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Rudolph MD, Sutphen CL, Register TC, Whitlow CT, Solingapuram Sai KK, Hughes TM, Bateman JR, Dage JL, Russ KA, Mielke MM, Craft S, Lockhart SN. Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort. Alzheimers Dement 2024; 20:4159-4173. [PMID: 38747525 PMCID: PMC11180870 DOI: 10.1002/alz.13835] [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: 11/08/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 06/05/2024]
Abstract
INTRODUCTION We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. METHODS We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). RESULTS Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. DISCUSSION eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. HIGHLIGHTS Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.
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Affiliation(s)
- Marc D. Rudolph
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Courtney L. Sutphen
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Thomas C. Register
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Christopher T. Whitlow
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Kiran K. Solingapuram Sai
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James R. Bateman
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jeffrey L. Dage
- Department Of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kristen A. Russ
- Department Of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Michelle M. Mielke
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Suzanne Craft
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samuel N. Lockhart
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
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Bucci M, Bluma M, Savitcheva I, Ashton NJ, Chiotis K, Matton A, Kivipelto M, Di Molfetta G, Blennow K, Zetterberg H, Nordberg A. Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic. Transl Psychiatry 2023; 13:268. [PMID: 37491358 PMCID: PMC10368630 DOI: 10.1038/s41398-023-02558-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023] Open
Abstract
Plasma biomarkers have shown promising performance in research cohorts in discriminating between different stages of Alzheimer's disease (AD). Studies in clinical populations are necessary to provide insights on the clinical utility of plasma biomarkers before their implementation in real-world settings. Here we investigated plasma biomarkers (glial fibrillary acidic protein (GFAP), tau phosphorylated at 181 and 231 (pTau181, pTau231), amyloid β (Aβ) 42/40 ratio, neurofilament light) in 126 patients (age = 65 ± 8) who were admitted to the Clinic for Cognitive Disorders, at Karolinska University Hospital. After extensive clinical assessment (including CSF analysis), patients were classified as: mild cognitive impairment (MCI) (n = 75), AD (n = 25), non-AD dementia (n = 16), no dementia (n = 9). To refine the diagnosis, patients were examined with [18F]flutemetamol PET (Aβ-PET). Aβ-PET images were visually rated for positivity/negativity and quantified in Centiloid. Accordingly, 68 Aβ+ and 54 Aβ- patients were identified. Plasma biomarkers were measured using single molecule arrays (SIMOA). Receiver-operated curve (ROC) analyses were performed to detect Aβ-PET+ using the different biomarkers. In the whole cohort, the Aβ-PET centiloid values correlated positively with plasma GFAP, pTau231, pTau181, and negatively with Aβ42/40 ratio. While in the whole MCI group, only GFAP was associated with Aβ PET centiloid. In ROC analyses, among the standalone biomarkers, GFAP showed the highest area under the curve discriminating Aβ+ and Aβ- compared to other plasma biomarkers. The combination of plasma biomarkers via regression was the most predictive of Aβ-PET, especially in the MCI group (prior to PET, n = 75) (sensitivity = 100%, specificity = 82%, negative predictive value = 100%). In our cohort of memory clinic patients (mainly MCI), the combination of plasma biomarkers was sensitive in ruling out Aβ-PET negative individuals, thus suggesting a potential role as rule-out tool in clinical practice.
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Affiliation(s)
- Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, SE-14186, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Anna Matton
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden.
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Payne T, Taylor J, Casey C, Kunkel D, Parker M, Blennow K, Zetterberg H, Pearce RA, Lennertz RC, Sanders RD. Prospective analysis of plasma amyloid beta and postoperative delirium in the Interventions for Postoperative Delirium: Biomarker-3 study. Br J Anaesth 2023; 130:546-556. [PMID: 36842841 PMCID: PMC10273086 DOI: 10.1016/j.bja.2023.01.020] [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: 09/19/2022] [Revised: 01/03/2023] [Accepted: 01/15/2023] [Indexed: 02/28/2023] Open
Abstract
BACKGROUND The effect of postoperative delirium on the amyloid cascade of Alzheimer's dementia is poorly understood. Using early postoperative plasma biomarkers, we explored whether surgery and delirium are associated with changes in amyloid pathways. METHODS We analysed data from 100 participants in the Interventions for Postoperative Delirium: Biomarker-3 (IPOD-B3) cohort study in the USA (NCT03124303 and NCT01980511), which recruited participants aged >65 yr undergoing non-intracranial surgery. We assessed the relationship between the change in plasma amyloid beta ratio (AβR; Aβ42:Aβ40) and delirium incidence (defined by the 3-Minute Diagnostic Confusion Assessment Method) and severity (quantified by the Delirium Rating Scale-Revised-98, the study's primary outcome). We also tested the relationship between plasma amyloid beta and intraoperative variables. RESULTS Across all participants, the plasma AβR increased from the preoperative period to postoperative Day 1 (Wilcoxon P<0.001). However, this increase was not associated with delirium incidence (Wilcoxon P=0.22) or peak severity after adjusting for confounders (log[incidence rate ratio]=0.43; P=0.14). Postoperative Day 1 change in plasma AβR was not associated with postoperative Day 1 change in plasma tau, neurofilament light, or inflammatory markers (interleukin [IL]-1β, IL-1Ra, IL-2, IL-4, IL-6, IL-8, IL-10, and IL-12), or with operative time or low intraoperative arterial pressure. CONCLUSIONS Perioperative changes in plasma amyloid do not appear to be associated with postoperative delirium. Our findings do not support associations of dynamic changes in amyloid with postoperative delirium. CLINICAL TRIAL REGISTRATION .NCT03124303 and NCT01980511.
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Affiliation(s)
- Thomas Payne
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia
| | - Jennifer Taylor
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia
| | - Cameron Casey
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - David Kunkel
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Maggie Parker
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Robert A Pearce
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard C Lennertz
- Department of Anesthesiology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Robert D Sanders
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Department of Anaesthetics, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia; Institute of Academic Surgery, Royal Prince Alfred Hospital, Sydney Local Health District, Sydney, NSW, Australia; NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
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Sapkota S, Erickson K, Fletcher E, Tomaszewski Farias SE, Jin LW, DeCarli C. Vascular Risk Predicts Plasma Amyloid β 42/40 Through Cerebral Amyloid Burden in Apolipoprotein E ε4 Carriers. Stroke 2023; 54:1227-1235. [PMID: 37021572 PMCID: PMC10121244 DOI: 10.1161/strokeaha.122.041854] [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: 11/02/2022] [Revised: 02/28/2023] [Accepted: 03/08/2023] [Indexed: 04/07/2023]
Abstract
BACKGROUND Understanding the neurobiological underpinnings between established multimodal dementia risk factors and noninvasive blood-based biomarkers may lead to greater precision and earlier identification of older adults at risk of accelerated decline and dementia. We examined whether key vascular and genetic risk impact the association between cerebral amyloid burden and plasma aβ (amyloid β) 42/40 in nondemented older adults. METHODS We used nondemented older adults from the UCD-ADRC (University of California, Davis-Alzheimer's Disease Research Center) study (n=96) and Alzheimer's Disease Neuroimaging Initiative (n=104). Alzheimer's Disease Neuroimaging Initiative was examined as confirmatory study cohort. We followed a cross-sectional design and examined linear regression followed by mediation analyses. Vascular risk score was obtained as the sum of hypertension, diabetes, hyperlipidemia, coronary artery disease, and cerebrovascular disease. Apolipoprotein E (APOE) ε4+ risk was genotyped, and plasma aβ42 and aβ40 were assayed. Cerebral amyloid burden was quantified using Florbetapir-PET scans. Baseline age was included as a covariate in all models. RESULTS Vascular risk significantly predicted cerebral amyloid burden in Alzheimer's Disease Neuroimaging Initiative but not in the UCD-ADRC cohort. Cerebral amyloid burden was associated with plasma aβ 42/40 in both cohorts. Higher vascular risk increased cerebral amyloid burden was indirectly associated with reduced plasma aβ 42/40 in Alzheimer's Disease Neuroimaging Initiative but not in UCD-ADRC cohort. However, when stratified by APOE ε4+ risk, we consistently observed this indirect relationship only in APOE ε4+ carriers across both cohorts. CONCLUSIONS Vascular risk is indirectly associated with the level of plasma aβ 42/40 via cerebral amyloid burden only in APOE ε4+ carriers. Nondemented older adults with genetic vulnerability to dementia and accelerated decline may benefit from careful monitoring of vascular risk factors directly associated with cerebral amyloid burden and indirectly with plasma aβ 42/40.
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Affiliation(s)
- Shraddha Sapkota
- Department of Neurology (S.S., E.F., S.E.T.F., C.D.), University of California, Davis
| | - Kelsey Erickson
- Department of Neurology (S.S., E.F., S.E.T.F., C.D.), University of California, Davis
| | - Evan Fletcher
- University of California, and Department of Pathology and Laboratory Medicine (K.E., L.-W.J.), University of California, Davis
| | | | - Lee-Way Jin
- University of California, and Department of Pathology and Laboratory Medicine (K.E., L.-W.J.), University of California, Davis
| | - Charles DeCarli
- Department of Neurology (S.S., E.F., S.E.T.F., C.D.), University of California, Davis
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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: 17] [Impact Index Per Article: 8.5] [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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Heshmatollah A, Fani L, Koudstaal PJ, Ghanbari M, Ikram MA, Ikram MK. Plasma Amyloid Beta, Total-Tau and Neurofilament Light Chain Levels and the Risk of Stroke: A Prospective Population-Based Study. Neurology 2022; 98:e1729-e1737. [PMID: 35232820 DOI: 10.1212/wnl.0000000000200004] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 01/03/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To unravel whether Alzheimer's disease-related pathology or neurodegeneration play a role in stroke etiology, we determined the effect of plasma levels amyloid β (Aβ), total-tau and neurofilament light chain (NfL) on risk of stroke and its subtypes. METHODS Between 2002 and 2005, we measured plasma Aβ40, Aβ42, total-tau, and NfL in 4,661 stroke-free participants from the population-based Rotterdam Study. We used Cox proportional-hazards models to determine the association between these markers with incident stroke for the entire cohort, per stroke subtype, and by median age, sex, Apolipoprotein E (APOE) ε4 carriership, and education. RESULTS After a mean follow-up of 10.8 ± 3.3 years, 379 participants suffered a first-ever stroke. Log2 total-tau at baseline showed a non-linear association with risk of any stroke and ischemic stroke: compared to the first (lowest) quartile the adjusted hazard ratio for the highest quartile total-tau was 1.68, 95% CI: 1.18-2.40 for any stroke. Log2 NfL was associated with an increased risk of any stroke (HR per SD increase 1.27, 95% CI: 1.12-1.44), ischemic stroke, and hemorrhagic stroke (HR 1.56, 95% CI: 1.14-2.12). Log2 Aβ40, Aβ42, and Aβ42/40 ratio levels were not associated with stroke risk.Discussion Participants with higher total-tau and NfL at baseline had a higher risk of stroke and several stroke subtypes. These findings support the role of markers of neurodegeneration in the etiology of stroke. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that higher plasma levels of total-tau and NfL are associated with an increased risk of subsequent stroke.
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Affiliation(s)
- Alis Heshmatollah
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Lana Fani
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Peter J Koudstaal
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
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Leuzy A, Mattsson‐Carlgren N, Palmqvist S, Janelidze S, Dage JL, Hansson O. Blood-based biomarkers for Alzheimer's disease. EMBO Mol Med 2022; 14:e14408. [PMID: 34859598 PMCID: PMC8749476 DOI: 10.15252/emmm.202114408] [Citation(s) in RCA: 119] [Impact Index Per Article: 59.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 11/02/2021] [Accepted: 11/05/2021] [Indexed: 12/01/2022] Open
Abstract
Neurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever-increasing role in research, clinical trials, and in the clinical work-up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)-based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra-sensitive assays, the levels of pathological brain- and AD-related proteins can now be measured in blood, with recent work showing promising results. Plasma P-tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD-specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease-modifying therapies. This review provides an overview of the progress achieved thus far using AD blood-based biomarkers, highlighting key areas of application and unmet challenges.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
| | - Niklas Mattsson‐Carlgren
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Department of NeurologySkåne University HospitalLundSweden
- Wallenberg Centre for Molecular MedicineLund UniversityLundSweden
| | - Sebastian Palmqvist
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Shorena Janelidze
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
| | - Jeffrey L Dage
- Stark Neuroscience Research InstituteIndiana University School of MedicineIndianapolisINUSA
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalLundSweden
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Bogolepova A, Makhnovich E, Kovalenko E, Osinovskaya N. Potential biomarkers of early diagnosis of Alzheimer’s disease. Zh Nevrol Psikhiatr Im S S Korsakova 2022; 122:7-14. [DOI: 10.17116/jnevro20221220917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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10
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She M, Shang S, Hu N, Chen C, Dang L, Gao L, Wei S, Huo K, Wang J, Wang J, Qu Q. Blood Pressure Level Is Associated With Changes in Plasma Aβ 1 -40 and Aβ 1-42 Levels: A Cross-sectional Study Conducted in the Suburbs of Xi'an, China. Front Aging Neurosci 2021; 13:650679. [PMID: 34149395 PMCID: PMC8211897 DOI: 10.3389/fnagi.2021.650679] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 05/06/2021] [Indexed: 11/23/2022] Open
Abstract
Objectives: Amyloid-β (Aβ) deposition in the brain is the hallmark of Alzheimer’s disease (AD) pathology. Hypertension is a risk factor for AD, but the effects of hypertension on Aβ deposition are not fully determined. Considering peripheral Aβ closely relates to Aβ deposition in the brain, we investigated the relationships between blood pressure (BP) level and plasma Aβ concentrations. Methods: One-thousand and sixty-nine participants (age above 45) from a village in the suburbs of Xi’an, China were enrolled. Questionnaires and validated Chinese versions of the Mini-Mental State Examination (MMSE) were used to collect information about vascular risk factors and assess cognition function. The apolipoprotein E (ApoE) genotype was detected using PCR and sequencing. Plasma Aβ levels were measured using ELISA. The associations between BP and plasma Aβ levels were analyzed by using multivariate linear regression. Results: Plasma Aβ1–40 level was higher in high BP group than that in normal BP group (53.34 ± 8.50 pg/ml vs. 51.98 ± 8.96 pg/ml, P = 0.013), in high SBP group than that in normal SBP group (53.68 ± 8.69 pg/ml vs. 51.88 ± 8.80 pg/ml, P = 0.001) and in high MABP group than that in normal MABP group (54.05 ± 8.78 pg/ml vs. 52.04 ± 8.75 pg/ml, P = 0.001). After controlling for the confounding factors, SBP (b = 0.078, P < 0.001), DBP (b = 0.090, P = 0.008) and MABP (b = 0.104, P < 0.001) correlated with plasma Aβ1–40 level positively in ApoE ε4 non-carriers, but not ApoE ε4 carriers. Conclusions: Elevated BP levels were associated with increased plasma Aβ1–40 levels in middle-aged and elderly ApoE ε4 non-carriers.
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Affiliation(s)
- Meilin She
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Neurology, Yulin Hospital of Traditional Chinese Medicine, Shaanxi, China
| | - Suhang Shang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ningwei Hu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chen Chen
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Liangjun Dang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ling Gao
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shan Wei
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kang Huo
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jingyi Wang
- Huyi Hospital of Traditional Chinese Medicine, Xi'an, China
| | - Jin Wang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qiumin Qu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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11
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Raffin J, Rolland Y, Aggarwal G, Nguyen AD, Morley JE, Li Y, Bateman RJ, Vellas B, Barreto PDS. Associations Between Physical Activity, Blood-Based Biomarkers of Neurodegeneration, and Cognition in Healthy Older Adults: The MAPT Study. J Gerontol A Biol Sci Med Sci 2021; 76:1382-1390. [PMID: 33864068 DOI: 10.1093/gerona/glab094] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Indexed: 01/12/2023] Open
Abstract
Physical activity (PA) demonstrated benefits on brain health, but its relationship with blood biomarkers of neurodegeneration remains poorly investigated. We explored the cross-sectional associations of PA with blood concentrations of neurofilament light chain (NFL) and beta amyloid (Aβ)42/40. We further examined whether the interaction between PA and these biomarkers was longitudinally related to cognition. Four-hundred and sixty-five nondemented older adults engaged in an interventional study and who had a concomitant assessment of PA levels and blood measurements of NFL (pg/mL) and Aβ 42/40 were analyzed. A composite Z-score combining 4 cognitive tests was used for cognitive assessment up to a 4-year follow-up. Multiple linear regressions demonstrated that people achieving 500-999 and 2000+ MET-min/week of PA had lower (ln)NFL concentrations than their inactive peers. Logistic regressions revealed that achieving at least 90 MET-min/week of PA was associated with a lower probability of having high NFL concentrations (ie, ≥91.961 pg/mL [third quartile]). PA was not associated with (Aβ)42/40. Mixed-model linear regressions demonstrated that the reverse relationship between PA and cognitive decline tended to be more pronounced as Aβ 42/40 increased, while it was dampened with increasing levels of (ln)NFL concentrations. This study demonstrates that PA is associated with blood NFL but not with Aβ 42/40. Furthermore, it suggests that PA may attenuate the negative association between amyloid load and cognition, while having high NFL levels mitigates the favorable relationship between PA and cognition. More investigations on non demented older adults are required for further validation of the present findings.
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Affiliation(s)
- Jérémy Raffin
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, France
| | - Yves Rolland
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, France.,UMR INSERM, 1027 University of Toulouse III and Faculté de Médecine, France
| | - Geetika Aggarwal
- Division of Geriatric Medicine, Saint Louis University School of Medicine, Missouri, USA.,Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, Missouri, USA
| | - Andrew D Nguyen
- Division of Geriatric Medicine, Saint Louis University School of Medicine, Missouri, USA.,Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, Missouri, USA
| | - John E Morley
- Division of Geriatric Medicine, Saint Louis University School of Medicine, Missouri, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA.,Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Bruno Vellas
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, France.,UMR INSERM, 1027 University of Toulouse III and Faculté de Médecine, France
| | - Philipe de Souto Barreto
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, France.,UMR INSERM, 1027 University of Toulouse III and Faculté de Médecine, France
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12
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Seino Y, Nakamura T, Harada T, Nakahata N, Kawarabayashi T, Ueda T, Takatama M, Shoji M. Quantitative Measurement of Cerebrospinal Fluid Amyloid-β Species by Mass Spectrometry. J Alzheimers Dis 2020; 79:573-584. [PMID: 33337370 PMCID: PMC7902963 DOI: 10.3233/jad-200987] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background: High sensitivity liquid chromatography mass spectrometry (LC-MS/MS) was recently introduced to measure amyloid-β (Aβ) species, allowing for a simultaneous assay that is superior to ELISA, which requires more assay steps with multiple antibodies. Objective: We validated the Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43 assay by LC-MS/MS and compared it with ELISA using cerebrospinal fluid (CSF) samples to investigate its feasibility for clinical application. Methods: CSF samples from 120 subjects [8 Alzheimer’s disease (AD) with dementia (ADD), 2 mild cognitive dementia due to Alzheimer’s disease (ADMCI), 14 cognitively unimpaired (CU), and 96 neurological disease subjects] were analyzed. Aβ species were separated using the Shimadzu Nexera X2 system and quantitated using a Qtrap 5500 LC-MS/MS system. Aβ1-40 and Aβ1-42 levels were validated using ELISA. Results: CSF levels in CU were 666±249 pmol/L in Aβ1-38, 2199±725 pmol/L in Aβ1-40, 153.7±79.7 pmol/L in Aβ1-42, and 9.78±4.58 pmol/L in Aβ1-43. The ratio of the amounts of Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-43 was approximately 68:225:16:1. Linear regression analyses showed correlations among the respective Aβ species. Both Aβ1-40 and Aβ1-42 values were strongly correlated with ELISA measurements. No significant differences were observed in Aβ1-38 or Aβ1-40 levels between AD and CU. Aβ1-42 and Aβ1-43 levels were significantly lower, whereas the Aβ1-38/1-42, Aβ1-38/1-43, and Aβ1-40/Aβ1-43 ratios were significantly higher in AD than in CU. The basic assay profiles of the respective Aβ species were adequate for clinical usage. Conclusion: A quantitative LC-MS/MS assay of CSF Aβ species is as reliable as specific ELISA for clinical evaluation of CSF biomarkers for AD.
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Affiliation(s)
- Yusuke Seino
- Department of Neurology, Hirosaki National Hospital, Hirosaki, Aomori, Japan
| | - Takumi Nakamura
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan
| | - Tomoo Harada
- Bioanalysis Department, LSI Medience Corporation, Itabashi-ku, Tokyo, Japan
| | - Naoko Nakahata
- Department of Speech-Language-Hearing Therapy, Hirosaki University of Health and Welfare, Hirosaki, Aomori, Japan
| | | | - Tetsuya Ueda
- Bioanalysis Department, LSI Medience Corporation, Itabashi-ku, Tokyo, Japan
| | - Masamitsu Takatama
- Dementia Center, Geriatrics Research Institute and Hospital, Maebashi, Gunma, Japan
| | - Mikio Shoji
- Dementia Center, Geriatrics Research Institute and Hospital, Maebashi, Gunma, Japan
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13
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Fani L, Ahmad S, Ikram MK, Ghanbari M, Ikram MA. Immunity and amyloid beta, total tau and neurofilament light chain: Findings from a community-based cohort study. Alzheimers Dement 2020; 17:446-456. [PMID: 33215849 PMCID: PMC8048997 DOI: 10.1002/alz.12212] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/20/2020] [Accepted: 09/23/2020] [Indexed: 12/24/2022]
Abstract
Introduction We investigated how components of immunity relate to biomarkers of Alzheimer's disease (AD) in plasma and explored the influence of AD genetic risk factors in the population‐based Rotterdam Study. Methods In 7397 persons, we calculated the granulocyte‐to‐lymphocyte ratio (GLR), platelet‐to‐lymphocyte ratio (PLR), and systemic immune‐inflammation index (SII). In 3615 of these persons, plasma amyloid‐beta (Aβ)42 and Aβ40 were measured. Next, we constructed an overall genetic risk score (GRS) based on genome‐wide significant variants, both including and excluding APOE ε4. Results All innate immunity phenotypes were related to higher Aβ, most strongly with a doubling in GLR leading to a 1.9% higher Aβ42 (95% confidence interval [95% CI] 0.4 to 3.3%) and 3.2% higher Aβ40 (95% CI 2.0 to 4.3%). Higher AD GRS including APOE ε4 was associated with higher immunity markers. Discussion Higher levels of immunity markers were associated with higher Aβ in plasma. Participants with a higher genetic predisposition to AD had higher immunity markers, where these effects were mainly driven by APOE ε4.
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Affiliation(s)
- Lana Fani
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.,Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands.,Erasmus MC, Department of Neurology, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
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14
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Doecke JD, Pérez-Grijalba V, Fandos N, Fowler C, Villemagne VL, Masters CL, Pesini P, Sarasa M. Total Aβ 42/Aβ 40 ratio in plasma predicts amyloid-PET status, independent of clinical AD diagnosis. Neurology 2020; 94:e1580-e1591. [PMID: 32179698 PMCID: PMC7251518 DOI: 10.1212/wnl.0000000000009240] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 10/24/2019] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To explore whether the plasma total β-amyloid (Aβ) Aβ42/Aβ40 ratio is a reliable predictor of the amyloid-PET status by exploring the association between these 2 variables in a subset of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging cohort. METHODS Taking plasma samples at 3 separate time points, month 18 (n = 176), month 36 (n = 169), and month 54 (n = 135), we assessed the total Aβ42/Aβ40 ratio in plasma (TP42/40) with regard to neocortical Aβ burden via PET standardized uptake value ratio (SUVR) and investigated both association with Aβ-PET status and correlation (and agreement) with SUVR. RESULTS The TP42/40 plasma ratio was significantly reduced in amyloid-PET-positive participants at all time points (p < 0.0001). Adjusting for covariates age, gender, APOE ε4 allele status, and clinical classification clearly affects the significance, with p values reduced and only comparisons at 54 months retaining significance (p = 0.006). Correlations with SUVR were similar across each time point, with Spearman ρ reaching -0.64 (p < 0.0001). Area under the curve values were highly reproducible over time points, with values ranging from 0.880 at 36 months to 0.913 at 54 months. In assessments of the healthy control group only, the same relationships were found. CONCLUSIONS The current study demonstrates reproducibility of the plasma assay to discriminate between amyloid-PET positive and negative over 3 time points, which can help to substantially reducing the screening rate of failure for clinical trials targeting preclinical or prodromal disease. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that plasma total Aβ42/Aβ40 ratio is associated with neocortical amyloid burden as measured by PET SUVR.
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Affiliation(s)
- James D Doecke
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Virginia Pérez-Grijalba
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Noelia Fandos
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Christopher Fowler
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Victor L Villemagne
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Colin L Masters
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
| | - Pedro Pesini
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia.
| | - Manuel Sarasa
- From the CSIRO Health and Biosecurity/Australian E-Health Research Centre (J.D.D.), Royal Brisbane and Women's Hospital, Herston, Queensland, Australia; R&D Department (V.P.-G., N.F., P.P., M.S.), Araclon Biotech Ltd, Zaragoza, Spain; and The Florey Institute of Neuroscience and Mental Health (C.F., V.L.V., C.L.M.), University of Melbourne, Parkville, Victoria, Australia
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15
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Wang X, Sun Y, Li T, Cai Y, Han Y. Amyloid-β as a Blood Biomarker for Alzheimer’s Disease: A Review of Recent Literature. J Alzheimers Dis 2020; 73:819-832. [PMID: 31868667 DOI: 10.3233/jad-190714] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Xiaoni Wang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yu Sun
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Taoran Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yanning Cai
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, Key Laboratory for Neurodegenerative Diseases of the Ministry of Education, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
- Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
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16
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Pérez-Grijalba V, Arbizu J, Romero J, Prieto E, Pesini P, Sarasa L, Guillen F, Monleón I, San-José I, Martínez-Lage P, Munuera J, Hernández I, Buendía M, Sotolongo-Grau O, Alegret M, Ruiz A, Tárraga L, Boada M, Sarasa M. Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study. Alzheimers Res Ther 2019; 11:96. [PMID: 31787105 PMCID: PMC6886187 DOI: 10.1186/s13195-019-0549-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/22/2019] [Indexed: 12/30/2022]
Abstract
BACKGROUND To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer's disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. METHODS We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. RESULTS Eighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779-0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden's cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913-0.100). CONCLUSIONS Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer's disease.
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Affiliation(s)
| | - Javier Arbizu
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | - Judith Romero
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Elena Prieto
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | - Pedro Pesini
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain.
| | - Leticia Sarasa
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Fernando Guillen
- Servicio de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Spain
| | | | - Itziar San-José
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
| | - Pablo Martínez-Lage
- Center for Research and Advanced Therapies and Memory Clinic, Fundación CITA-Alzheimer, San Sebastián, Spain
| | - Josep Munuera
- Institut de recerca Sant Joan de Déu, Hospital Infantil Sant Joan de Déu, Barcelona, Spain
| | - Isabel Hernández
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Mar Buendía
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
| | - Oscar Sotolongo-Grau
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
| | - Montserrat Alegret
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Agustín Ruiz
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Lluis Tárraga
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Manuel Sarasa
- Araclon Biotech S.L., Vía Hispanidad 21, 50009, Zaragoza, Spain
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17
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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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18
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Gao L, Jiang Y, Wei S, Shang S, Li P, Chen C, Dang L, Wang J, Huo K, Deng M, Wang J, Zhang R, Qu Q. The Level of Plasma Amyloid-β40 Is Correlated with Peripheral Transport Proteins in Cognitively Normal Adults: A Population-Based Cross-Sectional Study. J Alzheimers Dis 2019; 65:951-961. [PMID: 30103331 DOI: 10.3233/jad-180399] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND Transport proteins, soluble low-density lipoprotein receptor-related protein-1 (sLRP1), and soluble receptor of advanced glycation end products (sRAGE), play an important role in the clearance of plasma amyloid-β (Aβ). However, their relationship is not clear. OBJECTIVE The aim was to explore the relationship between plasma levels of sLRP1, sRAGE, and Aβ in a cross-sectional study. METHODS A total of 1,185 cognitively normal participants (age above 40) from a village in the suburbs of Xi'an, China were enrolled from October 8, 2014 to March 30, 2015. Plasma Aβ40, Aβ42, sLRP1, and sRAGE were tested using a commercial ELISA. Apolipoprotein E (APOE) genotyping was conducted using PCR and sequencing. The relationship between plasma levels of sLRP1, sRAGE, and Aβ was analyzed using Pearson's correlation analysis and multiple linear regression. RESULTS In the total population, Log sLRP1 and Log sRAGE were positively correlated with plasma Aβ40 (r= 0.103, p < 0.001; r= 0.064, p = 0.027, respectively), but neither were associated with plasma Aβ42. After multivariable adjustment in the regression model, Log sLRP1 and Log sRAGE were still positively related with plasma Aβ40 (β= 2.969, p < 0.001; β= 1.936, p = 0.017, respectively) but not Aβ42. Furthermore, the positive correlations between transport proteins and plasma Aβ40 remained significant only in APOEɛ4 non-carriers after Pearson's analysis and multiple regression analysis after stratification by gene status. CONCLUSION The concentrations of plasma sLRP1 and sRAGE had a significant impact on the level of plasma Aβ40 in cognitively normal adults, especially in APOEɛ4 non-carriers. However, the mechanism by which the transport proteins are involved in peripheral Aβ clearance and the relationship between transporters and amyloid burden in the brain needs further validation.
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Affiliation(s)
- Ling Gao
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yu Jiang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shan Wei
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Suhang Shang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Pei Li
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chen Chen
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Liangjun Dang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jin Wang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kang Huo
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Meiying Deng
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jingyi Wang
- Huxian Hospital of Traditional Chinese Medicine, Xi'an, China
| | - Rong Zhang
- Cerebrovascular Laboratory, Institute for Exercise and Environmental Medicine, UT Southwestern Medical Center at Dallas, Dallas, TX, USA
| | - Qiumin Qu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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19
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Risacher SL, Fandos N, Romero J, Sherriff I, Pesini P, Saykin AJ, Apostolova LG. Plasma amyloid beta levels are associated with cerebral amyloid and tau deposition. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:510-519. [PMID: 31384662 PMCID: PMC6661419 DOI: 10.1016/j.dadm.2019.05.007] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction We investigated the relationship of plasma amyloid beta (Aβ) with cerebral deposition of Aβ and tau on positron emission tomography (PET). Methods Forty-four participants (18 cognitively normal older adults [CN], 10 mild cognitive impairment, 16 Alzheimer's disease [AD]) underwent amyloid PET and a blood draw. Free and total plasma Aβ40 and Aβ42 were assessed using a validated assay. Thirty-seven participants (17 CN, 8 mild cognitive impairment, 12 AD) also underwent a [18F]flortaucipir scan. Scans were preprocessed by standard techniques, and mean global and regional amyloid and tau values were extracted. Free Aβ42/Aβ40 (Aβ F42:F40) and total Aβ42/Aβ40 (Aβ T42:T40) were evaluated for differences by diagnosis and relation to PET Aβ positivity. Relationships between these measures and cerebral Aβ and tau on both regional and voxel-wise basis were also evaluated. Results Lower Aβ T42:T40 was associated with diagnosis and PET Aβ positivity. Lower plasma Aβ T42:T40 ratios predicted cerebral Aβ positivity, both across the full sample and in CN only. Finally, lower plasma Aβ T42:T40 ratios were associated with increased cortical Aβ and tau in AD-related regions on both regional and voxel-wise analyses. Discussion Plasma Aβ measures may be useful biomarkers for predicting cerebral Aβ and tau. Additional studies in larger samples are warranted.
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Affiliation(s)
- Shannon L Risacher
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | | | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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20
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Cilento EM, Jin L, Stewart T, Shi M, Sheng L, Zhang J. Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases. J Neurochem 2019; 151:397-416. [PMID: 30474862 DOI: 10.1111/jnc.14635] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 11/15/2018] [Accepted: 11/19/2018] [Indexed: 12/16/2022]
Abstract
Accurate, reliable, and objective biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and related age-associated neurodegenerative disorders are urgently needed to assist in both diagnosis, particularly at early stages, and monitoring of disease progression. Technological advancements in protein detection platforms over the last few decades have resulted in a plethora of reported molecular biomarker candidates for both AD and PD; however, very few of these candidates are developed beyond the discovery phase of the biomarker development pipeline, a reflection of the current bottleneck within the field. In this review, the expanded use of selected reaction monitoring (SRM) targeted mass spectrometry will be discussed in detail as a platform for systematic verification of large panels of protein biomarker candidates prior to costly validation testing. We also advocate for the coupling of discovery-based proteomics with modern targeted MS-based approaches (e.g., SRM) within a single study in future workflows to expedite biomarker development and validation for AD and PD. It is our hope that improving the efficiency within the biomarker development process by use of an SRM pipeline may ultimately hasten the development of biomarkers that both decrease misdiagnosis of AD and PD and ultimately lead to detection at early stages of disease and objective assessment of disease progression. This article is part of the special issue "Proteomics".
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Affiliation(s)
- Eugene M Cilento
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA
| | - Lorrain Jin
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA
| | - Tessandra Stewart
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA
| | - Min Shi
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA
| | - Lifu Sheng
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA
| | - Jing Zhang
- Department of Pathology, University of Washington, School of Medicine, Seattle, Washington, USA.,Department of Pathology, School of Basic Medicine, Peking University Health Science Center, Peking University Third Hospital and Peking Key Laboratory for Early Diagnosis of Neurodegenerative Disorders, Beijing, China
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21
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de Rojas I, Romero J, Rodríguez-Gomez O, Pesini P, Sanabria A, Pérez-Cordon A, Abdelnour C, Hernández I, Rosende-Roca M, Mauleón A, Vargas L, Alegret M, Espinosa A, Ortega G, Gil S, Guitart M, Gailhajanet A, Santos-Santos MA, Moreno-Grau S, Sotolongo-Grau O, Ruiz S, Montrreal L, Martín E, Pelejà E, Lomeña F, Campos F, Vivas A, Gómez-Chiari M, Tejero MA, Giménez J, Pérez-Grijalba V, Marquié GM, Monté-Rubio G, Valero S, Orellana A, Tárraga L, Sarasa M, Ruiz A, Boada M. Correlations between plasma and PET beta-amyloid levels in individuals with subjective cognitive decline: the Fundació ACE Healthy Brain Initiative (FACEHBI). Alzheimers Res Ther 2018; 10:119. [PMID: 30497535 PMCID: PMC6267075 DOI: 10.1186/s13195-018-0444-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 10/29/2018] [Indexed: 01/30/2023]
Abstract
BACKGROUND Peripheral biomarkers that identify individuals at risk of developing Alzheimer's disease (AD) or predicting high amyloid beta (Aβ) brain burden would be highly valuable. To facilitate clinical trials of disease-modifying therapies, plasma concentrations of Aβ species are good candidates for peripheral AD biomarkers, but studies to date have generated conflicting results. METHODS The Fundació ACE Healthy Brain Initiative (FACEHBI) study uses a convenience sample of 200 individuals diagnosed with subjective cognitive decline (SCD) at the Fundació ACE (Barcelona, Spain) who underwent amyloid florbetaben(18F) (FBB) positron emission tomography (PET) brain imaging. Baseline plasma samples from FACEHBI subjects (aged 65.9 ± 7.2 years) were analyzed using the ABtest (Araclon Biotech). This test directly determines the free plasma (FP) and total plasma (TP) levels of Aβ40 and Aβ42 peptides. The association between Aβ40 and Aβ42 plasma levels and FBB-PET global standardized uptake value ratio (SUVR) was determined using correlations and linear regression-based methods. The effect of the APOE genotype on plasma Aβ levels and FBB-PET was also assessed. Finally, various models including different combinations of demographics, genetics, and Aβ plasma levels were constructed using logistic regression and area under the receiver operating characteristic curve (AUROC) analyses to evaluate their ability for discriminating which subjects presented brain amyloidosis. RESULTS FBB-PET global SUVR correlated weakly but significantly with Aβ42/40 plasma ratios. For TP42/40, this observation persisted after controlling for age and APOE ε4 allele carrier status (R2 = 0.193, p = 1.01E-09). The ROC curve demonstrated that plasma Aβ measurements are not superior to APOE and age in combination in predicting brain amyloidosis. It is noteworthy that using a simple preselection tool (the TP42/40 ratio with an empirical cut-off value of 0.08) optimizes the sensitivity and reduces the number of individuals subjected to Aβ FBB-PET scanners to 52.8%. No significant dependency was observed between APOE genotype and plasma Aβ measurements (p value for interaction = 0.105). CONCLUSION Brain and plasma Aβ levels are partially correlated in individuals diagnosed with SCD. Aβ plasma measurements, particularly the TP42/40 ratio, could generate a new recruitment strategy independent of the APOE genotype that would improve identification of SCD subjects with brain amyloidosis and reduce the rate of screening failures in preclinical AD studies. Independent replication of these findings is warranted.
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Affiliation(s)
- Itziar de Rojas
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | | | - O. Rodríguez-Gomez
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | | | - A. Sanabria
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - A. Pérez-Cordon
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - C. Abdelnour
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - I. Hernández
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - M. Rosende-Roca
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - A. Mauleón
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - L. Vargas
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - M. Alegret
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - A. Espinosa
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - G. Ortega
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - S. Gil
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - M. Guitart
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - A. Gailhajanet
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - M. A. Santos-Santos
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - Sonia Moreno-Grau
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - O. Sotolongo-Grau
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - S. Ruiz
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - L. Montrreal
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - E. Martín
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - E. Pelejà
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - F. Lomeña
- Servei de Medicina Nuclear, Hospital Clínic i Provincial, Barcelona, Spain
| | - F. Campos
- Servei de Medicina Nuclear, Hospital Clínic i Provincial, Barcelona, Spain
| | - A. Vivas
- Departament de Diagnòstic per la Imatge, Clínica Corachan, Barcelona, Spain
| | - M. Gómez-Chiari
- Departament de Diagnòstic per la Imatge, Clínica Corachan, Barcelona, Spain
| | - M. A. Tejero
- Departament de Diagnòstic per la Imatge, Clínica Corachan, Barcelona, Spain
| | - J. Giménez
- Departament de Diagnòstic per la Imatge, Clínica Corachan, Barcelona, Spain
| | | | - G. M. Marquié
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - G. Monté-Rubio
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - S. Valero
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - A. Orellana
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - L. Tárraga
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | | | - A. Ruiz
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
| | - M. Boada
- Research Center and Memory Clinic, Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya-Barcelona, C/ Marquès de Sentmenat, 57, 08029 Barcelona, Spain
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22
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Nakamura T, Kawarabayashi T, Seino Y, Hirohata M, Nakahata N, Narita S, Itoh K, Nakaji S, Shoji M. Aging and APOE-ε4 are determinative factors of plasma A β42 levels. Ann Clin Transl Neurol 2018; 5:1184-1191. [PMID: 30349853 PMCID: PMC6186936 DOI: 10.1002/acn3.635] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 07/25/2018] [Accepted: 07/25/2018] [Indexed: 01/29/2023] Open
Abstract
Objective The aim of this study was to confirm determinative factors for plasma Aβ and its association with cognitive function. Methods Fasting plasma Aβ40 and Aβ42 levels were measured by ELISA in 1019 participants in the Iwaki Health Promotion Project. The relationships between plasma Aβ and health-related items, including physical characteristics, cognitive function tests, blood chemistry, and APOE-ε4 genotype were analyzed. Results The plasma levels of Aβ40 and Aβ42, and Aβ40/42 ratio were found to significantly increase with aging. The age-dependent increase in Aβ42 level was significantly suppressed by APOE-ε4. Renal function was an associated factor for the plasma Aβ40 level. The plasma Aβ42 level and Aβ40/42 ratio correlated with cognitive function. Interpretation Age and APOE-ε4 are major determinative factors of plasma levels of Aβ42 and the Aβ40/42 ratio. These factors are critical adjustment factors for the usage of plasma Aβ as a biomarker of central nervous system amyloidosis.
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Affiliation(s)
- Takumi Nakamura
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Takeshi Kawarabayashi
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Yusuke Seino
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Mie Hirohata
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Naoko Nakahata
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Sakiko Narita
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Ken Itoh
- Department of Stress Response Science Hirosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Shigeyuki Nakaji
- Department of Social Medicine Hirosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
| | - Mikio Shoji
- Department of Neurology Hrosaki University Graduate School of Medicine 5 Zaifu-cho Hirosaki 037-8562 Japan
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23
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Chen K, Gao T, Bai Z, Yuan Z. Circulating APP, NCAM and Aβ serve as biomarkers for Alzheimer's disease. Brain Res 2018; 1699:117-120. [PMID: 30118716 DOI: 10.1016/j.brainres.2018.08.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 07/26/2018] [Accepted: 08/13/2018] [Indexed: 11/16/2022]
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease and the early diagnosis and intervention are important for valid treatment of AD. However, there are few biomarkers for the diagnosis and monitoring of AD. In the present study, circulating APP, NCAM, Aβ40, and Aβ42 were measured in order to identify which marker or combination of markers could be useful, cost-effective and noninvasive biomarkers for diagnosing and continuously monitoring AD. The results showed that circulating APP, NCAM, Aβ40, and Aβ42 were different between the AD group and the control group. Importantly, the combination of the four biomarkers had the highest AUC (0.997) with the highest sensitivity (98.5). Therefore, circulating APP, NCAM, Aβ40, and Aβ42 can be used as desirable biomarkers for AD diagnosis and monitoring.
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Affiliation(s)
- Keping Chen
- Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China.
| | - Tianli Gao
- Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210009, China
| | - Zhimao Bai
- Key Laboratory of Environmental Medicine Engineering of Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China
| | - Zuanning Yuan
- Van Andel Research Institute, Grand Rapids, MI 49503, USA
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24
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Fan LY, Tzen KY, Chen YF, Chen TF, Lai YM, Yen RF, Huang YY, Shiue CY, Yang SY, Chiu MJ. The Relation Between Brain Amyloid Deposition, Cortical Atrophy, and Plasma Biomarkers in Amnesic Mild Cognitive Impairment and Alzheimer's Disease. Front Aging Neurosci 2018; 10:175. [PMID: 29967578 PMCID: PMC6015901 DOI: 10.3389/fnagi.2018.00175] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 05/22/2018] [Indexed: 01/25/2023] Open
Abstract
Background: Neuritic plaques and neurofibrillary tangles are the pathological hallmarks of Alzheimer’s disease (AD), while the role of brain amyloid deposition in the clinical manifestation or brain atrophy remains unresolved. We aimed to explore the relation between brain amyloid deposition, cortical thickness, and plasma biomarkers. Methods: We used 11C-Pittsburgh compound B-positron emission tomography to assay brain amyloid deposition, magnetic resonance imaging to estimate cortical thickness, and an immunomagnetic reduction assay to measure plasma biomarkers. We recruited 39 controls, 25 subjects with amnesic mild cognitive impairment (aMCI), and 16 subjects with AD. PiB positivity (PiB+) was defined by the upper limit of the 95% confidence interval of the mean cortical SUVR from six predefined regions (1.0511 in this study). Results: All plasma biomarkers showed significant between-group differences. The plasma Aβ40 level was positively correlated with the mean cortical thickness of both the PiB+ and PiB- subjects. The plasma Aβ40 level of the subjects who were PiB+ was negatively correlated with brain amyloid deposition. In addition, the plasma tau level was negatively correlated with cortical thickness in both the PiB+ and PiB- subjects. Moreover, cortical thickness was negatively correlated with brain amyloid deposition in the PiB+ subjects. In addition, the cut-off point of plasma tau for differentiating between controls and AD was higher in the PiB- group than in the PiB+ group (37.5 versus 25.6 pg/ml, respectively). Lastly, ApoE4 increased the PiB+ rate in the aMCI and control groups. Conclusion: The contributions of brain amyloid deposition to cortical atrophy are spatially distinct. Plasma Aβ40 might be a protective indicator of less brain amyloid deposition and cortical atrophy. It takes more tau pathology to reach the same level of cognitive decline in subjects without brain amyloid deposition, and ApoE4 plays an early role in amyloid pathogenesis.
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Affiliation(s)
- Ling-Yun Fan
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Institute of Brain and Mind Sciences, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Kai-Yuan Tzen
- PET Center, Department of Nuclear Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Nuclear Medicine, Changhua Christian Hospital, Changhua City, Taiwan.,Molecular Imaging Center, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ya-Fang Chen
- Department of Medical Imaging, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ya-Mei Lai
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ruoh-Fang Yen
- PET Center, Department of Nuclear Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Molecular Imaging Center, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ya-Yao Huang
- Molecular Imaging Center, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chyng-Yann Shiue
- PET Center, Department of Nuclear Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Molecular Imaging Center, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,PET Center, Tri-Service General Hospital, Taipei, Taiwan
| | | | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Institute of Brain and Mind Sciences, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Psychology, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
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25
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Lewczuk P, Riederer P, O’Bryant SE, Verbeek MM, Dubois B, Visser PJ, Jellinger KA, Engelborghs S, Ramirez A, Parnetti L, Jack CR, Teunissen CE, Hampel H, Lleó A, Jessen F, Glodzik L, de Leon MJ, Fagan AM, Molinuevo JL, Jansen WJ, Winblad B, Shaw LM, Andreasson U, Otto M, Mollenhauer B, Wiltfang J, Turner MR, Zerr I, Handels R, Thompson AG, Johansson G, Ermann N, Trojanowski JQ, Karaca I, Wagner H, Oeckl P, van Waalwijk van Doorn L, Bjerke M, Kapogiannis D, Kuiperij HB, Farotti L, Li Y, Gordon BA, Epelbaum S, Vos SJB, Klijn CJM, Van Nostrand WE, Minguillon C, Schmitz M, Gallo C, Mato AL, Thibaut F, Lista S, Alcolea D, Zetterberg H, Blennow K, Kornhuber J, Riederer P, Gallo C, Kapogiannis D, Mato AL, Thibaut F. Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry. World J Biol Psychiatry 2018; 19:244-328. [PMID: 29076399 PMCID: PMC5916324 DOI: 10.1080/15622975.2017.1375556] [Citation(s) in RCA: 183] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.
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Affiliation(s)
- Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, and Department of Biochemical Diagnostics, University Hospital of Białystok, Białystok, Poland
| | - Peter Riederer
- Center of Mental Health, Clinic and Policlinic of Psychiatry, Psychosomatics and Psychotherapy, University Hospital Würzburg, Würzburg, Germany
| | - Sid E. O’Bryant
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Marcel M. Verbeek
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Salpêtrièrie Hospital, INSERM UMR-S 975 (ICM), Paris 6 University, Paris, France
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience VU University Medical Centre, Amsterdam, The Netherlands
| | | | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Alfredo Ramirez
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Lucilla Parnetti
- Section of Neurology, Center for Memory Disturbances, Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy
| | | | - Charlotte E. Teunissen
- Neurochemistry Lab and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, Paris, France
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Spain
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Disorders (DZNE), Bonn, Germany
| | - Lidia Glodzik
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Mony J. de Leon
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Anne M. Fagan
- 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
| | - José Luis Molinuevo
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Willemijn J. Jansen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Bengt Winblad
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ulf Andreasson
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel and University Medical Center Göttingen, Department of Neurology, Göttingen, Germany
| | - Jens Wiltfang
- Department of Psychiatry & Psychotherapy, University of Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Martin R. Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Inga Zerr
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Clinical Dementia Centre, Department of Neurology, University Medical School, Göttingen, Germany
| | - Ron Handels
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | | | - Gunilla Johansson
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogeriatrics, Huddinge, Sweden
| | - Natalia Ermann
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ilker Karaca
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Holger Wagner
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Patrick Oeckl
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Linda van Waalwijk van Doorn
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Dimitrios Kapogiannis
- Laboratory of Neurosciences, National Institute on Aging/National Institutes of Health (NIA/NIH), Baltimore, MD, USA
| | - H. Bea Kuiperij
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer center, Nijmegen, The Netherlands
| | - Lucia Farotti
- Section of Neurology, Center for Memory Disturbances, Lab of Clinical Neurochemistry, University of Perugia, Perugia, Italy
| | - Yi Li
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA
| | - Brian A. Gordon
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stéphane Epelbaum
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Salpêtrièrie Hospital, INSERM UMR-S 975 (ICM), Paris 6 University, Paris, France
| | - Stephanie J. B. Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Catharina J. M. Klijn
- Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | | | - Carolina Minguillon
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Matthias Schmitz
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Clinical Dementia Centre, Department of Neurology, University Medical School, Göttingen, Germany
| | - Carla Gallo
- Departamento de Ciencias Celulares y Moleculares/Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Andrea Lopez Mato
- Chair of Psychoneuroimmunoendocrinology, Maimonides University, Buenos Aires, Argentina
| | - Florence Thibaut
- Department of Psychiatry, University Hospital Cochin-Site Tarnier 89 rue d’Assas, INSERM 894, Faculty of Medicine Paris Descartes, Paris, France
| | - Simone Lista
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, Paris, France
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Spain
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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26
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Abstract
Alzheimer's disease (AD), the main form of dementia in the elderly, is the most common progressive neurodegenerative disease characterized by rapidly progressive cognitive dysfunction and behavior impairment. AD exhibits a considerable heritability and great advances have been made in approaches to searching the genetic etiology of AD. In AD genetic studies, methods have developed from classic linkage-based and candidate-gene-based association studies to genome-wide association studies (GWAS) and next generation sequencing (NGS). The identification of new susceptibility genes has provided deeper insights to understand the mechanisms underlying AD. In addition to searching novel genes associated with AD in large samples, the NGS technologies can also be used to shed light on the 'black matter' discovery even in smaller samples. The shift in AD genetics between traditional studies and individual sequencing will allow biomaterials of each patient as the central unit of genetic studies. This review will cover genetic findings in AD and consequences of AD genetic findings. Firstly, we will discuss the discovery of mutations in APP, PSEN1, PSEN2, APOE, and ADAM10. Then we will summarize and evaluate the information obtained from GWAS of AD. Finally, we will outline the efforts to identify rare variants associated with AD using NGS.
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27
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High performance plasma amyloid-β biomarkers for Alzheimer's disease. Nature 2018; 554:249-254. [PMID: 29420472 DOI: 10.1038/nature25456] [Citation(s) in RCA: 1001] [Impact Index Per Article: 166.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Accepted: 12/11/2017] [Indexed: 01/02/2023]
Abstract
To facilitate clinical trials of disease-modifying therapies for Alzheimer's disease, which are expected to be most efficacious at the earliest and mildest stages of the disease, supportive biomarker information is necessary. The only validated methods for identifying amyloid-β deposition in the brain-the earliest pathological signature of Alzheimer's disease-are amyloid-β positron-emission tomography (PET) imaging or measurement of amyloid-β in cerebrospinal fluid. Therefore, a minimally invasive, cost-effective blood-based biomarker is desirable. Despite much effort, to our knowledge, no study has validated the clinical utility of blood-based amyloid-β markers. Here we demonstrate the measurement of high-performance plasma amyloid-β biomarkers by immunoprecipitation coupled with mass spectrometry. The ability of amyloid-β precursor protein (APP)669-711/amyloid-β (Aβ)1-42 and Aβ1-40/Aβ1-42 ratios, and their composites, to predict individual brain amyloid-β-positive or -negative status was determined by amyloid-β-PET imaging and tested using two independent data sets: a discovery data set (Japan, n = 121) and a validation data set (Australia, n = 252 including 111 individuals diagnosed using 11C-labelled Pittsburgh compound-B (PIB)-PET and 141 using other ligands). Both data sets included cognitively normal individuals, individuals with mild cognitive impairment and individuals with Alzheimer's disease. All test biomarkers showed high performance when predicting brain amyloid-β burden. In particular, the composite biomarker showed very high areas under the receiver operating characteristic curves (AUCs) in both data sets (discovery, 96.7%, n = 121 and validation, 94.1%, n = 111) with an accuracy approximately equal to 90% when using PIB-PET as a standard of truth. Furthermore, test biomarkers were correlated with amyloid-β-PET burden and levels of Aβ1-42 in cerebrospinal fluid. These results demonstrate the potential clinical utility of plasma biomarkers in predicting brain amyloid-β burden at an individual level. These plasma biomarkers also have cost-benefit and scalability advantages over current techniques, potentially enabling broader clinical access and efficient population screening.
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28
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Tateno A, Sakayori T, Kim WC, Koeda M, Kumita S, Suzuki H, Okubo Y. Effect of apolipoprotein E phenotype on the association of plasma amyloid β and amyloid positron emission tomography imaging in Japan. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 9:51-56. [PMID: 28975146 PMCID: PMC5614760 DOI: 10.1016/j.dadm.2017.08.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The plasma concentration of beta-amyloid (Aβ) has been considered another biomarker of Alzheimer's disease and was reportedly associated with cortical Aβ accumulation. METHODS We analyzed 28 subjects with apolipoprotein E4 (ApoE4; E4 group) and 89 subjects without ApoE4 (non-E4 group) to determine the association between cortical Aβ accumulation by standard uptake value ratio with [18F]florbetapir positron emission tomography and plasma Aβ1-40 and Aβ1-42. RESULTS Aβ1-42/Aβ1-40 correlated significantly with mean regional [18F]florbetapir standard uptake value ratio in the non-E4 group (R2 = 0.06, P = .02) but not in the E4 group, and receiver operating characteristic curve analysis for Aβ1-42/Aβ1-40 in the non-E4 group showed sensitivity (92.9%) and specificity (45.9%) with a cutoff value of 0.150 for Aβ positivity. DISCUSSION We verified that the correlation between Aβ1-42/Aβ1-40 and Aβ accumulation differed according to ApoE phenotype. The high sensitivity of plasma Aβ1-42/Aβ1-40 for Aβ positivity in non-E4 subjects indicated a possible role of plasma Aβ1-42/Aβ1-40 as a screening biomarker before amyloid positron emission tomography in clinical settings.
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Affiliation(s)
- Amane Tateno
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Takeshi Sakayori
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Woo Chan Kim
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Michihiko Koeda
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Shinichiro Kumita
- Department of Radiology, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Hidenori Suzuki
- Department of Pharmacology, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Yoshiro Okubo
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
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29
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Simino J, Wang Z, Bressler J, Chouraki V, Yang Q, Younkin SG, Seshadri S, Fornage M, Boerwinkle E, Mosley TH. Whole exome sequence-based association analyses of plasma amyloid-β in African and European Americans; the Atherosclerosis Risk in Communities-Neurocognitive Study. PLoS One 2017; 12:e0180046. [PMID: 28704393 PMCID: PMC5509141 DOI: 10.1371/journal.pone.0180046] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 06/08/2017] [Indexed: 12/30/2022] Open
Abstract
Objective We performed single-variant and gene-based association analyses of plasma amyloid-β (aβ) concentrations using whole exome sequence from 1,414 African and European Americans. Our goal was to identify genes that influence plasma aβ42 concentrations and aβ42:aβ40 ratios in late middle age (mean = 59 years), old age (mean = 77 years), or change over time (mean = 18 years). Methods Plasma aβ measures were linearly regressed onto age, gender, APOE ε4 carrier status, and time elapsed between visits (fold-changes only) separately by race. Following inverse normal transformation of the residuals, seqMeta was used to conduct race-specific single-variant and gene-based association tests while adjusting for population structure. Linear regression models were fit on autosomal variants with minor allele frequencies (MAF)≥1%. T5 burden and Sequence Kernel Association (SKAT) gene-based tests assessed functional variants with MAF≤5%. Cross-race fixed effects meta-analyses were Bonferroni-corrected for the number of variants or genes tested. Results Seven genes were associated with aβ in late middle age or change over time; no associations were identified in old age. Single variants in KLKB1 (rs3733402; p = 4.33x10-10) and F12 (rs1801020; p = 3.89x10-8) were significantly associated with midlife aβ42 levels through cross-race meta-analysis; the KLKB1 variant replicated internally using 1,014 additional participants with exome chip. ITPRIP, PLIN2, and TSPAN18 were associated with the midlife aβ42:aβ40 ratio via the T5 test; TSPAN18 was significant via the cross-race meta-analysis, whereas ITPRIP and PLIN2 were European American-specific. NCOA1 and NT5C3B were associated with the midlife aβ42:aβ40 ratio and the fold-change in aβ42, respectively, via SKAT in African Americans. No associations replicated externally (N = 725). Conclusion We discovered age-dependent genetic effects, established associations between vascular-related genes (KLKB1, F12, PLIN2) and midlife plasma aβ levels, and identified a plausible Alzheimer’s Disease candidate gene (ITPRIP) influencing cell death. Plasma aβ concentrations may have dynamic biological determinants across the lifespan; plasma aβ study designs or analyses must consider age.
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Affiliation(s)
- Jeannette Simino
- Gertrude C. Ford MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
- Department of Data Science, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
- * E-mail:
| | - Zhiying Wang
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Vincent Chouraki
- Lille University, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE - Risk factors and molecular determinants of aging-related diseases; Lille, France
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, United States of America
| | - Steven G. Younkin
- Department of Neuroscience, Mayo Clinic College of Medicine, Mayo Clinic Jacksonville, Jacksonville, Florida, United States of America
| | - Sudha Seshadri
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, United States of America
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
- The Brown Foundation Institute of Molecular Medicine, Research Center for Human Genetics, The University of Texas Health Science Center, Houston, Texas, United States of America
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America
- The Brown Foundation Institute of Molecular Medicine, Research Center for Human Genetics, The University of Texas Health Science Center, Houston, Texas, United States of America
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, United States of America
| | - Thomas H. Mosley
- Gertrude C. Ford MIND Center, University of Mississippi Medical Center, Jackson, Mississippi, United States of America
- Department of Medicine, University of Mississippi Medical Center, Jackson, Massachusetts, United States of America
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30
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O'Bryant SE, Mielke MM, Rissman RA, Lista S, Vanderstichele H, Zetterberg H, Lewczuk P, Posner H, Hall J, Johnson L, Fong YL, Luthman J, Jeromin A, Batrla-Utermann R, Villarreal A, Britton G, Snyder PJ, Henriksen K, Grammas P, Gupta V, Martins R, Hampel H. Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic. Alzheimers Dement 2017; 13:45-58. [PMID: 27870940 PMCID: PMC5218961 DOI: 10.1016/j.jalz.2016.09.014] [Citation(s) in RCA: 192] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2016] [Accepted: 09/27/2016] [Indexed: 11/25/2022]
Abstract
The last decade has seen a substantial increase in research focused on the identification of blood-based biomarkers that have utility in Alzheimer's disease (AD). Blood-based biomarkers have significant advantages of being time- and cost-efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood-based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public-private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.
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Affiliation(s)
- Sid E O'Bryant
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA.
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Health Science Research, Mayo Clinic, Rochester, MN, USA
| | - Robert A Rissman
- Alzheimer's Disease Cooperative Study, Department of Neurosciences, UCSD School of Medicine, La Jolla, CA, USA
| | - Simone Lista
- AXA Research Fund and UPMC Chair, Paris, France; Department de Neurologie, Institut de la Memorie et de la Maladie d'Alzheimer (IM2A) et Institut du Cerveau et du la Moelle epiniere (ICM), Hospital de la Pitie-Salpetriere, Sorbonne Universites, Universite Pierre et Marie Curie, Paris, France
| | | | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gotenburg, Molndal, Sweden; UCL Institute of Neurology, London, UK
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany; Department of Neurodegeneration Diagnostics, Medical University of Bialystok, Bialystok, Poland
| | | | - James Hall
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Leigh Johnson
- Institute for Healthy Aging, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Yiu-Lian Fong
- Johnson & Johnson, London Innovation Center, London, UK
| | - Johan Luthman
- Neuroscience Clinical Development, Clinical Neuroscience Eisai, Woodcliff Lake, NJ, USA
| | | | | | - Alcibiades Villarreal
- Centro de Neurociencias y Unidad de Investigacion Clinica, Instituto de Investigaciones Cientificas y Servicios de Alta Tecnologia (INDICASAT AIP), Ciudad del Saber, Panama, Panama
| | - Gabrielle Britton
- Centro de Neurociencias y Unidad de Investigacion Clinica, Instituto de Investigaciones Cientificas y Servicios de Alta Tecnologia (INDICASAT AIP), Ciudad del Saber, Panama, Panama
| | - Peter J Snyder
- Department of Neurology, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI, USA
| | - Kim Henriksen
- Neurodegenerative Diseases, Nordic Bioscience Biomarkers and Research, Herlev, Denmark
| | - Paula Grammas
- George and Anne Ryan Institute for Neuroscience, University of Rhode Island, RI, USA
| | - Veer Gupta
- Faculty of Health, Engineering and Sciences, Center of Excellence for Alzheimer's Disease Research and Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Ralph Martins
- Faculty of Health, Engineering and Sciences, Center of Excellence for Alzheimer's Disease Research and Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Harald Hampel
- AXA Research Fund and UPMC Chair, Paris, France; Department de Neurologie, Institut de la Memorie et de la Maladie d'Alzheimer (IM2A) et Institut du Cerveau et du la Moelle epiniere (ICM), Hospital de la Pitie-Salpetriere, Sorbonne Universites, Universite Pierre et Marie Curie, Paris, France
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Plasma β-amyloid in Alzheimer's disease and vascular disease. Sci Rep 2016; 6:26801. [PMID: 27241045 PMCID: PMC4886210 DOI: 10.1038/srep26801] [Citation(s) in RCA: 405] [Impact Index Per Article: 50.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2016] [Accepted: 05/10/2016] [Indexed: 12/21/2022] Open
Abstract
Implementation of amyloid biomarkers in clinical practice would be accelerated if such biomarkers could be measured in blood. We analyzed plasma levels of Aβ42 and Aβ40 in a cohort of 719 individuals (the Swedish BioFINDER study), including patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD) dementia and cognitively healthy elderly, using a ultrasensitive immunoassay (Simoa platform). There were weak positive correlations between plasma and cerebrospinal fluid (CSF) levels for both Aβ42 and Aβ40, and negative correlations between plasma Aβ42 and neocortical amyloid deposition (measured with PET). Plasma levels of Aβ42 and Aβ40 were reduced in AD dementia compared with all other diagnostic groups. However, during the preclinical or prodromal AD stages (i.e. in amyloid positive controls, SCD and MCI) plasma concentration of Aβ42 was just moderately decreased whereas Aβ40 levels were unchanged. Higher plasma (but not CSF) levels of Aβ were associated with white matter lesions, cerebral microbleeds, hypertension, diabetes and ischemic heart disease. In summary, plasma Aβ is overtly decreased during the dementia stage of AD indicating that prominent changes in Aβ metabolism occur later in the periphery compared to the brain. Further, increased levels of Aβ in plasma are associated with vascular disease.
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Situmeang RF, Wahjoepramono EJ, Kaelan C, Purba JS, Suhadi B, As'ad S, Aliah A, Patellongi IJ, Wahid S. Genetic risk factor APOEε4 associates with plasma amyloid beta in amnestic mild cognitive impairment and alzheimer’s disease. MEDICAL JOURNAL OF INDONESIA 2016. [DOI: 10.13181/mji.v25i1.1255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
Background: APOEε4 is a strong genetic risk factor for Alzheimer’s disease (AD). AD itself has been associated with reduced Aβ clearance from the brain and plasma. Understanding the potential pathogenic link between APOEε4 and plasma Aβ might allow for earlier identification of people at risk of developing AD. The aim of this study is to find out the correlation between APOEε4 and plasma Aβ in amnestic mild cognitive impairment (aMCI) and AD patients.Methods: This is a comparative cross-sectional study of patients attending a memory clinic in Siloam Hospital Lippo Karawaci, Tangerang, during the period of 2013-2014. Subjects were categorized into three categories: normal aging, aMCI, and AD. We performed blood test to examine APOEε4, plasma Aβ4o level, and plasma Aβ42 level. All data analyses were performed using correlation test and logistic regression.Results: Sixty subjects (normal aging = 23, aMCI = 17, AD = 20) were included. There were 19 (31.7%) subjects with APOEε4 positive. Subjects carrying ε4 allele were more likely to have AD by 3.9-fold than subjects with APOE ε4 allele negative. There is a significant difference between the mean of plasma Aβ40 in aMCI group and AD group. We also found correlation between APOEε4 (+) and higher plasma Aβ42 (p<0.05).Conclusion: There is a correlation between APOEε4 and plasma Aβ42 level, which supports the hypothesis that this genetic isoform accelerates the rate and progression of AD through Aβ-dependent pathways.
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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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Quantitative multimodal multiparametric imaging in Alzheimer's disease. Brain Inform 2016; 3:29-37. [PMID: 27747597 PMCID: PMC4883163 DOI: 10.1007/s40708-015-0028-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Accepted: 12/07/2015] [Indexed: 12/18/2022] Open
Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, causing changes in memory, thinking, and other dysfunction of brain functions. More and more people are suffering from the disease. Early neuroimaging techniques of AD are needed to develop. This review provides a preliminary summary of the various neuroimaging techniques that have been explored for in vivo imaging of AD. Recent advances in magnetic resonance (MR) techniques, such as functional MR imaging (fMRI) and diffusion MRI, give opportunities to display not only anatomy and atrophy of the medial temporal lobe, but also at microstructural alterations or perfusion disturbance within the AD lesions. Positron emission tomography (PET) imaging has become the subject of intense research for the diagnosis and facilitation of drug development of AD in both animal models and human trials due to its non-invasive and translational characteristic. Fluorodeoxyglucose (FDG) PET and amyloid PET are applied in clinics and research departments. Amyloid beta (Aβ) imaging using PET has been recognized as one of the most important methods for the early diagnosis of AD, and numerous candidate compounds have been tested for Aβ imaging. Besides in vivo imaging method, a lot of ex vivo modalities are being used in the AD researches. Multiphoton laser scanning microscopy, neuroimaging of metals, and several metal bioimaging methods are also mentioned here. More and more multimodality and multiparametric neuroimaging techniques should improve our understanding of brain function and open new insights into the pathophysiology of AD. We expect exciting results will emerge from new neuroimaging applications that will provide scientific and medical benefits.
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Shanthi KB, Krishnan S, Rani P. A systematic review and meta-analysis of plasma amyloid 1-42 and tau as biomarkers for Alzheimer's disease. SAGE Open Med 2015; 3:2050312115598250. [PMID: 26770797 PMCID: PMC4679337 DOI: 10.1177/2050312115598250] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Accepted: 06/27/2015] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE Amyloid 1-42 (Aβ42) and tau in cerebrospinal fluid are currently used as markers for diagnosis of Alzheimer's disease. Conflicting reports exist regarding their plasma levels in Alzheimer's disease patients. A meta-analysis was performed to statistically validate the use of plasma Aβ42 and tau as biomarkers for Alzheimer's disease. METHODS Different databases were searched using the search key: (amyloid OR amyloid1-42 OR Aβ42) AND (tau OR total tau) AND plasma AND (alzheimer's OR alzheimer's disease), and for databases not accepting boolean search, records were retrieved using the search key: plasma + amyloid + tau + alzheimer's. A total of 1880 articles for Aβ42 and 1508 articles for tau were shortlisted. The abstracts were screened, and 69 articles reporting plasma Aβ42 levels and 6 articles reporting plasma tau were identified. After exclusion, 25 studies reporting plasma Aβ42 and 6 studies reporting total tau were analysed in Review Manager version 5.2 using weighted mean difference method, and the bias between studies was assessed using the funnel plot. RESULTS Plasma Aβ42 and tau did not vary significantly between Alzheimer's disease patients and controls. The funnel plot showed that there was no bias between studies for Aβ42, while possible bias existed for tau due to availability of limited studies. CONCLUSION This analysis pinpoints that plasma Aβ42 and tau could not serve as reliable markers independently for diagnosis of Alzheimer's disease and a cohort study with age, sex and apolipoprotein E correction is warranted for their possible use as Alzheimer's disease markers.
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Affiliation(s)
| | - Sreeram Krishnan
- Department of Biotechnology, PSG College of Technology, Coimbatore, India
| | - P Rani
- Department of Biotechnology, PSG College of Technology, Coimbatore, India
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Affiliation(s)
- Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK.
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Corlier F, Rivals I, Lagarde J, Hamelin L, Corne H, Dauphinot L, Ando K, Cossec JC, Fontaine G, Dorothée G, Malaplate-Armand C, Olivier JL, Dubois B, Bottlaender M, Duyckaerts C, Sarazin M, Potier MC. Modifications of the endosomal compartment in peripheral blood mononuclear cells and fibroblasts from Alzheimer's disease patients. Transl Psychiatry 2015; 5:e595. [PMID: 26151923 PMCID: PMC5068716 DOI: 10.1038/tp.2015.87] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2015] [Accepted: 05/21/2015] [Indexed: 12/16/2022] Open
Abstract
Identification of blood-based biomarkers of Alzheimer's disease (AD) remains a challenge. Neuropathological studies have identified enlarged endosomes in post-mortem brains as the earliest cellular change associated to AD. Here the presence of enlarged endosomes was investigated in peripheral blood mononuclear cells from 48 biologically defined AD patients (25 with mild cognitive impairment and 23 with dementia (AD-D)), and 23 age-matched healthy controls using immunocytochemistry and confocal microscopy. The volume and number of endosomes were not significantly different between AD and controls. However, the percentage of cells containing enlarged endosomes was significantly higher in the AD-D group as compared with controls. Furthermore, endosomal volumes significantly correlated to [C(11)]PiB cortical index measured by positron emission tomography in the AD group, independently of the APOE genotype, but not to the levels of amyloid-beta, tau and phosphorylated tau measured in the cerebrospinal fluid. Importantly, we confirmed the presence of enlarged endosomes in fibroblasts from six unrelated AD-D patients as compared with five cognitively normal controls. This study is the first, to our knowledge, to report morphological alterations of the endosomal compartment in peripheral cells from AD patients correlated to amyloid load that will now be evaluated as a possible biomarker.
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Affiliation(s)
- F Corlier
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France
| | - I Rivals
- Équipe de Statistique Appliquée, ESPCI ParisTech, PSL Research University, INSERM UMRS 1158, Paris, France
| | - J Lagarde
- Neurologie de la Mémoire et du Langage, Service de Neurologie, Université Paris Descartes, Sorbonne Paris Cité, INSERM UMR S894, Centre Hospitalier Sainte Anne, Paris, France
| | - L Hamelin
- Neurologie de la Mémoire et du Langage, Service de Neurologie, Université Paris Descartes, Sorbonne Paris Cité, INSERM UMR S894, Centre Hospitalier Sainte Anne, Paris, France
| | - H Corne
- Neurologie de la Mémoire et du Langage, Service de Neurologie, Université Paris Descartes, Sorbonne Paris Cité, INSERM UMR S894, Centre Hospitalier Sainte Anne, Paris, France
| | - L Dauphinot
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France
| | - K Ando
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France
| | - J-C Cossec
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France
| | - G Fontaine
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France
| | - G Dorothée
- INSERM UMRS 938, Laboratoire Système Immunitaire et Maladies Conformationnelles, Hôpital Saint-Antoine, Paris, France,Université Pierre et Marie Curie, Université Paris 6, Centre de Recherche Saint-Antoine, Hôpital Saint-Antoine, Paris, France
| | - C Malaplate-Armand
- Laboratoire de Biochimie et Biologie Moléculaire, UF Oncologie—Endocrinologie—Neurobiologie, Hôpital Central, Centre Hospitalier Universitaire, Nancy, France,UR AFPA—USC 340, Equipe BFLA, Université de Lorraine, Nancy, France
| | - J-L Olivier
- Laboratoire de Biochimie et Biologie Moléculaire, UF Oncologie—Endocrinologie—Neurobiologie, Hôpital Central, Centre Hospitalier Universitaire, Nancy, France,UR AFPA—USC 340, Equipe BFLA, Université de Lorraine, Nancy, France
| | - B Dubois
- Institut de la mémoire et de la maladie d'Alzheimer, IMMA, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - M Bottlaender
- CEA (MB), DSV, Institut d'Imagerie Biomédicale, Service Hospitalier Frédéric Joliot, Orsay, France
| | - C Duyckaerts
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France,Laboratoire de Neuropathologie Escourolle, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
| | - M Sarazin
- Neurologie de la Mémoire et du Langage, Service de Neurologie, Université Paris Descartes, Sorbonne Paris Cité, INSERM UMR S894, Centre Hospitalier Sainte Anne, Paris, France
| | - M-C Potier
- UPMC University Paris 06, UMRS 1127, Sorbonne Universités, Paris, France,INSERM U 1127, Paris, France,ICM Research Centre, CNRS UMR 7225, Paris, France,ICM Research Centre, Group of Alzheimer's and Prion's diseases, CNRS UMR7225, INSERM URM975, UPMC, Hôpital de la Pitié-Salpêtrière, 47 Boulevard de l'Hôpital, 75013 Paris, France. E-mail:
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Saykin AJ, Shen L, Yao X, Kim S, Nho K, Risacher SL, Ramanan VK, Foroud TM, Faber KM, Sarwar N, Munsie LM, Hu X, Soares HD, Potkin SG, Thompson PM, Kauwe JSK, Kaddurah-Daouk R, Green RC, Toga AW, Weiner MW. Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans. Alzheimers Dement 2015; 11:792-814. [PMID: 26194313 PMCID: PMC4510473 DOI: 10.1016/j.jalz.2015.05.009] [Citation(s) in RCA: 202] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Revised: 05/08/2015] [Accepted: 05/08/2015] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.
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Affiliation(s)
- Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, 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; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xiaohui Yao
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; School of Informatics and Computing, Indiana University, Purdue University - Indianapolis, Indianapolis, IN, USA
| | - Sungeun Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, 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; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Vijay K Ramanan
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana M Foroud
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kelley M Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | - Xiaolan Hu
- Bristol-Myers Squibb, Wallingford, CT, USA
| | | | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California - Irvine, Irvine, CA, USA
| | - Paul M Thompson
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA; Imaging Genetics Center, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA; Department of Neuroscience, Brigham Young University, Provo, UT, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Robert C Green
- Partners Center for Personalized Genetic Medicine, Boston, MA, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute for Neuroimaging and Neuroinformatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Michael W Weiner
- Department of Radiology, University of California-San Francisco, San Francisco, CA, USA; Department of Medicine, University of California-San Francisco, San Francisco, CA, USA; Department of Psychiatry, University of California-San Francisco, San Francisco, CA, USA; Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center, San Francisco, CA, USA
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Abstract
Since the original publication describing the illness in 1907, the genetic understanding of Alzheimer’s disease (AD) has advanced such that it is now clear that it is a genetically heterogeneous condition, the subtypes of which may not uniformly respond to a given intervention. It is therefore critical to characterize the clinical and preclinical stages of AD subtypes, including the rare autosomal dominant forms caused by known mutations in the PSEN1, APP, and PSEN2 genes that are being studied in the Dominantly Inherited Alzheimer Network study and its associated secondary prevention trial. Similar efforts are occurring in an extended Colombian family with a PSEN1 mutation, in APOE ε4 homozygotes, and in Down syndrome. Despite commonalities in the mechanisms producing the AD phenotype, there are also differences that reflect specific genetic origins. Treatment modalities should be chosen and trials designed with these differences in mind. Ideally, the varying pathological cascades involved in the different subtypes of AD should be defined so that both areas of overlap and of distinct differences can be taken into account. At the very least, clinical trials should determine the influence of known genetic factors in post hoc analyses.
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Chouraki V, Beiser A, Younkin L, Preis SR, Weinstein G, Hansson O, Skoog I, Lambert JC, Au R, Launer L, Wolf PA, Younkin S, Seshadri S. Plasma amyloid-β and risk of Alzheimer's disease in the Framingham Heart Study. Alzheimers Dement 2015; 11:249-57.e1. [PMID: 25217292 PMCID: PMC4362883 DOI: 10.1016/j.jalz.2014.07.001] [Citation(s) in RCA: 85] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2014] [Revised: 06/05/2014] [Accepted: 07/02/2014] [Indexed: 12/24/2022]
Abstract
BACKGROUND Plasma amyloid-β (Aβ) peptide levels have been examined as a low-cost accessible marker for risk of incident Alzheimer's disease (AD) and dementia, but results have varied between studies. We reassessed these associations in one of the largest, prospective, community-based studies to date. METHODS A total of 2189 dementia-free, Framingham Study participants aged >60 years (mean age, 72 ± 8 years; 56% women) had plasma Aβ1-42 and Aβ1-40 measured and were followed prospectively (mean, 7.6 ± 3.0 years) for dementia/AD. RESULTS Increased plasma Aβ1-42 levels were associated with lower risk of dementia (Aβ1-42: hazard ratio [HR] = 0.80 [0.71‒0.90], P < .001; Aβ1-42-to-Aβ1-40 ratio: HR = 0.86 [0.76‒0.98], P = .027) and AD (Aβ1-42: HR = 0.79 [0.69‒0.90], P < .001; Aβ1-42-to-Aβ1-40 ratio: HR = 0.83 [0.72‒0.96], P = .012). CONCLUSION Our results suggest that lower plasma Aβ levels are associated with risk of incident AD and dementia. They encourage further evaluation of plasma Aβ levels as a biomarker for risk of developing clinical AD and dementia.
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Affiliation(s)
- Vincent Chouraki
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | | | - Sarah Rosner Preis
- The Framingham Heart Study, Framingham, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Galit Weinstein
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Research Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Göteborg, Sweden
| | - Jean-Charles Lambert
- Inserm UMR 744, Lille, France; Université Lille Nord de France, Lille, France; Institut Pasteur de Lille, Lille, France
| | - Rhoda Au
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Philip A Wolf
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA; Department of Neurology, Boston University School of Medicine, Boston, MA, USA
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Cavedo E, Lista S, Khachaturian Z, Aisen P, Amouyel P, Herholz K, Jack CR, Sperling R, Cummings J, Blennow K, O'Bryant S, Frisoni GB, Khachaturian A, Kivipelto M, Klunk W, Broich K, Andrieu S, de Schotten MT, Mangin JF, Lammertsma AA, Johnson K, Teipel S, Drzezga A, Bokde A, Colliot O, Bakardjian H, Zetterberg H, Dubois B, Vellas B, Schneider LS, Hampel H. The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations. J Prev Alzheimers Dis 2014; 1:181-202. [PMID: 26478889 PMCID: PMC4606938 DOI: 10.14283/jpad.2014.32] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Alzheimer's disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group's revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard ("core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for "prodromal AD" and "mild cognitive impairment due to AD" include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication.
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Affiliation(s)
- E Cavedo
- Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) Hôpital de la Pitié-Salpétrière & Institut du Cerveau et de la Moelle épinière (ICM), UMR S 1127, Hôpital de la Pitié-Salpétrière Paris & CATI multicenter neuroimaging platform, France; Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS San Giovanni di Dio Fatebenefratelli Brescia, Italy
| | - S Lista
- AXA Research Fund & UPMC Chair; Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) Hôpital de la Pitié-Salpétrière & Inserm U1127 Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpétrière Paris, France
| | - Z Khachaturian
- The Campaign to Prevent Alzheimer's Disease by 2020 (PAD2020), Potomac, MD, USA
| | - P Aisen
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - P Amouyel
- Inserm, U744, Lille, 59000, France; Université Lille 2, Lille, 59000, France; Institut Pasteur de Lille, Lille, 59000, France; Centre Hospitalier Régional Universitaire de Lille, Lille, 59000, France
| | - K Herholz
- Institute of Brain, Behaviour and Mental Health, University of Manchester, UK
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - R Sperling
- Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - J Cummings
- Cleveland Clinic Lou Ruvo Center for Brain Health, 888 West Bonneville Avenue, Las Vegas, Nevada 89106, USA
| | - K Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - S O'Bryant
- Department of Internal Medicine, Institute for Aging & Alzheimer's Disease Research, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - G B Frisoni
- IRCCS Istituto Centro S. Giovanni di Dio Fatebenefratelli, Brescia, Italy; University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - M Kivipelto
- Karolinska Institutet Alzheimer Research Center, NVS, Stockholm, Sweden
| | - W Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; Department of Neurology, University of Pittsburgh School of Medicine, USA
| | - K Broich
- Federal Institute of Drugs and Medical Devices (BfArM), Bonn, Germany
| | - S Andrieu
- Inserm UMR1027, Université de Toulouse III Paul Sabatier, Toulouse, France; Public health department, CHU de Toulouse
| | - M Thiebaut de Schotten
- Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King's College London, London, UK; Université Pierre et Marie Curie-Paris 6, Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (ICM), UMRS 1127 Paris, France; Inserm, U 1127, Paris, France; CNRS, UMR 7225, Paris, France
| | - J-F Mangin
- CEA UNATI, Neurospin, CEA Gif-sur-Yvette, France & CATI multicenter neuroimaging platform
| | - A A Lammertsma
- Department of Radiology & Nuclear Medicine, VU University Medical Center, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - K Johnson
- Departments of Radiology and Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - S Teipel
- Department of Psychosomatic Medicine, University of Rostock, and DZNE, German Center for Neurodegenerative Diseases, Rostock, Germany
| | - A Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, Cologne Germany
| | - A Bokde
- Cognitive Systems Group, Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - O Colliot
- Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, F-75013, Paris, France; Institut du Cerveau et de la Moelle épinière, ICM, Inserm, U1127, F-75013, Paris, France; CNRS, UMR 7225 ICM, 75013, Paris, France; Inria, Aramis project-team, Centre de Recherche Paris-Rocquencourt, France
| | - H Bakardjian
- Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpétrière University Hospital, Paris, France; IHU-A-ICM - Paris Institute of Translational Neurosciences, Paris, France
| | - H Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; UCL Institute of Neurology, Queen Square, London, UK
| | - B Dubois
- Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) Hôpital de la Pitié-Salpétrière & Inserm U1127 Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpétrière Paris, France
| | - B Vellas
- Inserm UMR1027, University of Toulouse, Toulouse, France
| | - L S Schneider
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - H Hampel
- AXA Research Fund & UPMC Chair; Sorbonne Universités, Université Pierre et Marie Curie, Paris 06, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A) Hôpital de la Pitié-Salpétrière & Inserm U1127 Institut du Cerveau et de la Moelle épinière (ICM), Hôpital de la Pitié-Salpétrière Paris, France
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