Aβ antibody target engagement: a response to Siemers et al. Acta Neuropathol 2014; 128:611-4. [PMID: 25120193 DOI: 10.1007/s00401-014-1333-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2014] [Accepted: 08/07/2014] [Indexed: 10/24/2022]
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Perneczky R, Alexopoulos P. Cerebrospinal fluid BACE1 activity and markers of amyloid precursor protein metabolism and axonal degeneration in Alzheimer's disease. Alzheimers Dement 2014; 10:S425-S429.e1. [PMID: 24239250 PMCID: PMC4038661 DOI: 10.1016/j.jalz.2013.09.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Revised: 09/13/2013] [Accepted: 09/16/2013] [Indexed: 11/19/2022]
Abstract
OBJECTIVE The objective of this study was to assess cerebrospinal fluid (CSF) β-site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) activity in relation to Alzheimer's disease (AD) and to correlate the enzyme activity with protein markers of APP metabolism and axonal degeneration. METHODS BACE1 activity and protein concentrations were measured and analyzed in 342 participants of the Alzheimer's Disease Neuroimaging Initiative, including 99 normal control, 75 stable mild cognitive impairment (MCI), 87 progressive MCI, and 79 AD dementia cases. All statistical analyses were Bonferroni corrected for multiple comparisons. RESULTS No significant differences between controls and any of the three patient groups were detected for BACE1 activity and soluble APPβ (sAPPβ) concentrations in CSF. Significant correlations with BACE1 activity were found for CSF APPβ and total tau in all four groups and for CSF phosphorylated tau181 in all groups but the progressive MCI group. There were no correlations for CSF amyloid β (Aβ)1-42 or for plasma Aβ1-42 and Aβ1-40. CONCLUSIONS The consistent correlation between BACE1 activity and sAPPβ supports their role as biomarkers of target engagement in clinical trials on BACE1 inhibition.
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Affiliation(s)
- Robert Perneczky
- Neuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London, UK; West London Cognitive Disorders Treatment and Research Unit, West London Mental Health Trust, London, UK; Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany.
| | - Panagiotis Alexopoulos
- Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany
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Tzen KY, Yang SY, Chen TF, Cheng TW, Horng HE, Wen HP, Huang YY, Shiue CY, Chiu MJ. Plasma Aβ but not tau is related to brain PiB retention in early Alzheimer's disease. ACS Chem Neurosci 2014; 5:830-6. [PMID: 25054847 DOI: 10.1021/cn500101j] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Recent advances in biomarkers provide the possibility of early or preclinical diagnosis of Alzheimer's pathology. Currently, decreased levels of Aβ-42 and increased levels of tau proteins in cerebral spinal fluid are considered reliable biomarkers of Alzheimer's disease (AD); however, little evidence exists for the use of amyloid and tau protein levels in the plasma as useful biomarkers. We investigated the potential use of plasma biomarkers to diagnose AD and explored their relationships with brain Aβ deposition in amyloid imaging. We used an immunomagnetic reduction assay to measure the plasma levels of Aβ40, Aβ42, and tau proteins in 20 older control participants and 25 participants who had either mild cognitive impairment due to AD or early AD dementia. All participants received (11)C-labeled Pittsburgh compound B PET scans. The sensitivity of the plasma tau level at the cutoff value of 28.27 pg/mL was 92%, and the specificity was 100%; the sensitivity of the Aβ42/40 ratio at the cutoff value of 0.3693 was 84%, and the specificity was 100%. Regression analyses of the effects of plasma protein levels on brain amyloid retention, as determined by standard uptake value ratios in either side of the frontal, parietal, and temporal lobes and the precuneus, are predicted only by ratios of plasma Aβ42/40 (R(2) 0.326-0.449, all p < 0.001) but not by plasma tau levels. Plasma Aβ in terms of Aβ42/40 might provide an indirect estimation of Aβ deposition in the brain.
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Affiliation(s)
| | - Shieh-Yueh Yang
- Institute
of Electro-optical Science and Technology, National Taiwan Normal University, Taipei 10002, Taiwan
| | | | | | - Herng-Er Horng
- Institute
of Electro-optical Science and Technology, National Taiwan Normal University, Taipei 10002, Taiwan
| | | | | | - Chyng-Yann Shiue
- Department of Nuclear Medicine, PET Center, Tri-Service General Hospital, Taipei 11490, Taiwan
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40
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Wang T, Xiao S, Liu Y, Lin Z, Su N, Li X, Li G, Zhang M, Fang Y. The efficacy of plasma biomarkers in early diagnosis of Alzheimer's disease. Int J Geriatr Psychiatry 2014; 29:713-9. [PMID: 24318929 DOI: 10.1002/gps.4053] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Revised: 10/15/2013] [Accepted: 10/29/2013] [Indexed: 02/06/2023]
Abstract
BACKGROUND Early diagnosis of Alzheimer's disease (AD) is imperative for the prevention of disease progression and the development of effective treatments. OBJECTIVE Clinically, AD diagnosis has been based on adherence to clinical criteria. It has recently been proposed that diagnostic criteria should also incorporate biomarker findings. However, the most studied candidates or group of candidates for AD biomarkers, including pathological processes and proteins, needs further research. The current study aimed to investigate the capabilities of the following plasma proteins in the diagnosis of AD and amnesia mild cognitive impairment (aMCI): peripheral interleukin (IL) 10, IL-6, amyloid-β (Aβ) 40, Aβ42, phosphorylated tau 181, and total tau. METHODS In addition to 122 normal control (NC) group, 97 AD patients and 54 aMCI patients were recruited for this study. An enzyme-linked immunosorbent assay was used to analyze the concentration of the following blood plasma biomarkers: IL-10, IL-6, Aβ40, Aβ42, phosphorylated tau 181, and total tau. RESULTS A one-way analysis of variance (one-factor analysis of variance) of Aβ40 and IL-10 levels revealed a statistically significant difference between the three groups (p < 0.001 and p = 0.020). Using Aβ40 ≥ 42.70 pg/ml as the cut-off point, the sensitivity of the ability of Aβ40 to discriminate between AD and NC groups was 80.0%, and specificity was 69.6%. CONCLUSIONS The plasma Aβ40 biomarker was able to distinguish between AD and NC groups. However, the plasma biomarkers in the present research were not able to distinguish between aMCI and NC groups.
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Affiliation(s)
- Tao Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
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41
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Toledo JB, Da X, Weiner MW, Wolk DA, Xie SX, Arnold SE, Davatzikos C, Shaw LM, Trojanowski JQ. CSF Apo-E levels associate with cognitive decline and MRI changes. Acta Neuropathol 2014; 127:621-32. [PMID: 24385135 DOI: 10.1007/s00401-013-1236-0] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2013] [Revised: 12/16/2013] [Accepted: 12/17/2013] [Indexed: 12/31/2022]
Abstract
Apolipoprotein E (APOE) ε4 allele is the most important genetic risk factor for Alzheimer's disease (AD) and it is thought to do so by modulating levels of its product, apolipoprotein E (Apo-E), and regulating amyloid-β (Aβ) clearance. However, information on clinical and biomarker correlates of Apo-E proteins is scarce. We examined the relationship of cerebrospinal fluid (CSF) and plasma Apo-E protein levels, and APOE genotype to cognition and AD biomarker changes in 311 AD neuroimaging initiative subjects with CSF Apo-E measurements and 565 subjects with plasma Apo-E measurements. At baseline, higher CSF Apo-E levels were associated with higher total and phosphorylated CSF tau levels. CSF Apo-E levels were associated with longitudinal cognitive decline, MCI conversion to dementia, and gray matter atrophy rate in total tau/Aβ1-42 ratio and APOE genotype-adjusted analyses. In analyses stratified by APOE genotype, our results were only significant in the group without the ε4 allele. Baseline CSF Apo-E levels did not predict longitudinal CSF Aβ or tau changes. Plasma Apo-E levels show a mild correlation with CSF Apo-E levels, but were not associated with longitudinal cognitive and MRI changes. Based on our analyses, we speculate that increased CSF Apo-E2 or -E3 levels might represent a protective response to injury in AD and may have neuroprotective effects by decreasing neuronal damage independent of tau and amyloid deposition in addition to its effects on amyloid clearance.
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Affiliation(s)
- Jon B Toledo
- Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, HUP, Maloney 3rd, 36th and Spruce Streets, Philadelphia, PA, 19104-4283, USA
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42
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KANEKO N, NAKAMURA A, WASHIMI Y, KATO T, SAKURAI T, ARAHATA Y, BUNDO M, TAKEDA A, NIIDA S, ITO K, TOBA K, TANAKA K, YANAGISAWA K. Novel plasma biomarker surrogating cerebral amyloid deposition. PROCEEDINGS OF THE JAPAN ACADEMY. SERIES B, PHYSICAL AND BIOLOGICAL SCIENCES 2014; 90:353-64. [PMID: 25391320 PMCID: PMC4324927 DOI: 10.2183/pjab.90.353] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Alzheimer's disease (AD) is the most common and devastating dementia. Simple and practical biomarkers for AD are urgently required for accurate diagnosis and to facilitate the development of disease-modifying interventions. The subjects for the study were selected on the basis of PiB amyloid imaging by PET. Forty PiB-positive (PiB+) individuals, including cognitively healthy controls (HC), and mild cognitive impairment and AD individuals, and 22 PiB-negative (PiB-) HC participated. Employing our novel highly sensitive immunoprecipitation-mass spectrometry, we measured plasma amyloid β-proteins (Aβs; Aβ1-40 and Aβ1-42) and Aβ-approximate peptides (AβAPs), which were cleaved from amyloid precursor protein (APP). Among the AβAPs, APP669-711 appeared to be a good reference for deciphering pathological change of Aβ1-42. We evaluated the performance of the ratio of APP669-711 to Aβ1-42 (APP669-711/Aβ1-42) as a biomarker. APP669-711/Aβ1-42 significantly increased in the PiB+ groups. The sensitivity and specificity to discriminate PiB+ individuals from PiB- individuals were 0.925 and 0.955, respectively. Our plasma biomarker precisely surrogates cerebral amyloid deposition.
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Affiliation(s)
- Naoki KANEKO
- Koichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Kyoto, Japan
| | - Akinori NAKAMURA
- Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yukihiko WASHIMI
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Takashi KATO
- Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Takashi SAKURAI
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yutaka ARAHATA
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Masahiko BUNDO
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Akinori TAKEDA
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shumpei NIIDA
- BioBank, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Kengo ITO
- Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Kenji TOBA
- Hospital, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Koichi TANAKA
- Koichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Kyoto, Japan
| | - Katsuhiko YANAGISAWA
- Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan
- Correspondence should be addressed: K. Yanagisawa, Department of Alzheimer’s Disease Research, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, 35 Gengo, Morioka, Obu, Aichi 474-8522, Japan (e-mail: )
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Swaminathan S, Risacher SL, Yoder KK, West JD, Shen L, Kim S, Inlow M, Foroud T, Jagust WJ, Koeppe RA, Mathis CA, Shaw LM, Trojanowski JQ, Soares H, Aisen PS, Petersen RC, Weiner MW, Saykin AJ. Association of plasma and cortical amyloid beta is modulated by APOE ε4 status. Alzheimers Dement 2014; 10:e9-e18. [PMID: 23541187 PMCID: PMC3750076 DOI: 10.1016/j.jalz.2013.01.007] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2012] [Revised: 01/10/2013] [Accepted: 01/16/2013] [Indexed: 10/27/2022]
Abstract
BACKGROUND Apolipoprotein E (APOE) ε4 allele's role as a modulator of the relationship between soluble plasma amyloid beta (Aβ) and fibrillar brain Aβ measured by Pittsburgh compound B positron emission tomography ([(11)C]PiB PET) has not been assessed. METHODS Ninety-six Alzheimer's Disease Neuroimaging Initiative participants with [(11)C]PiB scans and plasma Aβ1-40 and Aβ1-42 measurements at the time of PET scanning were included. Regional and voxelwise analyses of [(11)C]PiB data were used to determine the influence of APOE ε4 allele on association of plasma Aβ1-40, Aβ1-42, and Aβ1-40/Aβ1-42 with [(11)C]PiB uptake. RESULTS In APOE ε4- but not ε4+ participants, positive relationships between plasma Aβ1-40/Aβ1-42 and [(11)C]PiB uptake were observed. Modeling the interaction of APOE and plasma Aβ1-40/Aβ1-42 improved the explained variance in [(11)C]PiB binding compared with using APOE and plasma Aβ1-40/Aβ1-42 as separate terms. CONCLUSIONS The results suggest that plasma Aβ is a potential Alzheimer's disease biomarker and highlight the importance of genetic variation in interpretation of plasma Aβ levels.
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Affiliation(s)
- Shanker Swaminathan
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Karmen K Yoder
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - John D West
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Li Shen
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sungeun Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Mark Inlow
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Mathematics, Rose-Hulman Institute of Technology, Terre Haute, IN, USA
| | - Tatiana Foroud
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, USA
| | - Robert A Koeppe
- Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | | - Paul S Aisen
- Department of Neurosciences, University of California at San Diego, San Diego, CA, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Liu E, Morris JC, Petersen RC, Saykin AJ, Schmidt ME, Shaw L, Shen L, Siuciak JA, Soares H, Toga AW, Trojanowski JQ. The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement 2013; 9:e111-94. [PMID: 23932184 DOI: 10.1016/j.jalz.2013.05.1769] [Citation(s) in RCA: 317] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/19/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA.
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Oligomers, fact or artefact? SDS-PAGE induces dimerization of β-amyloid in human brain samples. Acta Neuropathol 2013; 125:549-64. [PMID: 23354835 DOI: 10.1007/s00401-013-1083-z] [Citation(s) in RCA: 70] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2012] [Accepted: 01/16/2013] [Indexed: 12/14/2022]
Abstract
The formation of low-order oligomers of β-amyloid (Aβ) within the brain is widely believed to be a central component of Alzheimer's disease (AD) pathogenesis. However, despite advances in high-throughput and high-resolution techniques such as xMAP and mass spectrometry (MS), investigations into these oligomeric species have remained reliant on low-resolution Western blots and enzyme-linked immunosorbent assays. The current investigation compared Aβ profiles within human cortical tissue using sodium dodecyl sulphate (SDS) polyacrylamide gel electrophoresis (PAGE), xMAP and surface enhanced laser desorption/ionization time-of-flight MS and found that whilst there was significant correlation across the techniques regarding levels of monomeric Aβ, only SDS-PAGE was capable of detecting dimeric isoforms of Aβ. The addition of synthetic di-tyrosine cross-linked Aβ(1-40)Met(35)(O) to the AD tissue demonstrated that the MS methodology was capable of observing dimeric Aβ at femto-molar concentrations, with no noticeable effect on monomeric Aβ levels. Focus turned to the association between SDS-PAGE and levels of observable dimeric Aβ within the AD brain tissue. These investigations revealed that increased levels of dimeric Aβ were observed with increasing concentrations of SDS in the sample buffer. This finding was subsequently confirmed using synthetic Aβ(1-42) and suggests that SDS was inducing the formation of dimeric Aβ. The findings that SDS promotes Aβ dimerization have significant implications for the putative role of low-order oligomers in AD pathogenesis and draw into question the utility of oligomeric Aβ as a therapeutic target.
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Rembach A, Faux NG, Watt AD, Pertile KK, Rumble RL, Trounson BO, Fowler CJ, Roberts BR, Perez KA, Li QX, Laws SM, Taddei K, Rainey-Smith S, Robertson JS, Vandijck M, Vanderstichele H, Barnham KJ, Ellis KA, Szoeke C, Macaulay L, Rowe CC, Villemagne VL, Ames D, Martins RN, Bush AI, Masters CL. Changes in plasma amyloid beta in a longitudinal study of aging and Alzheimer's disease. Alzheimers Dement 2013; 10:53-61. [PMID: 23491263 DOI: 10.1016/j.jalz.2012.12.006] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2012] [Revised: 10/19/2012] [Accepted: 12/08/2012] [Indexed: 12/28/2022]
Abstract
BACKGROUND A practical biomarker is required to facilitate the preclinical diagnosis of Alzheimer's disease (AD). METHODS Plasma amyloid beta (Aβ)1-40, Aβ1-42, Aβn-40, and Aβn-42 peptides were measured at baseline and after 18 months in 771 participants from the Australian Imaging Biomarkers and Lifestyle (AIBL) study of aging. Aβ peptide levels were compared with clinical pathology, neuroimaging and neuropsychological measurements. RESULTS Although inflammatory and renal function covariates influenced plasma Aβ levels significantly, a decrease in Aβ1-42/Aβ1-40 was observed in patients with AD, and was also inversely correlated with neocortical amyloid burden. During the 18 months, plasma Aβ1-42 decreased in subjects with mild cognitive impairment (MCI) and in those transitioning from healthy to MCI. CONCLUSION Our findings are consistent with a number of published plasma Aβ studies and, although the prognostic value of individual measures in any given subject is limited, the diagnostic contribution of plasma Aβ may demonstrate utility when combined with a panel of peripheral biomarkers.
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Affiliation(s)
- Alan Rembach
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia.
| | - Noel G Faux
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Andrew D Watt
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Kelly K Pertile
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Rebecca L Rumble
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Brett O Trounson
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Christopher J Fowler
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Blaine R Roberts
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Keyla A Perez
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Qiao-Xin Li
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Simon M Laws
- Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital), Perth, Western Australia, Australia; Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup. Western Australia, Australia
| | - Kevin Taddei
- Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital), Perth, Western Australia, Australia; Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup. Western Australia, Australia
| | - Stephanie Rainey-Smith
- Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital), Perth, Western Australia, Australia; Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup. Western Australia, Australia
| | - Joanne S Robertson
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Manu Vandijck
- Department of Diagnostic Development, Innogenetics NV, Ghent, Belgium
| | - Hugo Vanderstichele
- Department of Diagnostic Development, Innogenetics NV, Ghent, Belgium; Biomarkable, Gent, Belgium
| | - Kevin J Barnham
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Kathryn A Ellis
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia; Department of Psychiatry, St George's Hospital, University of Melbourne, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Cassandra Szoeke
- Department of Psychiatry, St George's Hospital, University of Melbourne, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Lance Macaulay
- CSIRO Molecular and Health Technologies, Parkville, Victoria, Australia
| | - Christopher C Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Victor L Villemagne
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia; Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia
| | - Ralph N Martins
- Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital), Perth, Western Australia, Australia; Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup. Western Australia, Australia
| | - Ashley I Bush
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
| | - Colin L Masters
- The Mental Health Research Institute, The University of Melbourne, Victoria, Australia
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Toledo JB, Shaw LM, Trojanowski JQ. Plasma amyloid beta measurements - a desired but elusive Alzheimer's disease biomarker. ALZHEIMERS RESEARCH & THERAPY 2013; 5:8. [PMID: 23470128 PMCID: PMC3706955 DOI: 10.1186/alzrt162] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Cerebrospinal fluid and positron emission tomography biomarkers accurately predict an underlying Alzheimer's disease (AD) pathology; however, they represent either invasive or expensive diagnostic tools. Therefore, a blood-based biomarker like plasma amyloid beta (Aβ) that could correlate with the underlying AD pathology and serve as a prognostic biomarker or an AD screening strategy is urgently needed as a cost-effective and non-invasive diagnostic tool. In this paper we review the demographic, biologic, genetic and technical aspects that affect plasma Aβ levels. Findings of cross-sectional and longitudinal studies of plasma Aβ, including autosomal dominant AD cases, sporadic AD cases, Down syndrome cases and population studies, are also discussed. Finally, we review the association between cerebrovascular disease and Aβ plasma levels and the responses observed in clinical trials. Based on our review of the current literature on plasma Aβ, we conclude that further clinical research and assay development are needed before measures of plasma Aβ can be interpreted so they can be applied as trait, risk or state biomarkers for AD.
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Affiliation(s)
- Jon B Toledo
- Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
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Amyloid plaque pathogenesis in 5XFAD mouse spinal cord: retrograde transneuronal modulation after peripheral nerve injury. Neurotox Res 2012; 24:1-14. [PMID: 23055086 DOI: 10.1007/s12640-012-9355-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2012] [Revised: 09/14/2012] [Accepted: 09/26/2012] [Indexed: 12/25/2022]
Abstract
The spinal cord is composed of distinct neuronal groups with well-defined anatomic connections. In some transgenic (Tg) models of Alzheimer's disease (AD), amyloid plaques develop in this structure, although the underlying cellular mechanism remains elusive. We attempted to explore the origin, evolution, and modulation of spinal β-amyloid (Aβ) deposition using Tg mice harboring five familiar AD-related mutations (5XFAD) as an experiential model. Dystrophic neuritic elements with enhanced β-secretase-1 (BACE1) immunoreactivity (IR) appeared as early as 2 months of age, and increased with age up to 12 months examined in this study, mostly over the ventral horn (VH). Extracellular Aβ IR emerged and developed during this same period, site-specifically co-existing with BACE1-labeled neurites often in the vicinity of large VH neurons that expressed the mutant human APP. The BACE1-labeled neurites almost invariably colocalized with β-amyloid precursor protein (APP) and synaptophysin, and frequently with the vesicular glutamate transporter-1 (VGLUT). Reduced IR for the neuronal-specific nuclear antigen (NeuN) occurred in the VH by 12 months of age. In 8-month-old animals surviving 6 months after a unilateral sciatic nerve transection, there were significant increases of Aβ, BACE1, and VGLUT IR in the VN of the ipsilateral relative to contralateral lumbar spinal segments. These results suggest that extracellular Aβ deposition in 5XFAD mouse spinal cord relates to a progressive and amyloidogenic synaptic pathology largely involving presynaptic axon terminals from projection neurons in the brain. Spinal neuritic plaque formation is enhanced after peripheral axotomy, suggesting a retrograde transneuronal modulation on pathogenesis.
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Rissman RA, Trojanowski JQ, Shaw LM, Aisen PS. Longitudinal plasma amyloid beta as a biomarker of Alzheimer's disease. J Neural Transm (Vienna) 2012; 119:843-50. [PMID: 22354745 PMCID: PMC4305447 DOI: 10.1007/s00702-012-0772-4] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2011] [Accepted: 01/31/2012] [Indexed: 01/07/2023]
Abstract
Alzheimer's disease (AD) affects more than twenty-five million people worldwide and is the most common form of dementia. Symptomatic treatments have been developed, but effective intervention to alter disease progression is needed. Targets have been identified for disease-modifying drugs, but the results of clinical trials have been disappointing. Peripheral biomarkers of disease state may improve clinical trial design and analysis, increasing the likelihood of successful drug development. Amyloid-related measures, presumably reflecting principal pathology of AD, are among the leading cerebrospinal fluid and neuroimaging biomarkers, and measurement of plasma levels of amyloid peptides has been the focus of much investigation. In this review, we discuss recent data on plasma β-amyloid (Aβ) and examine the issues that have arisen in establishing it as a reliable biomarker of AD.
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Affiliation(s)
- Robert A Rissman
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, UCSD School of Medicine, La Jolla, CA 92037-0624, USA.
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