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Inglese M, Patel N, Linton-Reid K, Loreto F, Win Z, Perry RJ, Carswell C, Grech-Sollars M, Crum WR, Lu H, Malhotra PA, Aboagye EO. A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer's disease. COMMUNICATIONS MEDICINE 2022; 2:70. [PMID: 35759330 PMCID: PMC9209493 DOI: 10.1038/s43856-022-00133-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 05/24/2022] [Indexed: 01/12/2023] Open
Abstract
Background Alzheimer's disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called "Alzheimer's Predictive Vector" (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer's related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis.
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Affiliation(s)
- Marianna Inglese
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Neva Patel
- Department of Nuclear Medicine, Imperial College NHS Trust, London, UK
| | | | - Flavia Loreto
- Department of Brain Sciences, Imperial College London, London, UK
| | - Zarni Win
- Department of Nuclear Medicine, Imperial College NHS Trust, London, UK
| | - Richard J. Perry
- Department of Brain Sciences, Imperial College London, London, UK
- Department of Clinical Neurosciences, Imperial College NHS Trust, London, UK
| | - Christopher Carswell
- Department of Clinical Neurosciences, Imperial College NHS Trust, London, UK
- Department of Neurology, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK
| | - Matthew Grech-Sollars
- Department of Surgery and Cancer, Imperial College London, London, UK
- Department of Medical Physics, Royal Surrey NHS Foundation Trust, Guilford, UK
| | - William R. Crum
- Department of Surgery and Cancer, Imperial College London, London, UK
- Institute for Translational Medicine and Therapeutics, Imperial College London, London, UK
| | - Haonan Lu
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Paresh A. Malhotra
- Department of Brain Sciences, Imperial College London, London, UK
- Department of Clinical Neurosciences, Imperial College NHS Trust, London, UK
| | - Eric O. Aboagye
- Department of Surgery and Cancer, Imperial College London, London, UK
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Wang Q, Shi Y, Qi X, Qi L, Chen X, Shi J, Xie C, Zhang Z. Platelet-Derived Amyloid-β Protein Precursor as a Biomarker of Alzheimer's Disease. J Alzheimers Dis 2022; 88:589-599. [PMID: 35662121 DOI: 10.3233/jad-220122] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Platelet proteins may be associated with Alzheimer's disease (AD) pathology. OBJECTIVE To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. METHODS We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-β (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. RESULTS Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer's continuum (AD). The platelet amyloid-β protein precursor (AβPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-β42 level, which could affect MMSE scores through CSF amyloid-β42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AβPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. CONCLUSION Our study was the first to find an association between platelet AβPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.
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Affiliation(s)
- Qing Wang
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Yachen Shi
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Xinyang Qi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Lingyu Qi
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Xiang Chen
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Jingping Shi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China
| | - Zhijun Zhang
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China.,The Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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Li Q, Lv X, Jin F, Liao K, Gao L, Xu J. Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers. Front Aging Neurosci 2022; 14:849443. [PMID: 35493930 PMCID: PMC9047857 DOI: 10.3389/fnagi.2022.849443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/14/2022] [Indexed: 11/25/2022] Open
Abstract
Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.
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Affiliation(s)
- Qiaojun Li
- School of Information Engineering, Tianjin University of Commerce, Tianjin, China
| | - Xingping Lv
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Fei Jin
- Department of Molecular Imaging, Qingdao Central Hospital, Qingdao University, Qingdao, China
| | - Kun Liao
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Liyuan Gao
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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104
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Ebenau JL, Pelkmans W, Verberk IMW, Verfaillie SCJ, van den Bosch KA, van Leeuwenstijn M, Collij LE, Scheltens P, Prins ND, Barkhof F, van Berckel BNM, Teunissen CE, van der Flier WM. Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline. Neurology 2022; 98:e1315-e1326. [PMID: 35110378 PMCID: PMC8967429 DOI: 10.1212/wnl.0000000000200035] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 01/03/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD). METHODS We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker. RESULT We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%-19%). N biomarkers were modestly to moderately correlated (range r -0.28 - 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11-2.09]; 1.51 [1.05-2.17]; 1.50 [1.04-2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β -0.17 to -0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β -0.13 [SE 0.04]; p < 0.05). DISCUSSION In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.
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Affiliation(s)
- Jarith L Ebenau
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK.
| | - Wiesje Pelkmans
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Inge M W Verberk
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Sander C J Verfaillie
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Karlijn A van den Bosch
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Mardou van Leeuwenstijn
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Lyduine E Collij
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Philip Scheltens
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Niels D Prins
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Frederik Barkhof
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Bart N M van Berckel
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Charlotte E Teunissen
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Wiesje M van der Flier
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
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Jester DJ, Vyhnálek M, Andel R, Marková H, Nikolai T, Laczó J, Matusková V, Cechová K, Sheardova K, Hort J. Progression from Subjective Cognitive Decline to Mild Cognitive Impairment or Dementia: The Role of Baseline Cognitive Performance. J Alzheimers Dis 2022; 86:1763-1774. [DOI: 10.3233/jad-215291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Older adults with subjective cognitive decline (SCD) are at an increased risk of progression to mild cognitive impairment (MCI) or dementia. However, few have examined the specific cognitive tests that are associated with progression. Objective: This study examined performance on 18 neuropsychological tests among participants with SCD who later progressed to MCI or dementia. Methods: We included 131 participants from the Czech Brain Aging Study that had SCD at baseline. They completed a comprehensive neuropsychological battery including cognitive tests from the Uniform Data Set 2.0 enriched by the verbal memory test Rey Auditory Verbal Learning Test (RAVLT) and Rey-Osterrieth Complex Figure Test (ROCFT). Results: Fifty-five participants progressed: 53% to non-amnestic MCI (naMCI), 44% to amnestic MCI (aMCI), and 4% to dementia. Scoring one SD below the mean at baseline on the RAVLT 1 and RAVLT 1–5 was associated with 133% (RAVLT 1; HR: 2.33 [1.50, 3.62]) and 122% (RAVLT 1–5; HR: 2.22 [1.55, 3.16]) greater risk of progression to MCI or dementia over 3.84 years on average. Worse performance on the RAVLT 5, RAVLT 1–5, RAVLT 30, and ROCFT–Recall was associated with progression to aMCI whereas worse performance on the RAVLT 1, TMT B, and Boston Naming Test was associated with progression to naMCI. Conclusion: At baseline, lower verbal memory performance was most strongly associated with progression to aMCI whereas lower executive or language performance was most strongly associated with progression to naMCI.
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Affiliation(s)
- Dylan J. Jester
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Sam and Rose Stein Institute for Research on Aging, University of California San Diego, La Jolla, CA, USA
| | - Martin Vyhnálek
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Ross Andel
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
- School of Aging Studies, University of South Florida, Tampa, FL, USA
| | - Hana Marková
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Tomás Nikolai
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Jan Laczó
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Veronika Matusková
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Katerina Cechová
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
| | - Katerina Sheardova
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- First Department of Neurology, St. Anne’s University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Charles University, Second Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic
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Jack CR, Therneau TM, Lundt ES, Wiste HJ, Mielke MM, Knopman DS, Graff-Radford J, Lowe VJ, Vemuri P, Schwarz CG, Senjem ML, Gunter JL, Petersen RC. Long-term associations between amyloid positron emission tomography, sex, apolipoprotein E and incident dementia and mortality among individuals without dementia: hazard ratios and absolute risk. Brain Commun 2022; 4:fcac017. [PMID: 35310829 PMCID: PMC8924651 DOI: 10.1093/braincomms/fcac017] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/08/2021] [Accepted: 01/31/2022] [Indexed: 11/14/2022] Open
Abstract
Dementia and mortality rates rise inexorably with age and consequently interact. However, because of the major logistical difficulties in accounting for both outcomes in a defined population, very little work has examined how risk factors and biomarkers for incident dementia are influenced by competing mortality. The objective of this study was to examine long-term associations between amyloid PET, APOE ɛ4, sex, education and cardiovascular/metabolic conditions, and hazard and absolute risk of dementia and mortality in individuals without dementia at enrolment. Participants were enrolled in the Mayo Clinic Study of Aging, a population-based study of cognitive ageing in Olmsted County, MN, USA. All were without dementia and were age 55-92 years at enrolment and were followed longitudinally. Predictor variables were amyloid PET, APOE ɛ4 status, sex, education, cardiovascular/metabolic conditions and age. The main outcomes were incident dementia and mortality. Multivariable, multi-state models were used to estimate mortality and incident dementia rates and absolute risk of dementia and mortality by predictor variable group. Of the 4984 participants in the study, 4336 (87%) were cognitively unimpaired and 648 (13%) had mild cognitive impairment at enrolment. The median age at enrolment was 75 years; 2463 (49%) were women. The median follow-up time was 9.4 years (7.5 years after PET). High versus normal amyloid (hazard ratio 2.11, 95% confidence interval 1.43-2.79), APOE ɛ4 (women: hazard ratio 2.24, 95% confidence interval 1.80-2.77; men: hazard ratio 1.37, 95% confidence interval 1.09-1.71), older age and two additional cardiovascular/metabolic conditions (hazard ratio 1.37, 95% confidence interval 1.22-1.53) were associated with the increased hazard of dementia (all P < 0.001). Among APOE ɛ4 carriers with elevated amyloid, remaining lifetime risk of dementia at age 65 years was greater in women [74% (95% confidence interval 65-84%) high and 58% (95% confidence interval 52-65%) moderate amyloid], than men [62% (95% confidence interval 52-73%) high and 44% (95% confidence interval 35-53%) moderate amyloid]. Overall, the hazard and absolute risk of dementia varied considerably by predictor group. The absolute risk of dementia associated with predictors characteristic of Alzheimer's disease was greater in women than men while at the same time the combination of APOE ɛ4 non-carrier with normal amyloid was more protective in women than men. This set of findings may be attributed in part to different biological effects and in part to lower mortality rates in women.
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Affiliation(s)
| | - Terry M. Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Emily S. Lundt
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Heather J. Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Val J. Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
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Rostamzadeh A, Kahlert A, Kalthegener F, Jessen F. Psychotherapeutic interventions in individuals at risk for Alzheimer's dementia: a systematic review. Alzheimers Res Ther 2022; 14:18. [PMID: 35101105 PMCID: PMC8802419 DOI: 10.1186/s13195-021-00956-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 12/23/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Expanding technologies of early detection of Alzheimer's disease allow to identify individuals at risk of dementia in early and asymptomatic disease stages. Neuropsychiatric symptoms, such as anxiety and depression, are common in the course of AD and may be clinically observed many years before the onset of significant cognitive symptoms. To date, therapeutic interventions for AD focus on pharmacological and life style modification-based strategies. However, despite good evidence for psychotherapy in late-life depression, evidence for such therapeutic approaches to improve cognitive and emotional well-being and thereby reduce psychological risk factors in the course of AD are sparse. METHODS A systematic review was conducted in PUBMED, PsycINFO, Web of Science, and Clinical Trials to summarize the state of evidence on psychotherapeutic and psychoeducational interventions for individuals at risk for Alzheimer's dementia. Eligible articles needed to apply a manualized and standardized psychotherapeutic or psychoeducational content administered by trained professionals for individuals with subjective cognitive decline or mild cognitive impairment and measure mental health, quality of life or well-being. RESULTS The literature search yielded 32 studies that were included in this narrative summary. The data illustrates heterogeneous therapeutic approaches with mostly small sample sizes and short follow-up monitoring. Strength of evidence from randomized-controlled studies for interventions that may improve mood and well-being is scarce. Qualitative data suggests positive impact on cognitive restructuring, and disease acceptance, including positive effects on quality of life. Specific therapeutic determinants of efficacy have not been identified to date. CONCLUSIONS This review underlines the need of specific psychotherapeutic and psychoeducational approaches for individuals at risk of Alzheimer's dementia, particularly in terms of an early intervention aiming at improving mental health and well-being. One challenge is the modification of psychotherapeutic techniques according to the different stages of cognitive decline in the course of AD, which is needed to be sensitive to the individual needs.
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Affiliation(s)
- Ayda Rostamzadeh
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937, Cologne, Germany.
| | - Anna Kahlert
- Institute for Psychology, Rheinisch Westfälische Hochschule Aachen, Philosophical Faculty, 52056, Aachen, Germany
| | - Franziska Kalthegener
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937, Cologne, Germany
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Venusberg Campus 1, Gebäude 99, 53127, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50924, Cologne, Germany
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van de Beek M, Ooms FAH, Ebenau JL, Barkhof F, Scheltens P, Teunissen CE, van Harten AC, van der Flier WM, Lemstra AW. Association of the ATN Research Framework With Clinical Profile, Ccognitive Decline, and Mortality in Patients With Dementia With Lewy Bodies. Neurology 2022; 98:e1262-e1272. [PMID: 35074893 DOI: 10.1212/wnl.0000000000200048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 12/30/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The ATN framework has been developed to categorize biological processes within the Alzheimer's disease (AD) continuum. Since AD pathology often coincides with dementia with Lewy Bodies (DLB), we aimed to investigate the distribution of ATN profiles in DLB and associate ATN-profiles in DLB to prognosis. METHODS We included 202 DLB patients from the Amsterdam Dementia Cohort (68±7yrs, 19%F, MMSE: 24±3, DAT-SPECT abnormal: 105/119). Patients were classified into eight profiles according to the ATN framework, using CSF Aβ42 (A), CSF p-tau (T) and medial temporal atrophy scores (N). We compared presence of clinical symptoms in ATN profiles and used linear mixed models to analyze decline on cognitive tests (follow-up 3±2yrs for n=139). Mortality risk was assessed using Cox proportional hazards analysis. Analyses were performed on both the eight profiles, as well as three clustered categories (normal AD biomarkers, non-AD pathologic change, AD continuum). RESULTS Fifty (25%) DLB patients had normal AD biomarkers (A-T-N-), 37 (18%) had non-AD pathologic change (A-T+N-: 10%/A-T-N+: 6%/A-T+N+: 3%) and 115 (57%) were classified within the AD continuum (A+T-N-: 20%/A+T+N-: 16%/A+T-N+: 10%/A+T+N+: 9%). A+T+N+ patients were older and least often had RBD symptoms. Parkinsonism was more often present in A+T-, compared to A-T+ (independent of N). Compared to patients with normal AD biomarkers, patients in A+ categories showed steeper decline on memory tests and higher mortality risk. Cognitive decline and mortality did not differ between non-AD pathologic change and normal AD biomarkers. DISCUSSION In our DLB cohort, we found clinically relevant associations between ATN categories and disease manifestation. Patients within the AD continuum had steeper cognitive decline and shorter survival. Implementing the ATN framework within DLB patients aids in subtyping patients based on underlying biological processes and could provide targets for future treatment strategies, e.g. AD modifying treatment. Expanding the framework by incorporating markers for alpha-synucleinopathy would improve the use of the framework to characterize dementia patients with mixed pathology, which could enhance proper stratification of patients for therapeutic trials.
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Affiliation(s)
- Marleen van de Beek
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Floor A H Ooms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jarith L Ebenau
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands.,Institutes of Neurology and Healthcare Engineering, UCL, London, England, United Kingdom
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Neurochemistry, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Study Design and Baseline Results in a Cohort Study to Identify Predictors for the Clinical Progression to Mild Cognitive Impairment or Dementia From Subjective Cognitive Decline (CoSCo) Study. Dement Neurocogn Disord 2022; 21:147-161. [PMID: 36407288 PMCID: PMC9644060 DOI: 10.12779/dnd.2022.21.4.147] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 11/09/2022] Open
Abstract
Background and Purpose Subjective cognitive decline (SCD) refers to the self-perception of cognitive decline with normal performance on objective neuropsychological tests. SCD, which is the first help-seeking stage and the last stage before the clinical disease stage, can be considered to be the most appropriate time for prevention and treatment. This study aimed to compare characteristics between the amyloid positive and amyloid negative groups of SCD patients. Methods A cohort study to identify predictors for the clinical progression to mild cognitive impairment (MCI) or dementia from subjective cognitive decline (CoSCo) study is a multicenter, prospective observational study conducted in the Republic of Korea. In total, 120 people aged 60 years or above who presented with a complaint of persistent cognitive decline were selected, and various risk factors were measured among these participants. Continuous variables were analyzed using the Wilcoxon rank-sum test, and categorical variables were analyzed using the χ2 test or Fisher’s exact test. Logistic regression models were used to assess the predictors of amyloid positivity. Results The multivariate logistic regression model indicated that amyloid positivity on PET was related to a lack of hypertension, atrophy of the left temporal lateral and entorhinal cortex, low body mass index, low waist circumference, less body and visceral fat, fast gait speed, and the presence of the apolipoprotein E ε4 allele in amnestic SCD patients. Conclusions The CoSCo study is still in progress, and the authors aim to identify the risk factors that are related to the progression of MCI or dementia in amnestic SCD patients through a two-year follow-up longitudinal study.
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Frisoni GB, Altomare D, Thal DR, Ribaldi F, van der Kant R, Ossenkoppele R, Blennow K, Cummings J, van Duijn C, Nilsson PM, Dietrich PY, Scheltens P, Dubois B. The probabilistic model of Alzheimer disease: the amyloid hypothesis revised. Nat Rev Neurosci 2022; 23:53-66. [PMID: 34815562 PMCID: PMC8840505 DOI: 10.1038/s41583-021-00533-w] [Citation(s) in RCA: 242] [Impact Index Per Article: 80.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/04/2021] [Indexed: 01/03/2023]
Abstract
The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.
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Affiliation(s)
- Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland.
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, University of Leuven, Leuven, Belgium
- Department of Pathology, University Hospital Leuven, Leuven, Belgium
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Centro S. Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Rik van der Kant
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Kaj Blennow
- Cinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences; University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Peter M Nilsson
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Life Science Partners, Amsterdam, Netherlands
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d'Alzheimer, IM2A, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France
- Institut du Cerveau et de la Moelle Épinière, UMR-S975, INSERM, Paris, France
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111
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Song R, Wu X, Liu H, Guo D, Tang L, Zhang W, Feng J, Li C. Prediction of Cognitive Progression in Individuals with Mild Cognitive Impairment Using Radiomics as an Improvement of the ATN System: A Five-Year Follow-Up Study. Korean J Radiol 2022; 23:89-100. [PMID: 34983097 PMCID: PMC8743156 DOI: 10.3348/kjr.2021.0323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/19/2021] [Accepted: 08/24/2021] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). MATERIALS AND METHODS A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer's disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test. RESULTS The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer's continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer's disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD. CONCLUSION We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.
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Affiliation(s)
- Rao Song
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaojia Wu
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | | | - Dajing Guo
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lin Tang
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wei Zhang
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Junbang Feng
- Department of Radiology, Chongqing Emergency Medical Center, Chongqing, China
| | - Chuanming Li
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Pike KE, Cavuoto MG, Li L, Wright BJ, Kinsella GJ. Subjective Cognitive Decline: Level of Risk for Future Dementia and Mild Cognitive Impairment, a Meta-Analysis of Longitudinal Studies. Neuropsychol Rev 2021; 32:703-735. [PMID: 34748154 DOI: 10.1007/s11065-021-09522-3] [Citation(s) in RCA: 104] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 07/27/2021] [Indexed: 11/24/2022]
Abstract
Subjective Cognitive Decline (SCD) in older adults has been identified as a risk factor for dementia, although the literature is inconsistent, and it is unclear which factors moderate progression from SCD to dementia. Through separate meta-analyses, we aimed to determine if SCD increased the risk of developing dementia or mild cognitive impairment (MCI). Furthermore, we examined several possible moderators. Longitudinal studies of participants with SCD at baseline, with data regarding incident dementia or MCI, were extracted from MEDLINE and PsycINFO. Articles were excluded if SCD occurred solely in the context of dementia, MCI, or as part of a specific disease. Pooled estimates were calculated using a random-effects model, with moderator analyses examining whether risk varied according to SCD definition, demographics, genetics, recruitment source, and follow-up duration. Risk of study bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. 46 studies with more than 74,000 unique participants were included. SCD was associated with increased risk of developing dementia (HR = 1.90, 95% CI 1.52-2.36; OR = 2.48, 95% CI 1.97-3.14) and MCI (HR = 1.73, 95% CI 1.18-2.52; OR = 1.83, 95% CI 1.56-2.16). None of the potential moderating factors examined influenced the HR or OR of developing dementia. In contrast, including worry in the definition of SCD, younger age, and recruitment source impacted the OR of developing MCI, with clinic samples demonstrating highest risk. SCD thus represents an at-risk phase, ideal for early intervention, with further research required to identify effective interventions for risk reduction, and cognitive-behavioural interventions for cognitive management. PROSPERO, protocol number: CRD42016037993.
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Affiliation(s)
- Kerryn E Pike
- School of Psychology and Public Health, La Trobe University, Bundoora, Melbourne, VIC, 3086, Australia.
| | - Marina G Cavuoto
- School of Psychology and Public Health, La Trobe University, Bundoora, Melbourne, VIC, 3086, Australia
| | - Lily Li
- School of Psychology and Public Health, La Trobe University, Bundoora, Melbourne, VIC, 3086, Australia
| | - Bradley J Wright
- School of Psychology and Public Health, La Trobe University, Bundoora, Melbourne, VIC, 3086, Australia
| | - Glynda J Kinsella
- School of Psychology and Public Health, La Trobe University, Bundoora, Melbourne, VIC, 3086, Australia
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Visser LNC, Minguillon C, Sánchez-Benavides G, Abramowicz M, Altomare D, Fauria K, Frisoni GB, Georges J, Ribaldi F, Scheltens P, van der Schaar J, Zwan M, van der Flier WM, Molinuevo JL. Dementia risk communication. A user manual for Brain Health Services-part 3 of 6. Alzheimers Res Ther 2021; 13:170. [PMID: 34635169 PMCID: PMC8507171 DOI: 10.1186/s13195-021-00840-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 05/03/2021] [Indexed: 11/17/2022]
Abstract
Growing evidence suggests dementia incidence can be reduced through prevention programs targeting risk factors. To accelerate the implementation of such prevention programs, a new generation of brain health services (BHS) is envisioned, involving risk profiling, risk communication, risk reduction, and cognitive enhancement. The purpose of risk communication is to enable individuals at risk to make informed decisions and take action to protect themselves and is thus a crucial step in tailored prevention strategies of the dementia incidence. However, communicating about dementia risk is complex and challenging.In this paper, we provide an overview of (i) perspectives on communicating dementia risk from an ethical, clinical, and societal viewpoint; (ii) insights gained from memory clinical practice; (iii) available evidence on the impact of disclosing APOE and Alzheimer's disease biomarker test results gathered from clinical trials and observational studies; (iv) the value of established registries in light of BHS; and (v) practical recommendations regarding effective strategies for communicating about dementia risk.In addition, we identify challenges, i.e., the current lack of evidence on what to tell on an individual level-the actual risk-and on how to optimally communicate about dementia risk, especially concerning worried yet cognitively unimpaired individuals. Ideally, dementia risk communication strategies should maximize the desired impact of risk information on individuals' understanding of their health/disease status and risk perception and minimize potential harms. More research is thus warranted on the impact of dementia risk communication, to (1) evaluate the merits of different approaches to risk communication on outcomes in the cognitive, affective and behavioral domains, (2) develop an evidence-based, harmonized dementia risk communication protocol, and (3) develop e-tools to support and promote adherence to this protocol in BHSs.Based on the research reviewed, we recommend that dementia risk communication should be precise; include the use of absolute risks, visual displays, and time frames; based on a process of shared decision-making; and address the inherent uncertainty that comes with any probability.
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Affiliation(s)
- Leonie N C Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
- Center for Alzheimer Research, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Solna, Sweden.
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Marc Abramowicz
- Division of Genetic Medicine, Department of Diagnostics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | | | - Federica Ribaldi
- Division of Genetic Medicine, Department of Diagnostics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jetske van der Schaar
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marissa Zwan
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
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Ebenau JL, van der Lee SJ, Hulsman M, Tesi N, Jansen IE, Verberk IM, van Leeuwenstijn M, Teunissen CE, Barkhof F, Prins ND, Scheltens P, Holstege H, van Berckel BN, van der Flier WM. Risk of dementia in APOE ε4 carriers is mitigated by a polygenic risk score. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12229. [PMID: 34541285 PMCID: PMC8438688 DOI: 10.1002/dad2.12229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/09/2021] [Accepted: 06/28/2021] [Indexed: 12/22/2022]
Abstract
INTRODUCTION We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia. METHODS We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately. RESULTS The PRS and APOE ε4 were associated with amyloid-positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A-T+N-). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers. DISCUSSION Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.
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Affiliation(s)
- Jarith L. Ebenau
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Sven J. van der Lee
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
| | - Marc Hulsman
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Niccolò Tesi
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Iris E. Jansen
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Complex Trait GeneticsCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVU UniversityAmsterdamthe Netherlands
| | - Inge M.W. Verberk
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Mardou van Leeuwenstijn
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Niels D. Prins
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Henne Holstege
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Bart N.M. van Berckel
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam UMCAmsterdamthe Netherlands
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Li S, Wang C, Wang Z, Tan J. Involvement of cerebrovascular abnormalities in the pathogenesis and progression of Alzheimer's disease: an adrenergic approach. Aging (Albany NY) 2021; 13:21791-21806. [PMID: 34479211 PMCID: PMC8457611 DOI: 10.18632/aging.203482] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/17/2021] [Indexed: 01/09/2023]
Abstract
Alzheimer's disease (AD), as the most common neurodegenerative disease in elder population, is pathologically characterized by β-amyloid (Aβ) plaques, neurofibrillary tangles composed of highly-phosphorylated tau protein and consequently progressive neurodegeneration. However, both Aβ and tau fails to cover the whole pathological process of AD, and most of the Aβ- or tau-based therapeutic strategies are all failed. Increasing lines of evidence from both clinical and preclinical studies have indicated that age-related cerebrovascular dysfunctions, including the changes in cerebrovascular microstructure, blood-brain barrier integrity, cerebrovascular reactivity and cerebral blood flow, accompany or even precede the development of AD-like pathologies. These findings may raise the possibility that cerebrovascular changes are likely pathogenic contributors to the onset and progression of AD. In this review, we provide an appraisal of the cerebrovascular alterations in AD and the relationship to cognitive impairment and AD pathologies. Moreover, the adrenergic mechanisms leading to cerebrovascular and AD pathologies were further discussed. The contributions of early cerebrovascular factors, especially through adrenergic mechanisms, should be considered and treasured in the diagnostic, preventative, and therapeutic approaches to address AD.
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Affiliation(s)
- Song Li
- Liaoning Provincial Center for Clinical Research on Neurological Diseases, The First Affiliated Hospital, Dalian Medical University, Dalian 116021, China.,Liaoning Provincial Key Laboratory for Research on the Pathogenic Mechanisms of Neurological Diseases, The First Affiliated Hospital, Dalian Medical University, Dalian 116021, China
| | - Che Wang
- Department of Pharmaceutical Chemistry, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China
| | - Zhen Wang
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Jun Tan
- Key Laboratory of Endemic and Ethnic Diseases, Guizhou Medical University, Guiyang 550004, China
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Developing the ATX(N) classification for use across the Alzheimer disease continuum. Nat Rev Neurol 2021; 17:580-589. [PMID: 34239130 DOI: 10.1038/s41582-021-00520-w] [Citation(s) in RCA: 190] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/28/2021] [Indexed: 02/06/2023]
Abstract
Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.
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117
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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César-Freitas KG, Suemoto CK, Power MC, Brucki SMD, Nitrini R. Incidence of dementia in a Brazilian population: The Tremembé Epidemiologic Study. Alzheimers Dement 2021; 18:581-590. [PMID: 34338427 DOI: 10.1002/alz.12423] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 06/04/2021] [Accepted: 06/08/2021] [Indexed: 01/19/2023]
Abstract
INTRODUCTION Few dementia incidence studies have been performed in Latin America. We aimed to provide the incidence of dementia in a Brazilian community-dwelling elderly population. METHODS This study was conducted in urban and rural areas of Tremembé. The 520 participants without dementia at baseline were invited to participate in the follow-up. RESULTS After a median follow-up of 5 years, the incidence rate of dementia was 26.1 per 1000 person-years (PY) (95% confidence interval = 18.7-36.6/1000PY). This rate increased exponentially with age (8.3/1000PY for 60- to 64-year-olds to 110.2/1000PY for ≥80-year-olds) and lower education (10.5/1000PY for > 8 years of education to 59.2/1000PY for illiterates). Higher dementia risk was found among individuals with cognitive impairment no dementia at baseline. DISCUSSION The dementia incidence rate found was higher than in other countries in people under 65 years. Higher incidence in younger individuals is expected in developing countries probably due to low education and a high burden of cardiovascular diseases.
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Affiliation(s)
- Karolina G César-Freitas
- Cognitive and Behavioral Neurology Unit, Department of Neurology, University of São Paulo, São Paulo, Brazil
| | - Claudia K Suemoto
- Division of Geriatrics, University of São Paulo Medical School, São Paulo, Brazil
| | - Melinda C Power
- Department of Epidemiology, George Washington University, Washington, District of Columbia, USA
| | - Sonia M D Brucki
- Cognitive and Behavioral Neurology Unit, Department of Neurology, University of São Paulo, São Paulo, Brazil
| | - Ricardo Nitrini
- Cognitive and Behavioral Neurology Unit, Department of Neurology, Neurology, University of São Paulo Medical School, University of São Paulo, São Paulo, Brazil
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Dubois B, Villain N, Frisoni GB, Rabinovici GD, Sabbagh M, Cappa S, Bejanin A, Bombois S, Epelbaum S, Teichmann M, Habert MO, Nordberg A, Blennow K, Galasko D, Stern Y, Rowe CC, Salloway S, Schneider LS, Cummings JL, Feldman HH. Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group. Lancet Neurol 2021; 20:484-496. [PMID: 33933186 PMCID: PMC8339877 DOI: 10.1016/s1474-4422(21)00066-1] [Citation(s) in RCA: 500] [Impact Index Per Article: 125.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 01/21/2021] [Accepted: 02/18/2021] [Indexed: 12/13/2022]
Abstract
In 2018, the US National Institute on Aging and the Alzheimer's Association proposed a purely biological definition of Alzheimer's disease that relies on biomarkers. Although the intended use of this framework was for research purposes, it has engendered debate and challenges regarding its use in everyday clinical practice. For instance, cognitively unimpaired individuals can have biomarker evidence of both amyloid β and tau pathology but will often not develop clinical manifestations in their lifetime. Furthermore, a positive Alzheimer's disease pattern of biomarkers can be observed in other brain diseases in which Alzheimer's disease pathology is present as a comorbidity. In this Personal View, the International Working Group presents what we consider to be the current limitations of biomarkers in the diagnosis of Alzheimer's disease and, on the basis of this evidence, we propose recommendations for how biomarkers should and should not be used for diagnosing Alzheimer's disease in a clinical setting. We recommend that Alzheimer's disease diagnosis be restricted to people who have positive biomarkers together with specific Alzheimer's disease phenotypes, whereas biomarker-positive cognitively unimpaired individuals should be considered only at-risk for progression to Alzheimer's disease.
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Affiliation(s)
- Bruno Dubois
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France.
| | - Nicolas Villain
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Memory Clinic, University Hospital of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), Saint John of God Clinical Research Centre, Brescia, Italy
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology and Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Marwan Sabbagh
- Cleveland Clinic, Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Stefano Cappa
- University School for Advanced Studies, Pavia, Italy; RCCS Mondino Foundation, Pavia, Italy
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain; Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain; Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Stéphanie Bombois
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; INSERM, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, University of Lille, Lille, France
| | - Stéphane Epelbaum
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France; Inria ARAMIS project team, Inria-APHP collaboratio, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Marc Teichmann
- Assistance Publique-Hôpitaux de Paris (AP-HP) Department of Neurology, Sorbonne University, Paris, France
| | - Marie-Odile Habert
- AP-HP Department of Nuclear Medicine, Sorbonne University, Paris, France; CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Sorbonne University, Paris, France; Institut du Cerveau, Sorbonne University, Paris, France
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institute, Stockholm, Sweden; Theme Aging, The Aging Brain, Karolinska University Hospital, Stockholm, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Douglas Galasko
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, New York, NY, USA
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Stephen Salloway
- Department of Neurology and Department of Psychiatry, Alpert Medical School of Brown University, Providence, RI, USA; Butler Hospital, Providence, RI, USA
| | - Lon S Schneider
- Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Jeffrey L Cummings
- Cleveland Clinic, Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Howard H Feldman
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA; Shiley-Marcos Alzheimer's Disease Research Center, University of California San Diego, La Jolla, CA, USA; Alzheimer Disease Cooperative Study, University of California San Diego, La Jolla, CA, USA
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Highly specific and ultrasensitive plasma test detects Abeta(1-42) and Abeta(1-40) in Alzheimer's disease. Sci Rep 2021; 11:9736. [PMID: 33958661 PMCID: PMC8102604 DOI: 10.1038/s41598-021-89004-x] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 04/19/2021] [Indexed: 12/12/2022] Open
Abstract
Plasma biomarkers that reflect specific amyloid beta (Abeta) proteoforms provide an insight in the treatment effects of Alzheimer’s disease (AD) therapies. Our aim was to develop and validate ready-to-use Simoa ‘Amyblood’ assays that measure full length Abeta1-42 and Abeta1-40 and compare their performance with two commercial assays. Linearity, intra- and inter-assay %CV were compared between Amyblood, Quanterix Simoa triplex, and Euroimmun ELISA. Sensitivity and selectivity were assessed for Amyblood and the Quanterix triplex. Clinical performance was assessed in CSF biomarker confirmed AD (n = 43, 68 ± 6 years) and controls (n = 42, 62 ± 5 years). Prototype and Amyblood showed similar calibrator curves and differentiation (20 AD vs 20 controls, p < 0.001). Amyblood, Quanterix triplex, and ELISA showed similar linearity (96%-122%) and intra-assay %CVs (≤ 3.1%). A minor non-specific signal was measured with Amyblood of + 2.4 pg/mL Abeta1-42 when incubated with 60 pg/mL Abeta1-40. A substantial non-specific signal of + 24.7 pg/mL Abetax-42 was obtained when 40 pg/mL Abeta3-42 was measured with the Quanterix triplex. Selectivity for Abeta1-42 at physiological Abeta1-42 and Abeta1-40 concentrations was 125% for Amyblood and 163% for Quanterix. Amyblood and Quanterix ratios (p < 0.001) and ELISA Abeta1-42 concentration (p = 0.025) could differentiate AD from controls. We successfully developed and upscaled a prototype to the Amyblood assays with similar technical and clinical performance as the Quanterix triplex and ELISA, but better specificity and selectivity than the Quanterix triplex assay. These results suggest leverage of this specific assay for monitoring treatment response in trials.
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Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE, Cummings J, van der Flier WM. Alzheimer's disease. Lancet 2021; 397:1577-1590. [PMID: 33667416 PMCID: PMC8354300 DOI: 10.1016/s0140-6736(20)32205-4] [Citation(s) in RCA: 2385] [Impact Index Per Article: 596.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 08/21/2020] [Accepted: 10/15/2020] [Indexed: 12/16/2022]
Abstract
In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.
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Affiliation(s)
- Philip Scheltens
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Neurology, Amsterdam University Medical Centers, Amsterdam, Netherlands; Life Science Partners, Amsterdam, Netherlands.
| | - Bart De Strooper
- VIB Center for Brain and Disease Research, Leuven, Belgium; KU Leuven Department for Neurology, Leuven, Belgium; Dementia Research Institute, University College London, London, UK
| | - Miia Kivipelto
- Division of Clinical Geriatrics and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska University Hospital, Stockholm, Sweden; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Ageing and Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - Henne Holstege
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Clinical Genetics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gael Chételat
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Groupement d'Intérêt Public Cyceron, Caen, France
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, University of Nevada, Las Vegas, NV, USA; Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Wiesje M van der Flier
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Epidemiology and Datascience, Amsterdam University Medical Centers, Amsterdam, Netherlands
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Delmotte K, Schaeverbeke J, Poesen K, Vandenberghe R. Prognostic value of amyloid/tau/neurodegeneration (ATN) classification based on diagnostic cerebrospinal fluid samples for Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2021; 13:84. [PMID: 33879243 PMCID: PMC8059197 DOI: 10.1186/s13195-021-00817-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 03/23/2021] [Indexed: 11/12/2022]
Abstract
Objective The primary study objective of this retrospective academic memory clinic-based observational longitudinal study was to investigate the prognostic value of a cerebrospinal fluid (CSF)-based ATN classification for subsequent cognitive decline during the 3 years following lumbar puncture in a clinical, real-life setting. The secondary objective was to investigate the prognostic value of CSF biomarkers as continuous variables. Methods Data from 228 patients (median age 67 (47–85) years), who presented at the Neurology Memory Clinic UZ/KU Leuven between September 2011 and December 2016, were included with a follow-up period of up to 36 months. Patients underwent a CSF AD biomarker test for amyloid-beta 1–42 (Aβ42), hyperphosphorylated tau (p181-tau) and total tau (t-tau) in the clinical work-up for diagnostic reasons. Patients were divided into ATN classes based on CSF biomarkers: Aβ42 for amyloid (A), p181-tau for tau (T), and t-tau as a measure for neurodegeneration (N). Based on retrospective data analysis, cognitive performance was evaluated by Mini Mental State Examination (MMSE) scores every 6 months over a period up to 36 months following the lumbar puncture. The statistical analysis was based on linear mixed-effects modeling (LME). Results The distribution in the current clinical sample was as follows: A−/T−/N− 32.02%, A+/T−/N− 33.33%, A+/T+/N+ 17.11%, A+/T−/N+ 11.84%, A−/T−/N+ 4.39%, A−/T+/N+ 1.32% (3 cases), with no cases in the A−/T+/N− and A+/T+/N− class. Hence, the latter 3 classes were excluded from further analyses. The change of MMSE relative to A−/T−/N− over a 36-month period was significant in all four ATN classes: A+/T+/N+ = − 4.78 points on the MMSE; A−/T−/N+ = − 4.76; A+/T−/N+ = − 2.83; A+/T−/N− = − 1.96. The earliest significant difference was seen in the A+/T+/N+ class at 12 months after baseline. The effect of ATN class on future cognitive decline was confirmed for a different set of CSF thresholds. All individual baseline CSF biomarkers including the Aβ42/t-tau ratio showed a significant correlation with subsequent cognitive decline, with the highest correlation seen for Aβ42/t-tau. Conclusion ATN classification based on CSF biomarkers has a statistically significant and clinically relevant prognostic value for the course of cognitive decline in a 3-year period in a clinical practice setting. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00817-4.
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Affiliation(s)
- Koen Delmotte
- Department of Neurology, University Hospitals Leuven, Herestraat 49, B-3000, Leuven, Belgium. .,Department of Neurology, Jessa Hospital, Hasselt, Belgium.
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Laboratory of Neuropathology, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Koen Poesen
- Laboratory Medicine, University Hospitals Leuven, Leuven, Belgium.,Laboratory for Molecular Neurobiomarker Research, KU Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Department of Neurology, University Hospitals Leuven, Herestraat 49, B-3000, Leuven, Belgium.,Laboratory for Cognitive Neurology, Leuven Brain Institute, KU Leuven, Leuven, Belgium
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Rosenberg A, Solomon A, Soininen H, Visser PJ, Blennow K, Hartmann T, Kivipelto M. Research diagnostic criteria for Alzheimer's disease: findings from the LipiDiDiet randomized controlled trial. ALZHEIMERS RESEARCH & THERAPY 2021; 13:64. [PMID: 33766132 PMCID: PMC7995792 DOI: 10.1186/s13195-021-00799-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 02/23/2021] [Indexed: 12/18/2022]
Abstract
Background To explore the utility of the International Working Group (IWG)-1 criteria in recruitment for Alzheimer’s disease (AD) clinical trials, we applied the more recently proposed research diagnostic criteria to individuals enrolled in a randomized controlled prevention trial (RCT) and assessed their disease progression. Methods The multinational LipiDiDiet RCT targeted 311 individuals with IWG-1 defined prodromal AD. Based on centrally analyzed baseline biomarkers, participants were classified according to the IWG-2 and National Institute on Aging–Alzheimer’s Association (NIA-AA) 2011 and 2018 criteria. Linear mixed models were used to investigate the 2-year change in cognitive and functional performance (Neuropsychological Test Battery NTB Z scores, Clinical Dementia Rating-Sum of Boxes CDR-SB) (criteria × time interactions; baseline score, randomization group, sex, Mini-Mental State Examination (MMSE), and age also included in the models). Cox models adjusted for randomization group, MMSE, sex, age, and study site were used to investigate the risk of progression to dementia over 2 years. Results In total, 88%, 86%, and 69% of participants had abnormal cerebrospinal fluid (CSF) β-amyloid, total tau, and phosphorylated tau, respectively; 64% had an A+T+N+ profile (CSF available for N = 107). Cognitive-functional decline appeared to be more pronounced in the IWG-2 prodromal AD, NIA-AA 2011 high and intermediate AD likelihood, and NIA-AA 2018 AD groups, but few significant differences were observed between the groups within each set of criteria. Hazard ratio (95% CI) for dementia was 4.6 (1.6–13.7) for IWG-2 prodromal AD (reference group no prodromal AD), 7.4 (1.0–54.7) for NIA-AA 2011 high AD likelihood (reference group suspected non-AD pathology SNAP), and 9.4 (1.2–72.7) for NIA-AA 2018 AD (reference group non-Alzheimer’s pathologic change). Compared with the NIA-AA 2011 high AD likelihood group (abnormal β-amyloid and neuronal injury markers), disease progression was similar in the intermediate AD likelihood group (medial temporal lobe atrophy; no CSF available). Conclusions Despite being less restrictive than the other criteria, the IWG-1 criteria reliably identified individuals with AD pathology. More pragmatic and easily applicable selection criteria might be preferred due to feasibility in certain situations, e.g., in multidomain prevention trials that do not specifically target β-amyloid/tau pathologies. Trial registration Netherlands Trial Register, NL1620. Registered on 9 March 2009
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Affiliation(s)
- Anna Rosenberg
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.
| | - Alina Solomon
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Hilkka Soininen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Neurocenter, Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg, University of Maastricht, Maastricht, Netherlands.,Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, Netherlands
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Tobias Hartmann
- Deutsches Institut für Demenz Prävention (DIDP), Medical Faculty, and Department of Experimental Neurology, Saarland University, Homburg, Germany
| | - Miia Kivipelto
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Theme Aging, Karolinska University Hospital, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
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Tosun D, Veitch D, Aisen P, Jack CR, Jagust WJ, Petersen RC, Saykin AJ, Bollinger J, Ovod V, Mawuenyega KG, Bateman RJ, Shaw LM, Trojanowski JQ, Blennow K, Zetterberg H, Weiner MW. Detection of β-amyloid positivity in Alzheimer's Disease Neuroimaging Initiative participants with demographics, cognition, MRI and plasma biomarkers. Brain Commun 2021; 3:fcab008. [PMID: 33842885 PMCID: PMC8023542 DOI: 10.1093/braincomms/fcab008] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/02/2020] [Accepted: 12/04/2020] [Indexed: 01/18/2023] Open
Abstract
In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid42 or the β-amyloid42/β-amyloid40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid42/β-amyloid40, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid42/β-amyloid40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid42/β-amyloid40 may be improved by age and APOE genotype.
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Affiliation(s)
- Duygu Tosun
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Dallas Veitch
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Paul Aisen
- Alzheimer’s Therapeutic Research Institute (ATRI), Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | | | - William J Jagust
- School of Public Health and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Ronald C Petersen
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, 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 Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - James Bollinger
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Vitaliy Ovod
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Kwasi G Mawuenyega
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Michael W Weiner
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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125
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Lee S, Cho EJ, Kwak HB. Personalized Healthcare for Dementia. Healthcare (Basel) 2021; 9:healthcare9020128. [PMID: 33525656 PMCID: PMC7910906 DOI: 10.3390/healthcare9020128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/21/2021] [Accepted: 01/25/2021] [Indexed: 01/07/2023] Open
Abstract
Dementia is one of the most common health problems affecting older adults, and the population with dementia is growing. Dementia refers to a comprehensive syndrome rather than a specific disease and is characterized by the loss of cognitive abilities. Many factors are related to dementia, such as aging, genetic profile, systemic vascular disease, unhealthy diet, and physical inactivity. As the causes and types of dementia are diverse, personalized healthcare is required. In this review, we first summarize various diagnostic approaches associated with dementia. Particularly, clinical diagnosis methods, biomarkers, neuroimaging, and digital biomarkers based on advances in data science and wearable devices are comprehensively reviewed. We then discuss three effective approaches to treating dementia, including engineering design, exercise, and diet. In the engineering design section, recent advances in monitoring and drug delivery systems for dementia are introduced. Additionally, we describe the effects of exercise on the treatment of dementia, especially focusing on the effects of aerobic and resistance training on cognitive function, and the effects of diets such as the Mediterranean diet and ketogenic diet on dementia.
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Affiliation(s)
- Seunghyeon Lee
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (E.-J.C.)
- Department of Chemical Engineering, Inha University, Incheon 22212, Korea
| | - Eun-Jeong Cho
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (E.-J.C.)
| | - Hyo-Bum Kwak
- Program in Biomedical Science and Engineering, Inha University, Incheon 22212, Korea; (S.L.); (E.-J.C.)
- Correspondence: ; Tel.: +82-32-860-8183
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126
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Pelkmans W, Legdeur N, Ten Kate M, Barkhof F, Yaqub MM, Holstege H, van Berckel BNM, Scheltens P, van der Flier WM, Visser PJ, Tijms BM. Amyloid-β, cortical thickness, and subsequent cognitive decline in cognitively normal oldest-old. Ann Clin Transl Neurol 2021; 8:348-358. [PMID: 33421355 PMCID: PMC7886045 DOI: 10.1002/acn3.51273] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 12/14/2022] Open
Abstract
Objective To investigate the relationship between amyloid‐β (Aβ) deposition and markers of brain structure on cognitive decline in oldest‐old individuals with initial normal cognition. Methods We studied cognitive functioning in four domains at baseline and change over time in fifty‐seven cognitively intact individuals from the EMIF‐AD 90+ study. Predictors were Aβ status determined by [18F]‐flutemetamol PET (normal = Aβ − vs. abnormal = Aβ+), cortical thickness in 34 regions and hippocampal volume. Mediation analyses were performed to test whether effects of Aβ on cognitive decline were mediated by atrophy of specific anatomical brain areas. Results Subjects had a mean age of 92.7 ± 2.9 years, of whom 19 (33%) were Aβ+. Compared to Aβ−, Aβ+ individuals showed steeper decline on memory (β ± SE = −0.26 ± 0.09), and processing speed (β ± SE = −0.18 ± 0.08) performance over 1.5 years (P < 0.05). Furthermore, medial and lateral temporal lobe atrophy was associated with steeper decline in memory and language across individuals. Mediation analyses revealed that part of the memory decline observed in Aβ+ individuals was mediated through parahippocampal atrophy. Interpretation These results show that Aβ abnormality even in the oldest old with initially normal cognition is not part of normal aging, but is associated with a decline in cognitive functioning. Other pathologies may also contribute to decline in the oldest old as cortical thickness predicted cognitive decline similarly in individuals with and without Aβ pathology.
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Affiliation(s)
- Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Nienke Legdeur
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Queen Square Institute of Neurology and Centre for Medical Image Computing, UCL, London, UK
| | - Maqsood M Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands.,Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology I Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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127
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Functional connectivity differences in Alzheimer's disease and amnestic mild cognitive impairment associated with AT(N) classification and anosognosia. Neurobiol Aging 2021; 101:22-39. [PMID: 33561787 DOI: 10.1016/j.neurobiolaging.2020.12.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 12/24/2020] [Accepted: 12/28/2020] [Indexed: 11/22/2022]
Abstract
Alzheimer's continuum biological profiles (A+T-N-, A+T+N-, A+T-N+, and A+T+N+) were established in the 2018 National Institute on Aging and Alzheimer's Association research framework for Alzheimer's disease (AD). We aim to assess the relation between AT(N) biomarker profiles and brain functional connectivity (FC) and assess the neural correlates of anosognosia. We assessed local functional coupling and between-network connectivity through between-group intrinsic local correlation and independent component analyses. The neural correlates of anosognosia were assessed via voxel-wise linear regression analysis in prodromal AD. Statistical significance for the FC analysis was set at p ≤ 0.05 false discovery rate (FDR)-corrected for cluster size. One hundred and twenty-one and 73 participants were included in the FC and the anosognosia analysis, respectively. The FC in the default mode network is greater in prodromal AD than AD with dementia (i.e., local correlation: T = 8.26, p-FDR < 0.001, k = 1179; independent component analysis: cerebellar network, T = 4.01, p-FDR = 0.0012, k = 493). The default mode network is persistently affected in the early stages of Alzheimer's biological continuum. The anterior cingulate cortex (T = 2.52, p-FDR = 0.043, k = 704) is associated with anosognosia in prodromal AD.
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128
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Gustavson DE, Jak AJ, Elman JA, Panizzon MS, Franz CE, Gifford KA, Reynolds CA, Toomey R, Lyons MJ, Kremen WS. How Well Does Subjective Cognitive Decline Correspond to Objectively Measured Cognitive Decline? Assessment of 10-12 Year Change. J Alzheimers Dis 2021; 83:291-304. [PMID: 34308902 PMCID: PMC8482061 DOI: 10.3233/jad-210123] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Although not strongly correlated with current objective cognitive ability, subjective cognitive decline (SCD) is a risk factor for Alzheimer's disease. Most studies focus on SCD in relation to future decline rather than objective prior decline that it purportedly measures. OBJECTIVE We evaluated whether self-report of cognitive decline-as a continuous measure-corresponds to objectively-assessed episodic memory and executive function decline across the same period. METHODS 1,170 men completed the Everyday Cognition Questionnaire (ECog) at mean age 68 assessing subjective changes in cognitive ability relative to 10 years prior. A subset had mild cognitive impairment (MCI), but MCI was diagnosed without regard to subjective decline. Participants completed up to 3 objective assessments of memory and executive function (M = 56, 62, and 68 years). Informant-reported ECogs were completed for 1,045 individuals. Analyses controlled for depression and anxiety symptoms assessed at mean age 68. RESULTS Participant-reported ECog scores were modestly associated with objective decline for memory (β= -0.23, 95%CI [-0.37, -0.10]) and executive function (β= -0.19, 95%CI [-0.33, -0.05]) over the same time period. However, these associations were nonsignificant after excluding MCI cases. Results were similar for informant ratings. Participant-rated ECog scores were more strongly associated with concurrent depression and anxiety symptoms, (β= 0.44, 95%CI [0.36, 0.53]). CONCLUSION Continuous SCD scores are correlated with prior objective cognitive changes in non-demented individuals, though this association appears driven by individuals with current MCI. However, participants' current depression and anxiety ratings tend to be strongly associated with their SCD ratings. Thus, what primarily drives SCD ratings remains unclear.
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Affiliation(s)
- Daniel E. Gustavson
- Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN
| | - Amy J. Jak
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Psychology Service, Veterans Affairs San Diego Healthcare system, La Jolla, CA
| | - Jeremy A. Elman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Carol E. Franz
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, La Jolla, CA
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129
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Triaca V, Ruberti F, Canu N. NGF and the Amyloid Precursor Protein in Alzheimer's Disease: From Molecular Players to Neuronal Circuits. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1331:145-165. [PMID: 34453297 DOI: 10.1007/978-3-030-74046-7_10] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Alzheimer's disease (AD), one of the most common causes of dementia in elderly people, is characterized by progressive impairment in cognitive function, early degeneration of basal forebrain cholinergic neurons (BFCNs), abnormal metabolism of the amyloid precursor protein (APP), amyloid beta-peptide (Aβ) depositions, and neurofibrillary tangles. According to the cholinergic hypothesis, dysfunction of acetylcholine-containing neurons in the basal forebrain contributes markedly to the cognitive decline observed in AD. In addition, the neurotrophic factor hypothesis posits that the loss nerve growth factor (NGF) signalling in AD may account for the vulnerability to atrophy of BFCNs and consequent impairment of cholinergic functions. Though acetylcholinesterase inhibitors provide only partial and symptomatic relief to AD patients, emerging data from in vivo magnetic resonance imaging (MRI) and positron emission tomography (PET) studies in mild cognitive impairment (MCI) and AD patients highlight the early involvement of BFCNs in MCI and the early phase of AD. These data support the cholinergic and neurotrophic hypotheses of AD and suggest new targets for AD therapy.Different mechanisms account for selective vulnerability of BFCNs to AD pathology, with regard to altered metabolism of APP and tau. In this review, we provide a general overview of the current knowledge of NGF and APP interplay, focusing on the role of APP in regulating NGF receptors trafficking/signalling and on the involvement of NGF in modulating phosphorylation of APP, which in turn controls APP intracellular trafficking and processing. Moreover, we highlight the consequences of APP interaction with p75NTR and TrkA receptor, which share the same binding site within the APP juxta-membrane domain. We underline the importance of insulin dysmetabolism in AD pathology, in the light of our recent data showing that overlapping intracellular signalling pathways stimulated by NGF or insulin can be compensatory. In particular, NGF-based signalling is able to ameliorates deficiencies in insulin signalling in the medial septum of 3×Tg-AD mice. Finally, we present an overview of NGF-regulated microRNAs (miRNAs). These small non-coding RNAs are involved in post-transcriptional regulation of gene expression , and we focus on a subset that are specifically deregulated in AD and thus potentially contribute to its pathology.
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Affiliation(s)
- Viviana Triaca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Campus A. Buzzati-Traverso, Monterotondo, RM, Italy
| | - Francesca Ruberti
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Campus A. Buzzati-Traverso, Monterotondo, RM, Italy
| | - Nadia Canu
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Campus A. Buzzati-Traverso, Monterotondo, RM, Italy. .,Department of System Medicine, Section of Physiology, University of Rome "Tor Vergata", Rome, Italy.
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130
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Verberk IMW, Thijssen E, Koelewijn J, Mauroo K, Vanbrabant J, de Wilde A, Zwan MD, Verfaillie SCJ, Ossenkoppele R, Barkhof F, van Berckel BNM, Scheltens P, van der Flier WM, Stoops E, Vanderstichele HM, Teunissen CE. Combination of plasma amyloid beta (1-42/1-40) and glial fibrillary acidic protein strongly associates with cerebral amyloid pathology. ALZHEIMERS RESEARCH & THERAPY 2020; 12:118. [PMID: 32988409 PMCID: PMC7523295 DOI: 10.1186/s13195-020-00682-7] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 09/10/2020] [Indexed: 01/09/2023]
Abstract
BACKGROUND Blood-based biomarkers for Alzheimer's disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity. METHODS We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET-), mild cognitive impairment (26 PET+, 24 PET-), or AD-dementia (132 PET+). Plasma Abeta(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald's backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman's correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA). RESULTS Abeta(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83-93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = - 0.40 to - 0.26; NfL: range sβ = - 0.35 to - 0.18; all: p < 0.002), whereas Abeta(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 - 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman's rho> 0.33, p < 0.001). Abeta(1-42/1-40) showed a moderate negative correlation with MTA (Spearman's rho = - 0.24, p = 0.001). DISCUSSION AND CONCLUSIONS Combination of plasma Abeta(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.
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Affiliation(s)
- Inge M W Verberk
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. .,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Elisabeth Thijssen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Jannet Koelewijn
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | | | | | - Arno de Wilde
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marissa D Zwan
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sander C J Verfaillie
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | | | | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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