1
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Kozin SA, Kechko OI, Adzhubei AA, Makarov AA, Mitkevich VA. Switching On/Off Amyloid Plaque Formation in Transgenic Animal Models of Alzheimer's Disease. Int J Mol Sci 2023; 25:72. [PMID: 38203242 PMCID: PMC10778642 DOI: 10.3390/ijms25010072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 12/17/2023] [Accepted: 12/18/2023] [Indexed: 01/12/2024] Open
Abstract
A hallmark of Alzheimer's disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis, any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease-modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ-soluble protofibrils was approved by the US FDA for AD therapy, thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms were widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7-Aβ) and the α4β2 nicotinic acetylcholine receptor.
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Affiliation(s)
- Sergey A. Kozin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.I.K.); (A.A.A.); (A.A.M.)
| | | | | | | | - Vladimir A. Mitkevich
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.I.K.); (A.A.A.); (A.A.M.)
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2
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Gouilly D, Rafiq M, Nogueira L, Salabert AS, Payoux P, Péran P, Pariente J. Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology. Rev Neurol (Paris) 2023; 179:812-830. [PMID: 36906457 DOI: 10.1016/j.neurol.2022.12.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 10/02/2022] [Accepted: 12/02/2022] [Indexed: 03/13/2023]
Abstract
Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.
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Affiliation(s)
- D Gouilly
- Toulouse Neuroimaging Center, Toulouse, France.
| | - M Rafiq
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France
| | - L Nogueira
- Department of Cell Biology and Cytology, CHU Toulouse Purpan, France
| | - A-S Salabert
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France
| | - P Payoux
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
| | - P Péran
- Toulouse Neuroimaging Center, Toulouse, France
| | - J Pariente
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
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3
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Høilund-Carlsen PF, Revheim ME, Costa T, Kepp KP, Castellani RJ, Perry G, Alavi A, Barrio JR. FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls. Diagnostics (Basel) 2023; 13:2254. [PMID: 37443645 DOI: 10.3390/diagnostics13132254] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.
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Affiliation(s)
- Poul F Høilund-Carlsen
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark
- Research Unit of Clinical Physiology and Nuclear Medicine, Department of Clinical Research, University of Southern Denmark, 5230 Odense M, Denmark
| | - Mona-Elisabeth Revheim
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, 0372 Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, 0313 Oslo, Norway
| | - Tommaso Costa
- GDS, Department of Psychology, Koelliker Hospital, University of Turin, 10124 Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Kasper P Kepp
- Section of Biophysical and Biomedicinal Chemistry, DTU Chemistry, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Rudolph J Castellani
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - George Perry
- Department of Neuroscience, Developmental and Regenerative Biology and Genetics of Neurodegeneration, Departments of Psychiatry and Neuroscience, University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Abass Alavi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jorge R Barrio
- Department of Molecular and Medical Pharmacology, David Geffen UCLA School of Medicine, Los Angeles, CA 90095, USA
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4
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Kozin SA. Role of Interaction between Zinc and Amyloid Beta in Pathogenesis of Alzheimer’s Disease. BIOCHEMISTRY (MOSCOW) 2023; 88:S75-S87. [PMID: 37069115 DOI: 10.1134/s0006297923140055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Progression of Alzheimer's disease is accompanied by the appearance of extracellular deposits in the brain tissues of patients with characteristic supramolecular morphology (amyloid plaques) the main components of which are β-amyloid isoforms (Aβ) and biometal ions (zinc, copper, iron). For nearly 40 years and up to the present time, the vast majority of experimental data indicate critical role of formation and accumulation of amyloid plaques (cerebral amyloidogenesis) in pathogenesis of Alzheimer's disease, however, nature of the molecular agents that initiate cerebral amyloidogenesis, as well as causes of aggregation of the native Aβ molecules in vivo remained unknown for a long time. This review discusses the current level of fundamental knowledge about the molecular mechanisms of interactions of zinc ions with a number of Aβ isoforms present in amyloid plaques of the patients with Alzheimer's disease, and also shows how this knowledge made it possible to identify driving forces of the cerebral amyloidogenesis in Alzheimer's disease and made it possible to determine fundamentally new biomarkers and drug targets as part of development of innovative strategy for diagnosis and treatment of Alzheimer's disease.
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Affiliation(s)
- Sergey A Kozin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
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5
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Tippett LJ, Cawston EE, Morgan CA, Melzer TR, Brickell KL, Ilse C, Cheung G, Kirk IJ, Roberts RP, Govender J, Griner L, Le Heron C, Buchanan S, Port W, Dudley M, Anderson TJ, Williams JM, Cutfield NJ, Dalrymple-Alford JC, Wood P. Dementia Prevention Research Clinic: a longitudinal study investigating factors influencing the development of Alzheimer’s disease in Aotearoa, New Zealand. J R Soc N Z 2022. [DOI: 10.1080/03036758.2022.2098780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Affiliation(s)
- Lynette J. Tippett
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Erin E. Cawston
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Catherine A. Morgan
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tracy R. Melzer
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Kiri L. Brickell
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Christina Ilse
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Gary Cheung
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Ian J. Kirk
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Reece P. Roberts
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Jane Govender
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Leon Griner
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Campbell Le Heron
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
| | - Sarah Buchanan
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Waiora Port
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Makarena Dudley
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tim J. Anderson
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Joanna M. Williams
- NZ-Dementia Prevention Research Clinic, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Department of Anatomy, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Nicholas J. Cutfield
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - John C. Dalrymple-Alford
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Phil Wood
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Ministry of Health, Wellington, New Zealand
- Department of Older Adults and Home Health, Waitemata District Health Board, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
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6
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Riphagen JM, Suresh MB, Salat DH. The canonical pattern of Alzheimer's disease atrophy is linked to white matter hyperintensities in normal controls, differently in normal controls compared to in AD. Neurobiol Aging 2022; 114:105-112. [PMID: 35414420 PMCID: PMC9387174 DOI: 10.1016/j.neurobiolaging.2022.02.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 02/16/2022] [Accepted: 02/19/2022] [Indexed: 11/25/2022]
Abstract
White matter signal abnormalities (WMSA), either hypo- or hyperintensities in MRI imaging, are considered a proxy of cerebrovascular pathology and contribute to, and modulate, the clinical presentation of Alzheimer's disease (AD), with cognitive dysfunction being apparent at lower levels of amyloid and/or tau pathology when lesions are present. To what extent the topography of cortical thinning associated with AD may be explained by WMSA remains unclear. Cortical thickness group difference maps and subgroup analyses show that the effect of WMSA on cortical thickness in cognitively normal participants has a higher overlap with the canonical pattern of AD, compared to AD participants. (Age and sex-matched group of 119 NC (AV45 PET negative, CDR = 0) versus 119 participants with AD (AV45 PET-positive, CDR > 0.5). The canonical patterns of cortical atrophy thought to be specific to Alzheimer's disease are strongly linked to cerebrovascular pathology supporting a reinterpretation of the classical models of AD suggesting that a part of the typical AD pattern is due to co-localized cortical loss before the onset of AD.
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7
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Lazarev VF, Tsolaki M, Mikhaylova ER, Benken KA, Shevtsov MA, Nikotina AD, Lechpammer M, Mitkevich VA, Makarov AA, Moskalev AA, Kozin SA, Margulis BA, Guzhova IV, Nudler E. Extracellular GAPDH Promotes Alzheimer Disease Progression by Enhancing Amyloid-β Aggregation and Cytotoxicity. Aging Dis 2021; 12:1223-1237. [PMID: 34341704 PMCID: PMC8279520 DOI: 10.14336/ad.2020.1230] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 12/30/2020] [Indexed: 01/10/2023] Open
Abstract
Neuronal cell death at late stages of Alzheimer's disease (AD) causes the release of cytosolic proteins. One of the most abundant such proteins, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), forms stable aggregates with extracellular amyloid-β (Aβ). We detect these aggregates in cerebrospinal fluid (CSF) from AD patients at levels directly proportional to the progressive stages of AD. We found that GAPDH forms a covalent bond with Q15 of Aβ that is mediated by transglutaminase (tTG). The Q15A substitution weakens the interaction between Aβ and GAPDH and reduces Aβ-GAPDH cytotoxicity. Lentivirus-driven GAPDH overexpression in two AD animal models increased the level of apoptosis of hippocampal cells, neural degeneration, and cognitive dysfunction. In contrast, in vivo knockdown of GAPDH reversed these pathogenic abnormalities suggesting a pivotal role of GAPDH in Aβ-stimulated neurodegeneration. CSF from animals with enhanced GAPDH expression demonstrates increased cytotoxicity in vitro. Furthermore, RX-624, a specific GAPDH small molecular ligand reduced accumulation of Aβ aggregates and reversed memory deficit in AD transgenic mice. These findings argue that extracellular GAPDH compromises Aβ clearance and accelerates neurodegeneration, and, thus, is a promising pharmacological target for AD.
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Affiliation(s)
- Vladimir F Lazarev
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
| | - Magda Tsolaki
- 1 University Department of Neurology, AHEPA hospital Aristotle University of Thessaloniki and Greek Alzheimer Association, Thessaloniki, Greece.
| | - Elena R Mikhaylova
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
| | | | - Maxim A Shevtsov
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
- Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
| | - Alina D Nikotina
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
| | - Mirna Lechpammer
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
| | - Vladimir A Mitkevich
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
| | - Alexander A Makarov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
| | - Alexey A Moskalev
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
- Institute of Biology of Komi Scientific Centre of The Ural Branch of The Russian Academy of Sciences, Kommunisticheskaya, Russia.
| | - Sergey A Kozin
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
| | - Boris A Margulis
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
| | - Irina V Guzhova
- Institute of Cytology of the Russian Academy of Sciences (RAS), Petersburg, Russia.
| | - Evgeny Nudler
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
- Howard Hughes Medical Institute, New York University School of Medicine, New York, NY, USA.
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8
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Rockwood K. Open peer review commentary on building clinically relevant outcomes across the Alzheimer's disease spectrum. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12192. [PMID: 34195351 PMCID: PMC8234695 DOI: 10.1002/trc2.12192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 05/06/2021] [Indexed: 12/02/2022]
Affiliation(s)
- Kenneth Rockwood
- Dalhousie UniversityHalifaxNova ScotiaCanada
- Elder Care NetworkNova Scotia HealthHalifaxNova ScotiaCanada
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9
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Kapoor A, Bartha R, Black SE, Borrie M, Freedman M, Gao F, Herrmann N, Mandzia J, Ozzoude M, Ramirez J, Scott CJM, Symons S, Fischer CE, Frank A, Seitz D, Wolf MU, Verhoeff NPLG, Naglie G, Reichman W, Masellis M, Mitchell SB, Tang-Wai DF, Tartaglia MC, Kumar S, Pollock BG, Rajji TK, Finger E, Pasternak SH, Swartz RH. Structural Brain Magnetic Resonance Imaging to Rule Out Comorbid Pathology in the Assessment of Alzheimer's Disease Dementia: Findings from the Ontario Neurodegenerative Disease Research Initiative (ONDRI) Study and Clinical Trials Over the Past 10 Years. J Alzheimers Dis 2021; 74:747-757. [PMID: 32116253 PMCID: PMC7242844 DOI: 10.3233/jad-191097] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND/OBJECTIVE Structural brain magnetic resonance imaging (MRI) is not mandatory in Alzheimer's disease (AD) research or clinical guidelines. We aimed to explore the use of structural brain MRI in AD/mild cognitive impairment (MCI) trials over the past 10 years and determine the frequency with which inclusion of standardized structural MRI acquisitions detects comorbid vascular and non-vascular pathologies. METHODS We systematically searched ClinicalTrials.gov for AD clinical trials to determine their neuroimaging criteria and then used data from an AD/MCI cohort who underwent standardized MRI protocols, to determine type and incidence of clinically relevant comorbid pathologies. RESULTS Of 210 AD clinical trials, 105 (50%) included structural brain imaging in their eligibility criteria. Only 58 (27.6%) required MRI. 16,479 of 53,755 (30.7%) AD participants were in trials requiring MRI. In the observational AD/MCI cohort, 141 patients met clinical criteria; 22 (15.6%) had relevant MRI findings, of which 15 (10.6%) were exclusionary for the study. DISCUSSION In AD clinical trials over the last 10 years, over two-thirds of participants could have been enrolled without brain MRI and half without even a brain CT. In a study sample, relevant comorbid pathology was found in 15% of participants, despite careful screening. Standardized structural MRI should be incorporated into NIA-AA diagnostic guidelines (when available) and research frameworks routinely to reduce diagnostic heterogeneity.
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Affiliation(s)
| | - Robert Bartha
- Robarts Research Institute and the Department of Medical Biophysics, the University of Western Ontario, London, ON, Canada
| | - Sandra E Black
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | - Michael Borrie
- Parkwood Institute, St. Joseph's Health Care Center, London, ON, Canada
| | - Morris Freedman
- University of Toronto, Toronto, ON, Canada.,Rotman Research Institute of Baycrest Health Sciences, Toronto, ON, Canada.,Baycrest Health Sciences, Toronto, ON, Canada
| | - Fuqiang Gao
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Nathan Herrmann
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | - Jennifer Mandzia
- Western University, London, ON, Canada.,London Health Sciences Centre, London, ON, Canada
| | - Miracle Ozzoude
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | - Sean Symons
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Research, the Li Ka Shing Knowledge Institute, St. Michaels Hospital, Toronto, ON, Canada
| | | | - Dallas Seitz
- Department of Psychiatry and Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Michael Uri Wolf
- University of Toronto, Toronto, ON, Canada.,Baycrest Health Sciences, Toronto, ON, Canada
| | | | - Gary Naglie
- University of Toronto, Toronto, ON, Canada.,Rotman Research Institute of Baycrest Health Sciences, Toronto, ON, Canada.,Baycrest Health Sciences, Toronto, ON, Canada
| | - William Reichman
- University of Toronto, Toronto, ON, Canada.,Baycrest Health Sciences, Toronto, ON, Canada
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | - Sara B Mitchell
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | - David F Tang-Wai
- University of Toronto, Toronto, ON, Canada.,University Health Network Memory Clinic, University of Toronto, Division of Neurology & Geriatric Medicine, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- University of Toronto, Toronto, ON, Canada.,Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
| | - Sanjeev Kumar
- University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Bruce G Pollock
- University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- University of Toronto, Toronto, ON, Canada.,Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Elizabeth Finger
- Parkwood Institute, St. Joseph's Health Care Center, London, ON, Canada.,Western University, London, ON, Canada
| | - Stephen H Pasternak
- Robarts Research Institute and the Department of Medical Biophysics, the University of Western Ontario, London, ON, Canada.,Parkwood Institute, St. Joseph's Health Care Center, London, ON, Canada.,Western University, London, ON, Canada
| | | | - Richard H Swartz
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,University of Toronto, Toronto, ON, Canada
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10
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Drake JD, Chambers AB, Ott BR, Daiello LA. Peripheral Markers of Vascular Endothelial Dysfunction Show Independent but Additive Relationships with Brain-Based Biomarkers in Association with Functional Impairment in Alzheimer's Disease. J Alzheimers Dis 2021; 80:1553-1565. [PMID: 33720880 PMCID: PMC8150492 DOI: 10.3233/jad-200759] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Cerebrovascular dysfunction confers risk for functional decline in Alzheimer's disease (AD), yet the clinical interplay of these two pathogenic processes is not well understood. OBJECTIVE We utilized Alzheimer's Disease Neuroimaging Initiative (ADNI) data to examine associations between peripherally derived soluble cell adhesion molecules (CAMs) and clinical diagnostic indicators of AD. METHODS Using generalized linear regression models, we examined cross-sectional relationships of soluble plasma vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-Selectin to baseline diagnosis and functional impairment (clinical dementia rating sum-of-boxes, CDR-SB) in the ADNI cohort (n = 112 AD, n = 396 mild cognitive impairment (MCI), n = 58 cognitively normal). We further analyzed associations of these biomarkers with brain-based AD biomarkers in a subset with available cerebrospinal fluid (CSF) data (n = 351). p-values derived from main effects and interaction terms from the linear regressions were used to assess the relationship between independent and dependent variables for significance (significance level was set at 0.05 a priori for all analysis). RESULTS Higher mean VCAM-1 (p = 0.0026) and ICAM-1 (p = 0.0189) levels were found in AD versus MCI groups; however, not in MCI versus cognitively normal groups. Only VCAM-1 was linked with CDR-SB scores (p = 0.0157), and APOE ɛ4 genotype modified this effect. We observed independent, additive associations when VCAM-1 and CSF amyloid-β (Aβ42), total tau, phosphorylated tau (P-tau), or P-tau/Aβ42 (all < p = 0.01) were combined in a CDR-SB model; ICAM-1 showed a similar pattern, but to a lesser extent. CONCLUSION Our findings indicate independent associations of plasma-based vascular biomarkers and CSF biomarkers with AD-related clinical impairment.
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Affiliation(s)
- Jonathan D Drake
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Alison B Chambers
- Department of Medicine, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Brian R Ott
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
| | - Lori A Daiello
- Alzheimer's Disease and Memory Disorders Center, Rhode Island Hospital, Providence, RI, USA.,Department of Neurology, Brown University Warren Alpert Medical School, Providence RI, USA
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11
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Moseholm KF, Tybjerg K, Jensen MK, Westendorp RGJ. Too narrow and too broad: Differentiating late-onset dementia from its historical entanglement with Alzheimer's disease. AGING BRAIN 2021; 1:100010. [PMID: 36911504 PMCID: PMC9997125 DOI: 10.1016/j.nbas.2021.100010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Affiliation(s)
- Kristine F Moseholm
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Denmark
| | - Karin Tybjerg
- Medical Museion, Department of Public Health, University of Copenhagen, Denmark.,Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | - Majken K Jensen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Denmark.,Center for Healthy Aging, University of Copenhagen, Denmark
| | - Rudi G J Westendorp
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Denmark.,Center for Healthy Aging, University of Copenhagen, Denmark
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12
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Camarda C, Torelli P, Pipia C, Sottile G, Cilluffo G, Camarda R. APOE Genotypes and Brain Imaging Classes in Normal Cognition, Mild Cognitive Impairment, and Alzheimer's Disease: A Longitudinal Study. Curr Alzheimer Res 2020; 17:766-780. [PMID: 33167837 DOI: 10.2174/1567205017666201109093314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 08/20/2020] [Accepted: 10/10/2020] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To evaluate in 419 stroke-free cognitively normal subjects (CN) aged 45-82 years covering during a long prospective study (11.54 ± 1.47 years) the preclinical to dementia spectrum: 1) the distribution of small vessel disease (V) and brain atrophy (A) aggregated as following: V-/A-, V-/A+, V+/A-, V+/A+; 2) the relationship of these imaging classes with individual apolipoprotein E (APOE) genotypes; 3) the risk of progression to Alzheimer Disease (AD) of the individual APOE genotypes. METHODS Participants underwent one baseline (t0), and 4 clinical and neuropsychological assessments (t1,t2,t3, and t4). Brain MRI was performed in all subjects at t0, t2, t3 and t4.. White matter hyperintensities were assessed through two visual rating scales. Lacunes were also rated. Subcortical and global brain atrophy were determined through the bicaudate ratio and the lateral ventricle to brain ratio, respectively. APOE genotypes were determined at t0 in all subjects. Cox proportional hazard model was used to evaluate the risk of progression to AD. RESULTS The imaging class of mixed type was very common in AD, and in non amnestic mild cognitive impaired APOE ε4 non carriers. In these subjects, frontal and parieto-occipital regions were most affected by small vessel disease. CONCLUSION Our findings suggest that the APOE ε3 allele is probably linked to the brain vascular pathology.
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Affiliation(s)
- Cecilia Camarda
- Department of Biomedicine, Neurosciences, and Advanced Diagnostics, University of Palermo, Palermo, Italy
| | - Paola Torelli
- Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy
| | | | - Gianluca Sottile
- Department of Economics, Business, and Statistics, University of Palermo, Palermo, Italy,Institute for Research and Biomedical Innovation (IRIB), National Research Council, Palermo, Italy
| | - Giovanna Cilluffo
- Institute for Research and Biomedical Innovation (IRIB), National Research Council, Palermo, Italy
| | - Rosolino Camarda
- Department of Experimental Biomedicine and Clinical Neurosciences, University of Palermo, Palermo, Italy
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13
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Guo T, Korman D, La Joie R, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Normalization of CSF pTau measurement by Aβ 40 improves its performance as a biomarker of Alzheimer's disease. Alzheimers Res Ther 2020; 12:97. [PMID: 32799929 PMCID: PMC7429887 DOI: 10.1186/s13195-020-00665-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 08/04/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Alzheimer's disease (AD)-related tauopathy can be measured with CSF phosphorylated tau (pTau) and tau PET. We aim to investigate the associations between these measurements and their relative ability to predict subsequent disease progression. METHODS In 219 cognitively unimpaired and 122 impaired Alzheimer's Disease Neuroimaging Initiative participants with concurrent amyloid-β (Aβ) PET (18F-florbetapir or 18F-florbetaben), 18F-flortaucipir (FTP) PET, CSF measurements, structural MRI, and cognition, we examined inter-relationships between these biomarkers and their predictions of subsequent FTP and cognition changes. RESULTS The use of a CSF pTau/Aβ40 ratio eliminated positive associations we observed between CSF pTau alone and CSF Aβ42 in the normal Aβ range likely reflecting individual differences in CSF production rather than pathology. Use of the CSF pTau/Aβ40 ratio also increased expected associations with Aβ PET, FTP PET, hippocampal volume, and cognitive decline compared to pTau alone. In Aβ+ individuals, abnormal CSF pTau/Aβ40 only individuals (26.7%) were 4 times more prevalent (p < 0.001) than abnormal FTP only individuals (6.8%). Furthermore, among individuals on the AD pathway, CSF pTau/Aβ40 mediates the association between Aβ PET and FTP PET accumulation, but FTP PET is more closely linked to subsequent cognitive decline than CSF pTau/Aβ40. CONCLUSIONS Together, these findings suggest that CSF pTau/Aβ40 may be a superior measure of tauopathy compared to CSF pTau alone, and CSF pTau/Aβ40 enables detection of tau accumulation at an earlier stage than FTP among Aβ+ individuals.
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Affiliation(s)
- Tengfei Guo
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA.
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Deniz Korman
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
| | - Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, 132 Barker Hall, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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14
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Mullane K, Williams M. Alzheimer’s disease beyond amyloid: Can the repetitive failures of amyloid-targeted therapeutics inform future approaches to dementia drug discovery? Biochem Pharmacol 2020; 177:113945. [DOI: 10.1016/j.bcp.2020.113945] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 03/31/2020] [Indexed: 12/12/2022]
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15
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Sachdev PS. Developing robust biomarkers for vascular cognitive disorders: adding 'V' to the AT(N) research framework. Curr Opin Psychiatry 2020; 33:148-155. [PMID: 31895155 DOI: 10.1097/yco.0000000000000577] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW The AT(N) research framework was introduced in 2018 to define Alzheimer's disease as a biological entity. It is recognized that Alzheimer's disease lesions rarely occur in isolation in older brains, with cerebrovascular disease (CVD) being a common comorbidity. To fully characterize the disorder of dementia, the AT(N) framework needs to be extended with biomarkers for other disorders. The present review examines some of the requirements for adding a 'V' to the AT(N), and examines the currently available biomarkers as definitive markers of CVD. RECENT FINDINGS Neuroimaging biomarkers of CVD have received the greatest attention, with rapid advances in MRI techniques showing the greatest promise. Challenges remain in standardization of techniques, validation of some of the results and assessing total CVD burden from diverse lesion types. Retinal imaging shows promise as a window to cerebral vasculature. Biochemical markers are advancing rapidly, but their specificity for CVD is not established. SUMMARY Biomarkers of CVD have seen rapid advances but further validation and determination of their specificity are needed before they can be reliably used to delineate a V in the AT(N) framework as definitive indicators of significant CVD.
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Affiliation(s)
- Perminder S Sachdev
- Centre for Healthy Brain Ageing, University of New South Wales and the Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia
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16
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Nirale P, Paul A, Yadav KS. Nanoemulsions for targeting the neurodegenerative diseases: Alzheimer's, Parkinson's and Prion's. Life Sci 2020; 245:117394. [PMID: 32017870 DOI: 10.1016/j.lfs.2020.117394] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 01/31/2020] [Indexed: 12/14/2022]
Abstract
Neurodegenerative diseases need the drugs to be delivered right inside the brain to maximizing the therapeutic effects. This can be achieved by use of novel targeted delivery systems such as nanoemulsions. Nanoemulsions (NE) are nano-sized emulsions that are manufactured for enhancing the delivery of drugs to the targeted site and minimize adverse effects and toxic reactions. Looking into the advanced pharmaceutical applications of NE, the present review gives an insight to the understanding of the application of NE in NDs like AD, PD and Prion's disease. The review also touches upon the pathophysiology of these ND diseases to have a clear understanding of the molecular aspects of the disease. Finally, the review sets a standpoint of nanoemulsion's significance in the treatment therapy of ND besides the drawbacks associated with the current drug therapy in NDs.
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Affiliation(s)
- Prabhuti Nirale
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS, Deemed to be University, Mumbai 400 056, India
| | - Ankita Paul
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS, Deemed to be University, Mumbai 400 056, India
| | - Khushwant S Yadav
- Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS, Deemed to be University, Mumbai 400 056, India.
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17
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Yoon B, Choi SH, Jeong JH, Park KW, Kim EJ, Hwang J, Jang JW, Kim HJ, Hong JY, Lee JM, Kang JH, Yoon SJ. Balance and Mobility Performance Along the Alzheimer’s Disease Spectrum. J Alzheimers Dis 2020; 73:633-644. [DOI: 10.3233/jad-190601] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University School of Medicine, Seoul, Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A Medical Center, Dong-A University College of Medicine, Busan, Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Korea
| | - Jihye Hwang
- Department of Neurology, Keimyung University Dongsan Medical Center, Daegu, Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, Korea
| | - Ju-Hee Kang
- Department of Pharmacology, Inha University School of Medicine, Incheon, Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Korea
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18
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Jack CR, Wiste HJ, Botha H, Weigand SD, Therneau TM, Knopman DS, Graff-Radford J, Jones DT, Ferman TJ, Boeve BF, Kantarci K, Lowe VJ, Vemuri P, Mielke MM, Fields JA, Machulda MM, Schwarz CG, Senjem ML, Gunter JL, Petersen RC. The bivariate distribution of amyloid-β and tau: relationship with established neurocognitive clinical syndromes. Brain 2019; 142:3230-3242. [PMID: 31501889 PMCID: PMC6763736 DOI: 10.1093/brain/awz268] [Citation(s) in RCA: 120] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 06/26/2019] [Accepted: 07/07/2019] [Indexed: 12/14/2022] Open
Abstract
Large phenotypically diverse research cohorts with both amyloid and tau PET have only recently come into existence. Our objective was to determine relationships between the bivariate distribution of amyloid-β and tau on PET and established clinical syndromes that are relevant to cognitive ageing and dementia. All individuals in this study were enrolled in the Mayo Clinic Study of Aging, a longitudinal population-based study of cognitive ageing, or the Mayo Alzheimer Disease Research Center, a longitudinal study of individuals recruited from clinical practice. We studied 1343 participants who had amyloid PET and tau PET from 2 April 2015 to 3 May 2019, and met criteria for membership in one of five clinical diagnostic groups: cognitively unimpaired, mild cognitive impairment, frontotemporal dementia, probable dementia with Lewy bodies, and Alzheimer clinical syndrome. We examined these clinical groups in relation to the bivariate distribution of amyloid and tau PET values. Individuals were grouped into amyloid (A)/tau (T) quadrants based on previously established abnormality cut points of standardized uptake value ratio 1.48 (A) and 1.33 (T). Individual participants largely fell into one of three amyloid/tau quadrants: low amyloid and low tau (A-T-), high amyloid and low tau (A+T-), or high amyloid and high tau (A+T+). Seventy per cent of cognitively unimpaired and 74% of FTD participants fell into the A-T- quadrant. Participants with mild cognitive impairment spanned the A-T- (42%), A+T- (28%), and A+T+ (27%) quadrants. Probable dementia with Lewy body participants spanned the A-T- (38%) and A+T- (44%) quadrants. Most (89%) participants with Alzheimer clinical syndrome fell into the A+T+ quadrant. These data support several conclusions. First, among 1343 participants, abnormal tau PET rarely occurred in the absence of abnormal amyloid PET, but the reverse was common. Thus, with rare exceptions, amyloidosis appears to be required for high levels of 3R/4R tau deposition. Second, abnormal amyloid PET is compatible with normal cognition but highly abnormal tau PET is not. These two conclusions support a dynamic biomarker model in which Alzheimer's disease is characterized first by the appearance of amyloidosis and later by tauopathy, with tauopathy being the proteinopathy associated with clinical symptoms. Third, bivariate amyloid and tau PET relationships differed across clinical groups and thus have a role for clarifying the aetiologies underlying neurocognitive clinical syndromes.
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Affiliation(s)
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Tanis J Ferman
- Department of Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
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19
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McRae-McKee K, Udeh-Momoh CT, Price G, Bajaj S, de Jager CA, Scott D, Hadjichrysanthou C, McNaughton E, Bracoud L, Ahmadi-Abhari S, de Wolf F, Anderson RM, Middleton LT. Perspective: Clinical relevance of the dichotomous classification of Alzheimer's disease biomarkers: Should there be a "gray zone"? Alzheimers Dement 2019; 15:1348-1356. [PMID: 31564609 DOI: 10.1016/j.jalz.2019.07.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 06/21/2019] [Accepted: 07/14/2019] [Indexed: 11/23/2022]
Abstract
The 2018 National Institute on Aging and the Alzheimer's Association (NIA-AA) research framework recently redefined Alzheimer's disease (AD) as a biological construct, based on in vivo biomarkers reflecting key neuropathologic features. Combinations of normal/abnormal levels of three biomarker categories, based on single thresholds, form the AD signature profile that defines the biological disease state as a continuum, independent of clinical symptomatology. While single thresholds may be useful in defining the biological signature profile, we provide evidence that their use in studies with cognitive outcomes merits further consideration. Using data from the Alzheimer's Disease Neuroimaging Initiative with a focus on cortical amyloid binding, we discuss the limitations of applying the biological definition of disease status as a tool to define the increased likelihood of the onset of the Alzheimer's clinical syndrome and the effects that this may have on trial study design. We also suggest potential research objectives going forward and what the related data requirements would be.
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Affiliation(s)
- Kevin McRae-McKee
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Chinedu T Udeh-Momoh
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Geraint Price
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Sumali Bajaj
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Celeste A de Jager
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Christoforos Hadjichrysanthou
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Emily McNaughton
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Sara Ahmadi-Abhari
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Frank de Wolf
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Roy M Anderson
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Lefkos T Middleton
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom; Imperial College Healthcare NHS Trust, London, United Kingdom.
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20
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Puzo C, Labriola C, Sugarman MA, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Stein TD, Kowall NW, McKee AC, Mez J, Killiany RJ, Stern RA, Alosco ML. Independent effects of white matter hyperintensities on cognitive, neuropsychiatric, and functional decline: a longitudinal investigation using the National Alzheimer's Coordinating Center Uniform Data Set. Alzheimers Res Ther 2019; 11:64. [PMID: 31351489 PMCID: PMC6661103 DOI: 10.1186/s13195-019-0521-0] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 07/14/2019] [Indexed: 01/18/2023]
Abstract
BACKGROUND Longitudinal investigations are needed to improve understanding of the contributions of cerebral small vessel disease to the clinical manifestation of Alzheimer's disease, particularly in the early disease stages. This study leveraged the National Alzheimer's Coordinating Center Uniform Data Set to longitudinally examine the association between white matter hyperintensities and neuropsychological, neuropsychiatric, and functional decline among participants with normal cognition. METHODS The sample included 465 participants from the National Alzheimer's Coordinating Center Uniform Data Set who had quantitated volume of white matter hyperintensities from fluid-attenuated inversion recovery MRI, had normal cognition at the time of their MRI, and were administered the National Alzheimer's Coordinating Center Uniform Data Set neuropsychological test battery within 1 year of study evaluation and had at least two post-MRI time points of clinical data. Neuropsychiatric status was assessed by the Geriatric Depression Scale-15 and Neuropsychiatric Inventory-Questionnaire. Clinical Dementia Rating Sum of Boxes defined functional status. For participants subsequently diagnosed with mild cognitive impairment (MCI) or dementia, their impairment must have been attributed to Alzheimer's disease (AD) to evaluate the relationships between WMH and the clinical presentation of AD. RESULTS Of the 465 participants, 56 converted to MCI or AD dementia (average follow-up = 5 years). Among the 465 participants, generalized estimating equations controlling for age, sex, race, education, APOE ε4, and total brain and hippocampal volume showed that higher baseline log-white matter hyperintensities predicted accelerated decline on the following neuropsychological tests in rank order of effect size: Trails B (p < 0.01), Digit Symbol Coding (p < 0.01), Logical Memory Immediate Recall (p = 0.02), Trail Making A (p < 0.01), and Semantic Fluency (p < 0.01). White matter hyperintensities predicted increases in Clinical Dementia Rating Sum of Boxes (p < 0.01) and Geriatric Depression Scale-15 scores (p = 0.01). Effect sizes were comparable to total brain and hippocampal volume. White matter hyperintensities did not predict diagnostic conversion. All effects also remained after including individuals with non-AD suspected etiologies for those who converted to MCI or dementia. CONCLUSIONS In this baseline cognitively normal sample, greater white matter hyperintensities were associated with accelerated cognitive, neuropsychiatric, and functional decline independent of traditional risk factors and MRI biomarkers for Alzheimer's disease.
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Affiliation(s)
- Christian Puzo
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Caroline Labriola
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Michael A Sugarman
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Brett Martin
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Joseph N Palmisano
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
| | - Eric G Steinberg
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
| | - Thor D Stein
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Neil W Kowall
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, USA
| | - Jesse Mez
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Ronald J Killiany
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, USA
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, USA
| | - Robert A Stern
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Departments of Neurosurgery and Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Michael L Alosco
- Boston University Alzheimer's Disease Center and CTE Center, Boston University School of Medicine, 72 E. Concord Street, Suite B7800, Boston, MA, 02118, USA.
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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