151
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Lim YY, Laws SM, Perin S, Pietrzak RH, Fowler C, Masters CL, Maruff P. BDNF VAL66MET polymorphism and memory decline across the spectrum of Alzheimer's disease. GENES BRAIN AND BEHAVIOR 2020; 20:e12724. [PMID: 33369083 DOI: 10.1111/gbb.12724] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 12/07/2020] [Accepted: 12/20/2020] [Indexed: 12/29/2022]
Abstract
The brain-derived neurotrophic factor (BDNF) Val66Met (rs6265) polymorphism has been shown to moderate the extent to which memory decline manifests in preclinical Alzheimer's disease (AD). To date, no study has examined the relationship between BDNF and memory in individuals across biologically confirmed AD clinical stages (i.e., Aβ+). We aimed to understand the effect of BDNF on episodic memory decline and clinical disease progression over 126 months in individuals with preclinical, prodromal and clinical AD. Participants enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study who were Aβ + (according to positron emission tomography), and cognitively normal (CN; n = 238), classified as having mild cognitive impairment (MCI; n = 80), or AD (n = 66) were included in this study. Cognition was evaluated at 18 month intervals using an established episodic memory composite score over 126 months. We observed that in Aβ + CNs, Met66 was associated with greater memory decline with increasing age and were 1.5 times more likely to progress to MCI/AD over 126 months. In Aβ + MCIs, there was no effect of Met66 on memory decline or on disease progression to AD over 126 months. In Aβ + AD, Val66 homozygotes showed greater memory decline, while Met66 carriers performed at a constant and very impaired level. Our current results illustrate the importance of time and disease severity to clinicopathological models of the role of BDNF Val66Met in memory decline and AD clinical progression. Specifically, the effect of BDNF on memory decline is greatest in preclinical AD and reduces as AD clinical disease severity increases.
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Affiliation(s)
- Yen Ying Lim
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Simon M Laws
- Collaborative Genomics and Translation Group, Strategic Research Centre for Precision Health, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia.,School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Australia
| | - Stephanie Perin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Robert H Pietrzak
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Christopher Fowler
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia.,Cogstate Ltd, Melbourne, Australia
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152
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Structural imaging outcomes in subjective cognitive decline: Community vs. clinical-based samples. Exp Gerontol 2020; 145:111216. [PMID: 33340685 DOI: 10.1016/j.exger.2020.111216] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 11/13/2020] [Accepted: 12/05/2020] [Indexed: 11/21/2022]
Abstract
Subjective cognitive decline (SCD) has been proposed as a preclinical stage of Alzheimer's disease (AD). Neuroimaging studies have suggested early AD-like structural brain alterations in SCD subjects compared to healthy controls. However, there is substantial heterogeneity in the results, which might depend on whether SCD samples were drawn from the community or from memory clinics. Here we reviewed brain atrophy, assessed through structural magnetic resonance imaging, separately for SCD-community and clinic-based samples. SCD-community samples show a more consistent pattern of atrophy, involving the hippocampus and temporal and parietal cortices. Similarly, in SCD-clinic samples the temporo-parietal cortex showed early vulnerability, however these studies reported a more heterogeneous atrophy pattern. Overall, these studies suggest both commonalities and differences in brain atrophy patterns between SCD clinical and community samples. In SCD-community, the temporal cortex is involved, while SCD-clinical exhibited a more complex pattern of atrophy, which may be related to a more heterogeneous sample reporting neuropsychiatric symptoms along with preclinical AD.
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153
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Dehghani C, Frost S, Jayasena R, Fowler C, Masters CL, Kanagasingam Y, Jiao H, Lim JKH, Chinnery HR, Downie LE. Morphometric Changes to Corneal Dendritic Cells in Individuals With Mild Cognitive Impairment. Front Neurosci 2020; 14:556137. [PMID: 33362451 PMCID: PMC7755610 DOI: 10.3389/fnins.2020.556137] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 11/09/2020] [Indexed: 11/13/2022] Open
Abstract
Purpose There has been increasing interest in identifying non-invasive, imaging biomarkers for neurodegenerative disorders of the central nervous system (CNS). The aim of this proof-of-concept study was to investigate whether corneal sensory nerve and dendritic cell (DC) parameters, captured using in vivo confocal microscopy (IVCM), are altered in individuals with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Methods Fifteen participants were recruited from the Australian Imaging Biomarkers and Lifestyle (AIBL) study in Melbourne, VIC, Australia. The cohort consisted of cognitively normal (CN) individuals (n = 5), and those with MCI (n = 5) and AD (n = 5). Participants underwent a slit lamp examination of the anterior segment, followed by corneal imaging using laser-scanning in vivo confocal microscopy (IVCM) of the central and inferior whorl regions. Corneal DC density, field area, perimeter, circularity index, aspect ratio, and roundness were quantified using Image J. Quantitative data were derived for corneal nerve parameters, including nerve fiber length (CNFL), fiber density (CNFD), branch density (CNBD), and diameter. Results Corneal DC field area and perimeter were greater in individuals with MCI, relative to CN controls, in both the central and inferior whorl regions (p < 0.05 for all comparisons). In addition, corneal DCs in the whorl region of MCI eyes had lower circularity and roundness indices and a higher aspect ratio relative to CNs (p < 0.05 for all comparisons). DC density was similar across participant groups in both corneal regions. There was a trend toward lower quantitative parameters for corneal nerve architecture in the AD and MCI groups compared with CN participants, however, the inter-group differences did not reach statistical significance. Central corneal nerve diameters were similar between groups. Conclusion This study is the first to report morphological differences in corneal DCs in humans with MCI. These differences were evident in both the central and mid-peripheral cornea, and in the absence of significant nerve abnormalities or a difference in DC density. These findings justify future large-scale studies to assess the utility of corneal IVCM and DC analysis for identifying early stage pathology in neurodegenerative disorders of the CNS.
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Affiliation(s)
- Cirous Dehghani
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia.,CSIRO, Australian e-Health Research Centre (AEHRC), Parkville, VIC, Australia.,Discipline of Optometry, University of Canberra, Canberra, ACT, Australia
| | - Shaun Frost
- CSIRO, Australian e-Health Research Centre (AEHRC), Floreat, WA, Australia
| | - Rajiv Jayasena
- CSIRO, Australian e-Health Research Centre (AEHRC), Parkville, VIC, Australia
| | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | | | - Haihan Jiao
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Jeremiah K H Lim
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia.,Optometry and Vision Science, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, Australia
| | - Holly R Chinnery
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
| | - Laura E Downie
- Department of Optometry and Vision Sciences, University of Melbourne, Parkville, VIC, Australia
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154
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Zhang Y, Hao Y, Li L, Xia K, Wu G. A Novel Computational Proxy for Characterizing Cognitive Reserve in Alzheimer's Disease. J Alzheimers Dis 2020; 78:1217-1228. [PMID: 33252088 DOI: 10.3233/jad-201011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
BACKGROUND Although the abnormal depositions of amyloid plaques and neurofibrillary tangles are the hallmark of Alzheimer's disease (AD), converging evidence shows that the individual's neurodegeneration trajectory is regulated by the brain's capability to maintain normal cognition. OBJECTIVE The concept of cognitive reserve has been introduced into the field of neuroscience, acting as a moderating factor for explaining the paradoxical relationship between the burden of AD pathology and the clinical outcome. It is of high demand to quantify the degree of conceptual cognitive reserve on an individual basis. METHODS We propose a novel statistical model to quantify an individual's cognitive reserve against neuropathological burdens, where the predictors include demographic data (such as age and gender), socioeconomic factors (such as education and occupation), cerebrospinal fluid biomarkers, and AD-related polygenetic risk score. We conceptualize cognitive reserve as a joint product of AD pathology and socioeconomic factors where their interaction manifests a significant role in counteracting the progression of AD in our statistical model. RESULTS We apply our statistical models to re-investigate the moderated neurodegeneration trajectory by considering cognitive reserve, where we have discovered that 1) high education individuals have significantly higher reserve against the neuropathology than the low education group; however, 2) the cognitive decline in the high education group is significantly faster than low education individuals after the level of pathological burden increases beyond the tipping point. CONCLUSION We propose a computational proxy of cognitive reserve that can be used in clinical routine to assess the progression of AD.
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Affiliation(s)
- Ying Zhang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yajing Hao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lang Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai Xia
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Guorong Wu
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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155
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Lim B, Prassas I, Diamandis EP. Alzheimer Disease Pathogenesis: The Role of Autoimmunity. J Appl Lab Med 2020; 6:756-764. [PMID: 33241314 DOI: 10.1093/jalm/jfaa171] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 08/26/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND In addition to deposits of amyloid β (Aβ) plaques and neurofibrillary tangles, growing evidence demonstrates that complex and multifaceted biological processes can arise during Alzheimer disease (AD) pathogenesis. The recent failures of clinical trials based on the amyloid hypothesis and the presence of Aβ plaques in cognitively healthy elderly persons without AD point toward a need to explore novel pathobiological mechanisms of AD. CONTENT In the search for alternative AD mechanisms, numerous genome-wide association studies and mechanistic discoveries suggest a potential immunologic component of the disease. However, new experimental tools are needed to uncover these immunogenic components. The current methods, such as ELISAs or protein microarrays, have limitations of low throughput and/or sensitivity and specificity. In this article, we briefly discuss evidence of potential autoimmune contributions to AD pathobiology, describe the current methods for identifying autoantibodies in patient fluids, and outline our own efforts to develop new techniques for novel autoantibody biomarker discovery. SUMMARY Uncovering the putative autoimmune components of AD may be crucial in paving the way to new concepts for pathogenesis, diagnosis, and therapy. IMPACT STATEMENT In addition to deposits of amyloid β plaques and neurofibrillary tangles, growing evidence demonstrates that complex and multifaceted biological processes can arise during Alzheimer disease (AD) pathogenesis. Numerous research directions, including genome-wide association, clinical correlation, and mechanistic studies, have pointed to a potential autoimmunologic contribution to AD pathology. We present research suggesting the association between autoimmunity and AD and demonstrate the need for new laboratory techniques to further characterize potential brain antigen-specific autoantibodies. Uncovering the putative autoimmune components of AD may be crucial in paving the way to new concepts for pathogenesis, diagnosis, and therapy.
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Affiliation(s)
- Bryant Lim
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Ioannis Prassas
- Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada
| | - Eleftherios P Diamandis
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.,Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, Canada.,Department of Clinical Biochemistry, University Health Network, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
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156
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van Havre Z, Maruff P, Villemagne VL, Mengersen K, Rousseau J, White N, Doecke JD. Identification of Pre-Clinical Alzheimer's Disease in a Population of Elderly Cognitively Normal Participants. J Alzheimers Dis 2020; 73:683-693. [PMID: 31868673 DOI: 10.3233/jad-191095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Alzheimer's disease (AD) has a long pathological process, with an approximate lead-time of 20 years. During the early stages of the disease process, little evidence of the building pathology is identifiable without cerebrospinal fluid and/or imaging analyses. Clinical manifestations of AD do not present until irreversible pathological changes have occurred. Given an opportunity to provide treatment prior to irreversible pathological change, this study aims to identify a subgroup of cognitively normal (CN) participants from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL), where subtle changes in cognition are indicative of early AD-related pathology. Using a Bayesian method for unsupervised clustering via mixture models, we define an aggregate measure of posterior probabilities (AMPP score) establishing the likelihood of pre-clinical AD. From Baseline through to 54 months, visuo-spatial function had the greatest contribution to the AMPP score, followed by attention and processing speed and visual memory. Participants with the highest AMPP scores had both increasing neo-cortical amyloid burden and decreasing hippocampus volume over 54 months, compared to those in the lowest category with stable amyloid burden and hippocampus volume. The identification of a possible pre-clinical stage in CN participants via this method, without the aid of disease specific biomarkers, represents an important step in utilizing the strength of cognitive composite scores for the early detection of AD pathology.
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Affiliation(s)
- Zoe van Havre
- ACEMS, Queensland University of Technology, Queensland, Australia.,CEREMADE, Universite Paris Dauphine, Paris, France
| | - Paul Maruff
- Mental Health Research Institute, The University of Melbourne, Parkville, Victoria, Australia.,CogState Ltd., Victoria, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Victoria, Australia.,Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Kerrie Mengersen
- ACEMS, Queensland University of Technology, Queensland, Australia
| | | | - Nicole White
- ACEMS, Queensland University of Technology, Queensland, Australia
| | - James D Doecke
- CSIRO Health and Biosecurity/Australian e-Health Research Centre, Herston, Queensland, Australia
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157
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Farrell ME, Jiang S, Schultz AP, Properzi MJ, Price JC, Becker JA, Jacobs HIL, Hanseeuw BJ, Rentz DM, Villemagne VL, Papp KV, Mormino EC, Betensky RA, Johnson KA, Sperling RA, Buckley RF. Defining the Lowest Threshold for Amyloid-PET to Predict Future Cognitive Decline and Amyloid Accumulation. Neurology 2020; 96:e619-e631. [PMID: 33199430 DOI: 10.1212/wnl.0000000000011214] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 09/21/2020] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION As clinical trials move toward earlier intervention, we sought to redefine the β-amyloid (Aβ)-PET threshold based on the lowest point in a baseline distribution that robustly predicts future Aβ accumulation and cognitive decline in 3 independent samples of clinically normal individuals. METHODS Sequential Aβ cutoffs were tested to identify the lowest cutoff associated with future change in cognition (Preclinical Alzheimer Cognitive Composite [PACC]) and Aβ-PET in clinically normal participants from the Harvard Aging Brain Study (n = 342), Australian Imaging, Biomarker and Lifestyle study of aging (n = 157), and Alzheimer's Disease Neuroimaging Initiative (n = 356). RESULTS Within samples, cutoffs derived from future Aβ-PET accumulation and PACC decline converged on the same inflection point, beyond which trajectories diverged from normal. Across samples, optimal cutoffs fell within a short range (Centiloid 15-18.5). DISCUSSION These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. Threshold convergence raises the possibility of contemporaneous early changes in Aβ and cognition. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that among clinically normal individuals a specific Aβ-PET threshold is predictive of cognitive decline.
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Affiliation(s)
- Michelle E Farrell
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Shu Jiang
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Aaron P Schultz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Michael J Properzi
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Julie C Price
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - J Alex Becker
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Heidi I L Jacobs
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Bernard J Hanseeuw
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Dorene M Rentz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Kathryn V Papp
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Elizabeth C Mormino
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rebecca A Betensky
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Keith A Johnson
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Reisa A Sperling
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rachel F Buckley
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia.
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158
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Toppala S, Ekblad LL, Lötjönen J, Helin S, Hurme S, Johansson J, Jula A, Karrasch M, Koikkalainen J, Laine H, Parkkola R, Viitanen M, Rinne JO. Midlife Insulin Resistance as a Predictor for Late-Life Cognitive Function and Cerebrovascular Lesions. J Alzheimers Dis 2020; 72:215-228. [PMID: 31561373 PMCID: PMC6839606 DOI: 10.3233/jad-190691] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background: Type 2 diabetes (T2DM) increases the risk for Alzheimer’s disease (AD) but not for AD neuropathology. The association between T2DM and AD is assumed to be mediated through vascular mechanisms. However, insulin resistance (IR), the hallmark of T2DM, has been shown to associate with AD neuropathology and cognitive decline. Objective: To evaluate if midlife IR predicts late-life cognitive performance and cerebrovascular lesions (white matter hyperintensities and total vascular burden), and whether cerebrovascular lesions and brain amyloid load are associated with cognitive functioning. Methods: This exposure-to-control follow-up study examined 60 volunteers without dementia (mean age 70.9 years) with neurocognitive testing, brain 3T-MRI and amyloid-PET imaging. The volunteers were recruited from the Finnish Health 2000 survey (n = 6062) to attend follow-up examinations in 2014–2016 according to their insulin sensitivity in 2000 and their APOE genotype. The exposure group (n = 30) had IR in 2000 and the 30 controls had normal insulin sensitivity. There were 15 APOEɛ4 carriers per group. Statistical analyses were performed with multivariable linear models. Results: At follow-up the IR+group performed worse on executive functions (p = 0.02) and processing speed (p = 0.007) than the IR- group. The groups did not differ in cerebrovascular lesions. No associations were found between cerebrovascular lesions and neurocognitive test scores. Brain amyloid deposition associated with slower processing speed. Conclusion: Midlife IR predicted poorer executive functions and slower processing speed, but not cerebrovascular lesions. Brain amyloid deposition was associated with slower processing speed. The association between midlife IR and late-life cognition might not be mediated through cerebrovascular lesions measured here.
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Affiliation(s)
- Sini Toppala
- Turku PET Centre, University of Turku, Finland.,Turku City Hospital, University of Turku, Finland
| | | | | | - Semi Helin
- Turku PET Centre, University of Turku, Finland
| | - Saija Hurme
- Department of Biostatistics, University of Turku, Finland
| | - Jarkko Johansson
- Turku PET Centre, University of Turku, Finland.,Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Antti Jula
- National Institute for Health and Welfare, Turku, Finland
| | - Mira Karrasch
- Department of Psychology, Åbo Akademi University, Turku, Finland
| | | | - Hanna Laine
- Turku City Hospital, University of Turku, Finland.,Department of Medicine, University of Turku, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, Turku University and Turku University Hospital, Turku, Finland
| | - Matti Viitanen
- Turku City Hospital, University of Turku, Finland.,Clinical Geriatrics, Karolinska Institutet, Karolinska University Hospital, Huddinge, Sweden
| | - Juha O Rinne
- Turku PET Centre, University of Turku, Finland.,Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
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159
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Emrani S, Arain HA, DeMarshall C, Nuriel T. APOE4 is associated with cognitive and pathological heterogeneity in patients with Alzheimer's disease: a systematic review. Alzheimers Res Ther 2020; 12:141. [PMID: 33148345 PMCID: PMC7643479 DOI: 10.1186/s13195-020-00712-4] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 10/22/2020] [Indexed: 02/06/2023]
Abstract
Possession of the ε4 allele of apolipoprotein E (APOE) is the primary genetic risk factor for the sporadic form of Alzheimer's disease (AD). While researchers have extensively characterized the impact that APOE ε4 (APOE4) has on the susceptibility of AD, far fewer studies have investigated the phenotypic differences of patients with AD who are APOE4 carriers vs. those who are non-carriers. In order to understand these differences, we performed a qualitative systematic literature review of the reported cognitive and pathological differences between APOE4-positive (APOE4+) vs. APOE4-negative (APOE4-) AD patients. The studies performed on this topic to date suggest that APOE4 is not only an important mediator of AD susceptibility, but that it likely confers specific phenotypic heterogeneity in AD presentation, as well. Specifically, APOE4+ AD patients appear to possess more tau accumulation and brain atrophy in the medial temporal lobe, resulting in greater memory impairment, compared to APOE4- AD patients. On the other hand, APOE4- AD patients appear to possess more tau accumulation and brain atrophy in the frontal and parietal lobes, resulting in greater impairment in executive function, visuospatial abilities, and language, compared to APOE4+ AD patients. Although more work is necessary to validate and interrogate these findings, these initial observations of pathological and cognitive heterogeneity between APOE4+ vs. APOE4- AD patients suggest that there is a fundamental divergence in AD manifestation related to APOE genotype, which may have important implications in regard to the therapeutic treatment of these two patient populations.
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Affiliation(s)
- Sheina Emrani
- Department of Psychology, Rowan University, 201 Mullica Hill Road, Glassboro, NJ, 08028, USA
| | - Hirra A Arain
- Department of Pathology and Cell Biology, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, 630 West 168th Street, New York, NY, 10032, USA
| | - Cassandra DeMarshall
- Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, One Medical Center Drive, Stratford, NJ, 08084, USA
| | - Tal Nuriel
- Department of Pathology and Cell Biology, Columbia University, 630 West 168th Street, New York, NY, 10032, USA.
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, 630 West 168th Street, New York, NY, 10032, USA.
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160
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Baek MS, Cho H, Lee HS, Lee JH, Ryu YH, Lyoo CH. Effect of APOE ε4 genotype on amyloid-β and tau accumulation in Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:140. [PMID: 33129364 PMCID: PMC7603688 DOI: 10.1186/s13195-020-00710-6] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 10/20/2020] [Indexed: 02/12/2023]
Abstract
Background To assess the effects of apolipoprotein E (ApoE) ε4 genotype on amyloid-β (Aβ) and tau burden and their longitudinal changes in Alzheimer’s disease (AD) spectrum. Methods Among 272 individuals who underwent PET scans (18F-florbetaben for Aβ and 18F-flortaucipir for tau) and ApoE genotyping, 187 individuals completed 2-year follow-up PET scans. After correcting for the partial volume effect, we compared the standardized uptake value ratio (SUVR) for Aβ and tau burden between the ε4+ and ε4− groups. By using a linear mixed-effect model, we measured changes in SUVR in the ApoE ε4+ and ε4− groups. Results The ε4+ group showed greater baseline Aβ burden in the diffuse cortical regions and greater tau burden in the lateral, and medial temporal, cingulate, and insula cortices. Tau accumulation rate was higher in the parietal, occipital, lateral, and medial temporal cortices in the ε4+ group. In Aβ+ individuals, baseline tau burden was greater in the medial temporal cortex, while Aβ burden was conversely greater in the ε4− group. Tau accumulation rate was higher in the ε4+ group in a small region in the lateral temporal cortex. The effect of ApoE ε4 on enhanced tau accumulation persisted even after adjusting for the global cortical Aβ burden. Conclusions Progressive tau accumulation may be more prominent in ε4 carriers, particularly in the medial and lateral temporal cortices. ApoE ε4 allele has differential effects on the Aβ burden depending on the existing amyloidosis and may enhance vulnerability to progressive tau accumulation in the AD spectrum independent of Aβ. Supplementary information Supplementary information accompanies this paper at 10.1186/s13195-020-00710-6.
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Affiliation(s)
- Min Seok Baek
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jae Hoon Lee
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea.
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161
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Squarzoni P, Faria DDP, Yassuda MS, Porto FHDG, Coutinho AM, Costa NAD, Nitrini R, Forlenza OV, Duran FLDS, Brucki SMD, Buchpiguel CA, Busatto GF. Relationship Between PET-Assessed Amyloid Burden and Visual and Verbal Episodic Memory Performance in Elderly Subjects. J Alzheimers Dis 2020; 78:229-244. [PMID: 32986673 DOI: 10.3233/jad-200758] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Studies of elderly subjects using biomarkers that are proxies for Alzheimer's disease (AD) pathology have the potential to document meaningful relationships between cognitive performance and biomarker changes along the AD continuum. OBJECTIVE To document cognitive performance differences across distinct AD stages using a categorization based on the presence of PET-assessed amyloid-β (Aβ) burden and neurodegeneration. METHODS Patients with mild dementia compatible with AD (n = 38) or amnestic mild cognitive impairment (aMCI; n = 43) and a cognitively unimpaired group (n = 27) underwent PET with Pittsburgh compound-B (PiB) assessing Aβ aggregation (A+) and [18F]FDG-PET assessing neurodegeneration ((N)+). Cognitive performance was assessed with verbal and visual episodic memory tests and the Mini-Mental State Examination. RESULTS The A+(N)+ subgroup (n = 32) showed decreased (p < 0.001) cognitive test scores compared to both A+(N)-(n = 18) and A-(N)-(n = 49) subjects, who presented highly similar mean cognitive scores. Despite its modest size (n = 9), the A-(N)+ subgroup showed lower (p < 0.043) verbal memory scores relative to A-(N)-subjects, and trend lower (p = 0.096) scores relative to A+(N)-subjects. Continuous Aβ measures (standard uptake value ratios of PiB uptake) were correlated most significantly with visual memory scores both in the overall sample and when analyses were restricted to dementia or (N)+ subjects, but not in non-dementia or (N)-groups. CONCLUSION These results demonstrate that significant Aβ-cognition relationships are highly salient at disease stages involving neurodegeneration. The fact that findings relating Aβ burden to memory performance were detected only at (N)+ stages, together with the similarity of test scores between A+(N)-and A-(N)-subjects, reinforce the view that Aβ-cognition relationships during early AD stages may remain undetectable unless substantially large samples are evaluated.
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Affiliation(s)
- Paula Squarzoni
- Laboratory of Psychiatric Neuroimaging (LIM 21), Departament of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Daniele de Paula Faria
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Mônica Sanches Yassuda
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Fábio Henrique de Gobbi Porto
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Artur Martins Coutinho
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Naomi Antunes da Costa
- Laboratory of Psychiatric Neuroimaging (LIM 21), Departament of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Ricardo Nitrini
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Orestes Vicente Forlenza
- Laboratory of Neuroscience (LIM 27), Departament of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Fabio Luiz de Souza Duran
- Laboratory of Psychiatric Neuroimaging (LIM 21), Departament of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Carlos Alberto Buchpiguel
- Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Geraldo F Busatto
- Laboratory of Psychiatric Neuroimaging (LIM 21), Departament of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil.,Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil
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Chanisa C, Monchaya N, Anchisa K, Chetsadaporn P, Attapon J. Analysis of amyloid and tau deposition in Alzheimer's disease using 11C-Pittsburgh compound B and 18F-THK 5351 positron emission tomography imaging. World J Nucl Med 2020; 20:61-72. [PMID: 33850491 PMCID: PMC8034795 DOI: 10.4103/wjnm.wjnm_50_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 04/29/2020] [Accepted: 05/16/2020] [Indexed: 01/30/2023] Open
Abstract
This study aims to determine the deposition of 11C-Pittsburgh compound B (11C-PiB) and 18F-THK 5351 using a normal database of the optimal cut-off-points for standardized uptake value ratios (SUVRs) in Alzheimer's disease (AD) patients. Sixteen AD patients and 24 cognitively normal individuals were enrolled in this study. The optimal cutoff points for the SUVR from the normal database were used for quantitative analysis. P-mod software with the Automated Anatomical Labeling merged atlas was employed to generate automatic volumes of interest to identify different brain regions, and the SUVRs of AD patients were compared with those of the age-matched normal controls. The correlation between PiB and THK5351 deposition at matching brain regions was identified. The mean regional 11C-PiB SUVRs of the AD patients were significantly higher than the healthy controls (P < 0.05). The 11C-PiB SUVR cut-offs were 1.46–1.81, with sensitivity ranging from 81.25% to 93.75% and specificity of 100%. The mean SUVRs of 18F-THK 5351 in various regions were also significantly higher in the AD patients than in the healthy controls (P < 0.05). The inferior temporal gyrus yielded an optimum SUVR cut-off-points of 1.5 with 80% sensitivity and 83.33% specificity. The correlation of PiB and THK5351 SUVR was reported at precuneus, parietal, and occipital brain areas, with spearman's rho of 0.67, 0.66, and 0.72, respectively. Our findings allow determination of the SUVRs of 11C-PiB and 18F-THK-5351 amyloid and tau positron emission tomography tracers for clinical use, according to the normal database of the optimal cut-off-points for SUVRs in AD patients.
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Affiliation(s)
- Chotipanich Chanisa
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Nivorn Monchaya
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Kunawudhi Anchisa
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
| | | | - Jantarato Attapon
- National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand
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163
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Wang X, Huang W, Su L, Xing Y, Jessen F, Sun Y, Shu N, Han Y. Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease. Mol Neurodegener 2020; 15:55. [PMID: 32962744 PMCID: PMC7507636 DOI: 10.1186/s13024-020-00395-3] [Citation(s) in RCA: 121] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/07/2020] [Indexed: 12/15/2022] Open
Abstract
Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.
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Affiliation(s)
- Xiaoqi Wang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge, UK.,Sino-Britain Centre for Cognition and Ageing Research, Southwest University, Chongqing, China
| | - Yue Xing
- Radiological Sciences, Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50937, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Yu Sun
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China. .,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China. .,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China. .,National Clinical Research Center for Geriatric Disorders, Beijing, China.
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164
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Jia F, Li Y, Li M, Cao F. Subjective Cognitive Decline, Cognitive Reserve Indicators, and the Incidence of Dementia. J Am Med Dir Assoc 2020; 22:1449-1455.e4. [PMID: 32967819 DOI: 10.1016/j.jamda.2020.08.005] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/04/2020] [Accepted: 08/08/2020] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Both cognitive reserve and subjective cognitive decline are closely related to the risk of dementia. We investigated whether cognitive reserve can modify the risk of dementia developing from subjective cognitive decline. DESIGN Longitudinal population-based study. SETTING AND PARTICIPANTS The prospective study analyzed data from 2099 participants aged 65 or over from the Cognitive Function and Ageing Study-Wales (CFAS-Wales). METHODS Dementia was ascertained through the comprehensive judgment symptoms of geriatric mental state automated geriatric examination for computer assisted taxonomy (GMS-AGECAT). Subjective cognitive decline was evaluated by 2 questions in the baseline interview. Cognitive reserve indicators were derived from 3 previously identified factors: early life education, mid-life occupational complexity, and late-life cognitive activities. We used logistic regression models to estimate dementia risk in relation to subjective cognitive decline and indicators of cognitive reserve. The interaction between subjective cognitive decline and cognitive reserve were evaluated by additive and multiplicative scales. RESULTS Baseline subjective cognitive decline and low cognitive reserve significantly increased the risk of dementia, after 2 years of follow-up. There was an additive interaction between subjective cognitive decline and cognitive reserve [the relative excess risk due to interaction = -0.63, 95% confidence interval (CI) = -0.89 to -0.36, P for additive interaction <0.001]. There was no multiplicative interaction between subjective cognitive decline and cognitive reserve indicator (P = .138). Statistically significant association between subjective cognitive decline and dementia was found only in the low-level and medium-level cognitive reserve group (OR = 3.78, 95% CI = 1.50-9.55 and OR = 3.64, 95% CI = 1.09-12.2, respectively), but not in the high-level groups. CONCLUSION AND IMPLICATIONS Cognitive reserve attenuated subjective cognitive decline associated risk of developing dementia. This finding suggests the need for greater emphasis on detecting prodromal dementia when older patients having lower cognitive reserve present with subjective cognitive decline.
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Affiliation(s)
- Feifei Jia
- Department of Nursing Psychology, Nursing School, Shandong University, Jinan, China
| | - Yanyan Li
- Department of Nursing Psychology, Nursing School, Shandong University, Jinan, China
| | - Min Li
- Department of Gynecology, Qilu Hospital of Shandong University, Jinan, China
| | - Fenglin Cao
- Department of Nursing Psychology, Nursing School, Shandong University, Jinan, China.
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165
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Toledo JB, Habes M, Sotiras A, Bjerke M, Fan Y, Weiner MW, Shaw LM, Davatzikos C, Trojanowski JQ. APOE Effect on Amyloid-β PET Spatial Distribution, Deposition Rate, and Cut-Points. J Alzheimers Dis 2020; 69:783-793. [PMID: 31127775 DOI: 10.3233/jad-181282] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
There are conflicting results regarding how APOE genotype, the strongest genetic risk factor for Alzheimer's disease (AD), influences spatial and longitudinal amyloid-β (Aβ) deposition and its impact on the selection of biomarker cut-points. In our study, we sought to determine the impact of APOE genotype on cross-sectional and longitudinal florbetapir positron emission tomography (PET) amyloid measures and its impact in classification of patients and interpretation of clinical cohort results. We included 1,019 and 1,072 Alzheimer's Disease Neuroimaging Initiative participants with cerebrospinal fluid Aβ1 - 42 and florbetapir PET values, respectively. 623 of these subjects had a second florbetapir PET scans two years after the baseline visit. We evaluated the effect of APOE genotype on Aβ distribution pattern, pathological biomarker cut-points, cross-sectional clinical associations with Aβ load, and longitudinal Aβ deposition rate measured using florbetapir PET scans. 1) APOEɛ4 genotype influences brain amyloid deposition pattern; 2) APOEɛ4 genotype does not modify Aβ biomarker cut-points estimated using unsupervised mixture modeling methods if white matter and brainstem references are used (but not when cerebellum is used as a reference); 3) findings of large differences in Aβ biomarker value differences based on APOE genotype are due to increased probability of having AD neuropathology and are most significant in mild cognitive impairment subjects; and 4) APOE genotype and age (but not gender) were associated with increased Aβ deposition rate. APOEɛ4 carrier status affects rate and location of brain Aβ deposition but does not affect choice of biomarker cut-points if adequate references are selected for florbetapir PET processing.
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Affiliation(s)
- Jon B Toledo
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, Houston Methodist Hospital, Houston, TX, USA
| | - Mohamad Habes
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Aristeidis Sotiras
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA.,Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Maria Bjerke
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Yong Fan
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael W Weiner
- Department of Radiology, Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco, San Francisco, CA, USA
| | - Leslie M Shaw
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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166
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Gao F, Shang S, Chen C, Dang L, Gao L, Wei S, Wang J, Huo K, Deng M, Wang J, Qu Q. Non-linear Relationship Between Plasma Amyloid-β 40 Level and Cognitive Decline in a Cognitively Normal Population. Front Aging Neurosci 2020; 12:557005. [PMID: 33061905 PMCID: PMC7516983 DOI: 10.3389/fnagi.2020.557005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 08/19/2020] [Indexed: 01/06/2023] Open
Abstract
Objectives Recent studies regarding the relationships between plasma amyloid-β (Aβ) levels and cognitive performance had inconsistent results. In this study, we aimed to characterize the relationship between cognitive decline and plasma Aβ levels in a large-sample cognitively normal population. Methods This population-based, prospective cohort study included 1,240 participants with normal cognition. The Mini-Mental State Examination (MMSE) was used to assess cognitive function at baseline and 2 years later. Restricted cubic splines, multivariate logistic regression, and multivariate linear regression models were used to evaluate the type of relationship between cognitive decline during the 2-year follow-up period and plasma Aβ levels (Aβ40, Aβ42, and Aβ42/40). Results Participants with moderate Aβ40 levels had the highest risk of cognitive decline during a 2-year follow-up relative to individuals with low Aβ40 [odds ratio (OR): 0.60, 95% confidence interval (CI): 0.45–0.81, p < 0.001] or high Aβ40 (OR: 0.65, 95% CI: 0.49–0.87, p = 0.004) levels. The association between Aβ40 and cognitive decline did not depend on sex, education level, or APOE ε4 status. There was an interaction found between age (≤ 65 and > 65 years) and Aβ40 (p for interaction = 0.021). In individuals older than 65 years, there was a positive linear relationship between plasma Aβ40 and cognitive decline (OR: 1.02, 95% CI: 1.00–1.04, p = 0.027). For participants ≤ 65 years old, the lower Aβ40 and higher Aβ40 groups had a lower risk of cognitive decline than the medium Aβ40 group (OR: 0.69, 95% CI: 0.50–0.94, p = 0.02; OR: 0.63, 95% CI: 0.45–0.86, p = 0.004). None of relationship between plasma Aβ42, Aβ42/40 and cognitive decline was found during a 2-year follow-up. Conclusion The relationship between plasma Aβ40 and cognitive decline was not linear, but an inverted-U shape in a cognitively normal population. The underlying mechanism requires further investigation.
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Affiliation(s)
- Fan Gao
- Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Suhang Shang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chen Chen
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Liangjun Dang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ling Gao
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shan Wei
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jin Wang
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kang Huo
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Meiying Deng
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jingyi Wang
- Department of Neurology, Huxian Hospital of Traditional Chinese Medicine, Xi'an, China
| | - Qiumin Qu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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167
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Li G, Qin Z, Radosevich AT. P(III)/P(V)-Catalyzed Methylamination of Arylboronic Acids and Esters: Reductive C-N Coupling with Nitromethane as a Methylamine Surrogate. J Am Chem Soc 2020; 142:16205-16210. [PMID: 32886500 DOI: 10.1021/jacs.0c08035] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The direct reductive N-arylation of nitromethane by organophosphorus-catalyzed reductive C-N coupling with arylboronic acid derivatives is reported. This method operates by the action of a small ring organophosphorus-based catalyst (1,2,2,3,4,4-hexamethylphosphetane P-oxide) together with a mild terminal reductant hydrosilane to drive the selective installation of the methylamino group to (hetero)aromatic boronic acids and esters. This method also provides for a unified synthetic approach to isotopically labeled N-methylanilines from various stable isotopologues of nitromethane (i.e., CD3NO2, CH315NO2, and 13CH3NO2), revealing this easy-to-handle compound as a versatile precursor for the direct installation of the methylamino group.
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Affiliation(s)
- Gen Li
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Ziyang Qin
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Alexander T Radosevich
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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168
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Hu H, Tan L, Bi YL, Xu W, Tan L, Shen XN, Hou XH, Ma YH, Dong Q, Yu JT. Association of serum Apolipoprotein B with cerebrospinal fluid biomarkers of Alzheimer's pathology. Ann Clin Transl Neurol 2020; 7:1766-1778. [PMID: 32910550 PMCID: PMC7545610 DOI: 10.1002/acn3.51153] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 06/23/2020] [Accepted: 07/16/2020] [Indexed: 12/29/2022] Open
Abstract
Objective To examine whether apolipoprotein B (ApoB), apolipoprotein A‐1 (ApoA1), or their ratio (ApoB/A1) were associated with early changes in cerebrospinal fluid (CSF) biomarkers of Alzheimer’s disease (AD) pathology in elderly adults with subjective cognitive decline (SCD). Methods This study included 507 objective cognitive normal participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database including 288 cognitive normal participants (CN) and 219 SCD. Multiple linear regression models were used to examine the associations of apolipoproteins with CSF AD biomarkers. Results Compared with control group, SCD participants with significant AD biological characteristics had lower ApoB levels (P = 0.0461). In total participants, lower level of serum ApoB was associated with decreases in CSF Aβ42 (P = 0.0015) and Aβ42/40 (P = 0.0081) as well as increases in CSF p‐tau/Aβ42 (P < 0.0001) and t‐tau/Aβ42 (P = 0.0013), independent of APOEɛ4 status. In further subgroup analysis, these associations were more significant in SCD participants (ApoB × Diagnose: P < 0.05). In addition, lower levels of ApoB were also found associated with increases in p‐tau in the SCD subgroup (P = 0.0263). Furthermore, these protective associations were more significant in the overweight participants (ApoB × weight: P < 0.05). Results showed no association between ApoA1 and CSF biomarkers. Interpretation This study is the first to find protective associations of serum ApoB with CSF AD core biomarkers, especially in SCD individuals. It indicated that ApoB may be a potential biomarker for preclinical AD and may play different roles in different stages of AD.
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Affiliation(s)
- Hao Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan-Lin Bi
- Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lin Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiao-He Hou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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169
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Rynearson KD, Buckle RN, Herr RJ, Mayhew NJ, Chen X, Paquette WD, Sakwa SA, Yang J, Barnes KD, Nguyen P, Mobley WC, Johnson G, Lin JH, Tanzi RE, Wagner SL. Design and synthesis of novel methoxypyridine-derived gamma-secretase modulators. Bioorg Med Chem 2020; 28:115734. [PMID: 33007551 DOI: 10.1016/j.bmc.2020.115734] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/18/2020] [Accepted: 08/21/2020] [Indexed: 11/19/2022]
Abstract
The evolution of gamma-secretase modulators (GSMs) through the introduction of novel heterocycles with the goal of aligning activity for reducing the levels of Aβ42 and properties consistent with a drug-like molecule are described. The insertion of a methoxypyridine motif within the tetracyclic scaffold provided compounds with improved activity for arresting Aβ42 production as well as improved properties, including solubility. In vivo pharmacokinetic analysis demonstrated that several compounds within the novel series were capable of crossing the BBB and accessing the therapeutic target. Treatment with methoxypyridine-derived compound 64 reduced Aβ42 levels in the plasma of J20 mice, in addition to reducing Aβ42 levels in the plasma and brain of Tg2576 mice.
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Affiliation(s)
- Kevin D Rynearson
- Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093-0624, United States.
| | - Ronald N Buckle
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - R Jason Herr
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Nicholas J Mayhew
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Xinchao Chen
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - William D Paquette
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Samuel A Sakwa
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Jinhai Yang
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Keith D Barnes
- Department of Medicinal Chemistry, AMRI, East Campus, 3 University Place, Rensselaer, NY 12144, United States
| | - Phuong Nguyen
- Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093-0624, United States
| | - William C Mobley
- Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093-0624, United States
| | - Graham Johnson
- NuPharmAdvise, 3 Lakeside Drive, Sanbornton, NH 03269, United States
| | - Juinn H Lin
- Biopharm Consulting Partners, 2 Willet Drive, Ambler, PA 19002, United States
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, United States
| | - Steven L Wagner
- Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093-0624, United States; Veterans Administrative San Diego Healthcare System, La Jolla, CA 92161, United States.
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170
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Yasuno F, Minami H, Hattori H. Interaction effect of Alzheimer's disease pathology and education, occupation, and socioeconomic status as a proxy for cognitive reserve on cognitive performance: in vivo positron emission tomography study. Psychogeriatrics 2020; 20:585-593. [PMID: 32285577 DOI: 10.1111/psyg.12552] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/05/2020] [Accepted: 03/16/2020] [Indexed: 11/29/2022]
Abstract
AIM Educational attainment, occupation, and socioeconomic status have been regarded as major factors influencing cognitive reserve (CR). This study aimed to investigate the interaction effect of amyloid-β/tau burden and education/occupation/socioeconomic status as a proxy for CR on cognitive performance. METHODS We analyzed the datasets of the Alzheimer's Disease Neuroimaging Initiative. We included clinically normal subjects and patients with mild cognitive impairment or Alzheimer's disease who had undergone a florbetapir scan within 1 year of a flortaucipir (AV-1451) scan (n = 127). Partial correlation analysis between the standardized uptake value ratio of florbetapir/AV-1451 and the proxy for CR was performed with the 13-item Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) score as a covariate. Stepwise multiple linear regression analysis was performed to determine the predictors of ADAS-cog performance based on the interaction between the imaging biomarkers and the proxy for CR. RESULTS We found a significant positive partial correlation between educational level and tau pathology in Braak stage 1/2 areas, and we observed significantly higher tau accumulation among participants with higher education when ADAS-cog score was used as a covariate. The interaction between tau and education was a good predictor of cognitive function, with higher tau accumulation showing a greater association with higher ADAS-cog score among participants with less education than among those with more education. CONCLUSION Our findings indicate the protective effect of education against cognitive dysfunction in early-stage Alzheimer's disease pathology and suggest that education may exert a beneficial effect by reducing the adverse cognitive consequences of tau aggregation.
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Affiliation(s)
- Fumihiko Yasuno
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Hiroyuki Minami
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Hideyuki Hattori
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, Japan
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171
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Rowley PA, Samsonov AA, Betthauser TJ, Pirasteh A, Johnson SC, Eisenmenger LB. Amyloid and Tau PET Imaging of Alzheimer Disease and Other Neurodegenerative Conditions. Semin Ultrasound CT MR 2020; 41:572-583. [PMID: 33308496 DOI: 10.1053/j.sult.2020.08.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Although diagnosing the syndrome of dementia is largely a clinical endeavor, neuroimaging plays an increasingly important role in accurately determining the underlying etiology, which extends beyond its traditional role in excluding other causes of altered cognition. New neuroimaging methods not only facilitate the diagnosis of the most common neurodegenerative conditions (particularly Alzheimer Disease [AD]) after symptom onset, but also show diagnostic promise even in the very early or presymptomatic phases of disease. Positron emission tomography (PET) is increasingly recognized as a key clinical tool for differentiating normal age-related changes in brain metabolism (using 18F-fluorodeoxyglucose [FDG]) from those seen in the earliest stages of specific forms of dementia. However, FDG PET only demonstrates nonspecific changes in altered parenchymal glucose uptake and not the specific etiologic proteinopathy causing the abnormal glucose uptake. A growing class of radiotracers targeting specific protein aggregates for amyloid-β (Aβ) and tau are changing the way AD is diagnosed, as these radiotracers directly label the underlying disease pathology. As these pathology-specific radiotracers are currently making their way to the clinic, it is important for the clinical neuroradiologist to understand the underlying patterns of Aβ and tau deposition in the context of AD (across its clinical continuum) and in other causes of dementia, as well as understand the implications of current research.
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Affiliation(s)
- Paul A Rowley
- Department of Radiology, University of Wisconsin, Madison, WI
| | | | | | - Ali Pirasteh
- Department of Radiology, University of Wisconsin, Madison, WI
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172
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The Effects of Longitudinal White Matter Hyperintensity Change on Cognitive Decline and Cortical Thinning over Three Years. J Clin Med 2020; 9:jcm9082663. [PMID: 32824599 PMCID: PMC7465642 DOI: 10.3390/jcm9082663] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/14/2020] [Accepted: 08/15/2020] [Indexed: 01/18/2023] Open
Abstract
White matter hyperintensity (WMH) has been recognised as a surrogate marker of small vessel disease and is associated with cognitive impairment. We investigated the dynamic change in WMH in patients with severe WMH at baseline, and the effects of longitudinal change of WMH volume on cognitive decline and cortical thinning. Eighty-seven patients with subcortical vascular mild cognitive impairment were prospectively recruited from a single referral centre. All of the patients were followed up with annual neuropsychological tests and 3T brain magnetic resonance imaging. The WMH volume was quantified using an automated method and the cortical thickness was measured using surface-based methods. Participants were classified into WMH progression and WMH regression groups based on the delta WMH volume between the baseline and the last follow-up. To investigate the effects of longitudinal change in WMH volume on cognitive decline and cortical thinning, a linear mixed effects model was used. Seventy patients showed WMH progression and 17 showed WMH regression over a three-year period. The WMH progression group showed more rapid cortical thinning in widespread regions compared with the WMH regression group. However, the rate of cognitive decline in language, visuospatial function, memory and executive function, and general cognitive function was not different between the two groups. The results of this study indicated that WMH volume changes are dynamic and WMH progression is associated with more rapid cortical thinning.
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173
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Spencer BE, Jennings RG, Brewer JB. Combined Biomarker Prognosis of Mild Cognitive Impairment: An 11-Year Follow-Up Study in the Alzheimer's Disease Neuroimaging Initiative. J Alzheimers Dis 2020; 68:1549-1559. [PMID: 30958366 DOI: 10.3233/jad-181243] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND Biomarkers may soon be used to predict decline in older individuals. Extended follow-up studies are needed to determine the stability of such biomarker-based predictions. OBJECTIVE To examine the long-term performance of baseline cognitive, neuroimaging, and cerebrospinal fluid (CSF) biomarker-assisted prognosis in patients with mild cognitive impairment. METHODS Established, biomarker-defined, cohorts of subjects with mild cognitive impairment were examined for progression to dementia. Subjects with a baseline volumetric MRI, lumbar puncture, and Rey Auditory Verbal Learning Test were included. Dementia-free survival time in each biomarker-defined risk group was determined with Kaplan-Meier survival curves. The influence of each risk factor or combination of factors on dementia-free survival was examined with Cox proportional hazard analyses. RESULTS 185 subjects were followed longitudinally for a mean (SD) 4.3 (2.8) years. 59% of participants converted within the follow-up period and the median dementia-free survival time was 2.8 years. Each individual risk factor predicted conversion to dementia (HR 1.9-3.7). The joint presence of any two risk factors increased risk for conversion (HR 7.1-11.0), with the presence of medial temporal atrophy and memory impairment showing the greatest risk for decline. Concordant atrophy, memory impairment, and abnormal CSF amyloid and tau was associated with the highest risk for conversion (HR 15.1). The presence of medial temporal atrophy was associated with the shortest dementia-free survival time, both alone and in combination with memory impairment, abnormal CSF amyloid and tau, or both. CONCLUSION These results suggest that baseline biomarker-assisted predictions of decline to dementia are stable over the long term, and that combinations of complementary biomarkers can improve the accuracy of these predictions.
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Affiliation(s)
- Barbara E Spencer
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Robin G Jennings
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - James B Brewer
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.,Department of Radiology, University of California, San Diego, La Jolla, CA, USA
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174
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The preclinical amyloid sensitive composite to determine subtle cognitive differences in preclinical Alzheimer's disease. Sci Rep 2020; 10:13583. [PMID: 32788669 PMCID: PMC7423599 DOI: 10.1038/s41598-020-70386-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 07/22/2020] [Indexed: 12/13/2022] Open
Abstract
Recently, the focus of Alzheimer's disease (AD) research has shifted from the clinical stage to the preclinical stage. We, therefore, aimed to develop a cognitive composite score that can detect the subtle cognitive differences between the amyloid positive (Aβ+) and negative (Aβ-) status in cognitively normal (CN) participants. A total of 423 CN participants with Aβ positron emission tomography images were recruited. The multiple-indicators multiple-causes model found the latent mean difference between the Aβ+ and Aβ- groups in the domains of verbal memory, visual memory, and executive functions. The multivariate analysis of covariance (MANCOVA) showed that the Aβ+ group performed worse in tests related to the verbal and visual delayed recall, semantic verbal fluency, and inhibition of cognitive inference within the three cognitive domains. The Preclinical Amyloid Sensitive Composite (PASC) model we developed using the result of MANCOVA and the MMSE presented a good fit with the data. The accuracy of the PASC score when applied with age, sex, education, and APOE ε4 for distinguishing between Aβ+ and Aβ- was adequate (AUC = 0.764; 95% CI = 0.667-0.860) in the external validation set (N = 179). We conclude that the PASC can eventually contribute to facilitating more prevention trials in preclinical AD.
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175
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Zhao J, Liu X, Xia W, Zhang Y, Wang C. Targeting Amyloidogenic Processing of APP in Alzheimer's Disease. Front Mol Neurosci 2020; 13:137. [PMID: 32848600 PMCID: PMC7418514 DOI: 10.3389/fnmol.2020.00137] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 07/08/2020] [Indexed: 12/11/2022] Open
Abstract
Alzheimer's disease (AD) is the most common type of senile dementia, characterized by neurofibrillary tangle and amyloid plaque in brain pathology. Major efforts in AD drug were devoted to the interference with the production and accumulation of amyloid-β peptide (Aβ), which plays a causal role in the pathogenesis of AD. Aβ is generated from amyloid precursor protein (APP), by consecutive cleavage by β-secretase and γ-secretase. Therefore, β-secretase and γ-secretase inhibition have been the focus for AD drug discovery efforts for amyloid reduction. Here, we review β-secretase inhibitors and γ-secretase inhibitors/modulators, and their efficacies in clinical trials. In addition, we discussed the novel concept of specifically targeting the γ-secretase substrate APP. Targeting amyloidogenic processing of APP is still a fundamentally sound strategy to develop disease-modifying AD therapies and recent advance in γ-secretase/APP complex structure provides new opportunities in designing selective inhibitors/modulators for AD.
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Affiliation(s)
- Jing Zhao
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Xinyue Liu
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Weiming Xia
- Geriatric Research Education Clinical Center, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States
- Department of Pharmacology and Experimental Therapeutics, School of Medicine, Boston University, Boston, MA, United States
| | - Yingkai Zhang
- Department of Chemistry, New York University, New York, NY, United States
| | - Chunyu Wang
- Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, United States
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States
- Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, United States
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176
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Sprung J, Abcejo AS(A, Knopman DS, Petersen RC, Mielke MM, Hanson AC, Schroeder DR, Schulte PJ, Martin DP, Weingarten TN, Pasternak JJ, Warner DO. Anesthesia With and Without Nitrous Oxide and Long-term Cognitive Trajectories in Older Adults. Anesth Analg 2020; 131:594-604. [PMID: 31651458 PMCID: PMC7165021 DOI: 10.1213/ane.0000000000004490] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
BACKGROUND We evaluated the hypothesis that the rate of postoperative decline in global cognition is greater in older adults exposed to general anesthesia with nitrous oxide (N2O) compared to general anesthesia without N2O. METHODS Longitudinal measures of cognitive function were analyzed in nondemented adults, 70-91 years of age, enrolled in the Mayo Clinic Study of Aging. Linear mixed-effects models with time-varying covariates assessed the relationship between exposure to surgery with general anesthesia (surgery/GA) with or without N2O and the rate of long-term cognitive changes. Global cognition and domain-specific cognitive outcomes were defined using z scores, which measure how far an observation is, in standard deviations, from the unimpaired population mean. RESULTS The analysis included 1819 participants: 280 exposed to GA without N2O following enrollment and before censoring during follow-up (median [interquartile range {IQR}] follow-up of 5.4 [3.9-7.9] years); 256 exposed to GA with N2O (follow-up 5.6 [4.0-7.9] years); and 1283 not exposed to surgery/GA (follow-up 4.1 [2.5-6.4] years). The slope of the global cognitive z score was significantly more negative following exposure to surgery/GA after enrollment (change in slope of -0.062 [95% confidence interval {CI}, -0.085 to -0.039] for GA without N2O, and -0.058 [95% CI, -0.080 to -0.035] for GA with N2O, both P < .001). The change in slope following exposure to surgery/GA did not differ between those exposed to anesthesia without versus with N2O (estimated difference -0.004 [95% CI, -0.035 to 0.026], P = .783). CONCLUSIONS Exposure to surgery/GA is associated with a small, but statistically significant decline in cognitive z scores. Cognitive decline did not differ between anesthetics with and without N2O. This finding provides evidence that the use of N2O in older adults does not need to be avoided because of concerns related to decline in cognition.
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Affiliation(s)
- Juraj Sprung
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Arnoley S. (Arney) Abcejo
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - David S. Knopman
- Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Michelle M. Mielke
- Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Andrew C. Hanson
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Darrell R. Schroeder
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Phillip J. Schulte
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - David P. Martin
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Toby N. Weingarten
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Jeffrey J. Pasternak
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - David O. Warner
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
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177
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Rittman T. Neurological update: neuroimaging in dementia. J Neurol 2020; 267:3429-3435. [PMID: 32638104 PMCID: PMC7578138 DOI: 10.1007/s00415-020-10040-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 06/26/2020] [Accepted: 06/30/2020] [Indexed: 12/18/2022]
Abstract
Neuroimaging for dementia has made remarkable progress in recent years, shedding light on diagnostic subtypes of dementia, predicting prognosis and monitoring pathology. This review covers some updates in the understanding of dementia using structural imaging, positron emission tomography (PET), structural and functional connectivity, and using big data and artificial intelligence. Progress with neuroimaging methods allows neuropathology to be examined in vivo, providing a suite of biomarkers for understanding neurodegeneration and for application in clinical trials. In addition, we highlight quantitative susceptibility imaging as an exciting new technique that may prove to be a sensitive biomarker for a range of neurodegenerative diseases. There are challenges in translating novel imaging techniques to clinical practice, particularly in developing standard methodologies and overcoming regulatory issues. It is likely that clinicians will need to lead the way if these obstacles are to be overcome. Continued efforts applying neuroimaging to understand mechanisms of neurodegeneration and translating them to clinical practice will complete a revolution in neuroimaging.
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Affiliation(s)
- Timothy Rittman
- Department of Neurosciences, University of Cambridge, Cambridge, UK.
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178
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Yang BH, Chen JC, Chou WH, Huang WS, Fuh JL, Liu R, Wu CH. Classification of Alzheimer’s Disease from 18F-FDG and 11C-PiB PET Imaging Biomarkers Using Support Vector Machine. J Med Biol Eng 2020. [DOI: 10.1007/s40846-020-00548-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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179
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Nadkarni NK, Tudorascu D, Campbell E, Snitz BE, Cohen AD, Halligan E, Mathis CA, Aizenstein HJ, Klunk WE. Association Between Amyloid-β, Small-vessel Disease, and Neurodegeneration Biomarker Positivity, and Progression to Mild Cognitive Impairment in Cognitively Normal Individuals. J Gerontol A Biol Sci Med Sci 2020; 74:1753-1760. [PMID: 30957843 DOI: 10.1093/gerona/glz088] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND We estimated the prevalence and incidence of amyloid-β deposition (A), small-vessel disease (V), and neurodegeneration (N) biomarker positivity in community-dwelling cognitively normal individuals (CN). We determined the longitudinal association between the respective biomarker indices with progression to all-cause mild cognitive impairment (MCI) and its amnestic and nonamnestic subtypes. METHODS CN participants, recruited by advertising, underwent brain [C-11]Pittsburgh Compound-B (PiB)-positron emission tomography (PET), magnetic resonance imaging, and [F-18]fluoro-2-deoxy-glucose (FDG)-PET, and were designated as having high or low amyloid-β (A+/A-), greater or lower white matter hyperintensities burden (V+/V-) and diminished or normal cortical glucose metabolism (N+/N-). MCI was adjudicated using clinical assessments. We examined the association between A, V, and N biomarker positivity at study baseline and endpoint, with progression to MCI using linear regression, Cox proportional hazards and Kaplan-Meier analyses adjusted for age and APOE-ε4 carrier status. RESULTS In 98 CN individuals (average age 74 years, 65% female), A+, V+, and N+ prevalence was 26%, 33%, and 8%, respectively. At study endpoint (median: 5.5 years), an A+, but not a V+ or N+ scan, was associated with higher odds of all-cause MCI (Chi-square = 3.9, p = .048, odds ratio, 95% confidence interval = 2.6 [1.01-6.8]). Baseline A+, V+, or N+ were not associated with all-cause MCI, however, baseline A+ (p = .018) and A+N+ (p = .049), and endpoint A+N+ (p = .025) were associated with time to progression to amnestic, not nonamnestic, MCI. CONCLUSION Longitudinal assessments clarify the association between amyloid-β and progression to all-cause MCI in CN individuals. The association between biomarker positivity indices of amyloid-β and neurodegeneration, and amnestic MCI reflects the underlying pathology involved in the progression to prodromal Alzheimer's disease.
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Affiliation(s)
- Neelesh K Nadkarni
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Dana Tudorascu
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Biostatistics, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Annie D Cohen
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | - Edye Halligan
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | | | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
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180
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Hadjichrysanthou C, Evans S, Bajaj S, Siakallis LC, McRae-McKee K, de Wolf F, Anderson RM. The dynamics of biomarkers across the clinical spectrum of Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:74. [PMID: 32534594 PMCID: PMC7293779 DOI: 10.1186/s13195-020-00636-z] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 05/20/2020] [Indexed: 12/20/2022]
Abstract
Background Quantifying changes in the levels of biological and cognitive markers prior to the clinical presentation of Alzheimer’s disease (AD) will provide a template for understanding the underlying aetiology of the clinical syndrome and, concomitantly, for improving early diagnosis, clinical trial recruitment and treatment assessment. This study aims to characterise continuous changes of such markers and determine their rate of change and temporal order throughout the AD continuum. Methods The methodology is founded on the development of stochastic models to estimate the expected time to reach different clinical disease states, for different risk groups, and synchronise short-term individual biomarker data onto a disease progression timeline. Twenty-seven markers are considered, including a range of cognitive scores, cerebrospinal (CSF) and plasma fluid proteins, and brain structural and molecular imaging measures. Data from 2014 participants in the Alzheimer’s Disease Neuroimaging Initiative database is utilised. Results The model suggests that detectable memory dysfunction could occur up to three decades prior to the onset of dementia due to AD (ADem). This is closely followed by changes in amyloid-β CSF levels and the first cognitive decline, as assessed by sensitive measures. Hippocampal atrophy could be observed as early as the initial amyloid-β accumulation. Brain hypometabolism starts later, about 14 years before onset, along with changes in the levels of total and phosphorylated tau proteins. Loss of functional abilities occurs rapidly around ADem onset. Neurofilament light is the only protein with notable early changes in plasma levels. The rate of change varies, with CSF, memory, amyloid PET and brain structural measures exhibiting the highest rate before the onset of ADem, followed by a decline. The probability of progressing to a more severe clinical state increases almost exponentially with age. In accordance with previous studies, the presence of apolipoprotein E4 alleles and amyloid-β accumulation can be associated with an increased risk of developing the disease, but their influence depends on age and clinical state. Conclusions Despite the limited longitudinal data at the individual level and the high variability observed in such data, the study elucidates the link between the long asynchronous pathophysiological processes and the preclinical and clinical stages of AD.
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Affiliation(s)
| | - Stephanie Evans
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.,Modelling and Economics Unit, National Infection Service, Public Health England, London, UK
| | - Sumali Bajaj
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Loizos C Siakallis
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, UK
| | - Kevin McRae-McKee
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Frank de Wolf
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Roy M Anderson
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
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181
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Burnham SC, Laws SM, Budgeon CA, Doré V, Porter T, Bourgeat P, Buckley RF, Murray K, Ellis KA, Turlach BA, Salvado O, Ames D, Martins RN, Rentz D, Masters CL, Rowe CC, Villemagne VL. Impact of APOE-ε4 carriage on the onset and rates of neocortical Aβ-amyloid deposition. Neurobiol Aging 2020; 95:46-55. [PMID: 32750666 DOI: 10.1016/j.neurobiolaging.2020.06.001] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 05/11/2020] [Accepted: 06/01/2020] [Indexed: 12/11/2022]
Abstract
Neocortical Aβ-amyloid deposition, one of the hallmark pathologic features of Alzheimer's disease (AD), begins decades prior to the presence of clinical symptoms. As clinical trials move to secondary and even primary prevention, understanding the rates of neocortical Aβ-amyloid deposition and the age at which Aβ-amyloid deposition becomes abnormal is crucial for optimizing the timing of these trials. As APOE-ε4 carriage is thought to modulate the age of clinical onset, it is also important to understand the impact of APOE-ε4 carriage on the age at which the neocortical Aβ-amyloid deposition becomes abnormal. Here, we show that, for 455 participants with over 3 years of follow-up, abnormal levels of neocortical Aβ-amyloid were reached on average at age 72 (66.5-77.1). The APOE-ε4 carriers reached abnormal levels earlier at age 63 (59.6-70.3); however, noncarriers reached the threshold later at age 78 (76.1-84.4). No differences in the rates of deposition were observed between APOE-ε4 carriers and noncarriers after abnormal Aβ-amyloid levels had been reached. These results suggest that primary and secondary prevention trials, looking to recruit at the earliest stages of disease, should target APOE-ε4 carriers between the ages of 60 and 66 and noncarriers between the ages of 76 and 84.
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Affiliation(s)
- Samantha C Burnham
- eHealth, CSIRO Health and Biosecurity, Parkville, Victoria, Australia; Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.
| | - Simon M Laws
- Collaborative Genomics Group, Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia; School of Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia; Cooperative Research Centre for Mental Health, http://www.mentalhealthcrc.com, Perth, Western Australia, Australia
| | - Charley A Budgeon
- Centre for Applied Statistics, University of Western Australia, Crawley, Western Australia, Australia; eHealth, CSIRO Health and Biosecurity, Floreat, Western Australia, Australia
| | - Vincent Doré
- eHealth, CSIRO Health and Biosecurity, Herston, Queensland, Australia; Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Tenielle Porter
- Collaborative Genomics Group, Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia; Cooperative Research Centre for Mental Health, http://www.mentalhealthcrc.com, Perth, Western Australia, Australia
| | - Pierrick Bourgeat
- eHealth, CSIRO Health and Biosecurity, Herston, Queensland, Australia
| | - Rachel F Buckley
- Florey Institute, University of Melbourne, Parkville, Victoria, Australia; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Kevin Murray
- School of Population and Global Health, University of Western Australia, Crawley, Western Australia, Australia
| | - Kathryn A Ellis
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, University of Melbourne, Parkville, Victoria, Australia
| | - Berwin A Turlach
- Centre for Applied Statistics, University of Western Australia, Crawley, Western Australia, Australia
| | - Olivier Salvado
- eHealth, CSIRO Health and Biosecurity, Herston, Queensland, Australia; Florey Institute, University of Melbourne, Parkville, Victoria, Australia
| | - David Ames
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, Victoria, Australia; National Ageing Research Institute, Parkville, Victoria, Australia
| | - Ralph N Martins
- Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Dorene Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Colin L Masters
- Florey Institute, University of Melbourne, Parkville, Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia
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182
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Plasma transferrin and hemopexin are associated with altered Aβ uptake and cognitive decline in Alzheimer's disease pathology. ALZHEIMERS RESEARCH & THERAPY 2020; 12:72. [PMID: 32517787 PMCID: PMC7285604 DOI: 10.1186/s13195-020-00634-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 05/18/2020] [Indexed: 02/06/2023]
Abstract
Background Heme and iron homeostasis is perturbed in Alzheimer’s disease (AD); therefore, the aim of the study was to examine the levels and association of heme with iron-binding plasma proteins in cognitively normal (CN), mild cognitive impairment (MCI), and AD individuals from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) and Kerr Anglican Retirement Village Initiative in Ageing Health (KARVIAH) cohorts. Methods Non-targeted proteomic analysis by high-resolution mass spectrometry was performed to quantify relative protein abundances in plasma samples from 144 CN individuals from the AIBL and 94 CN from KARVIAH cohorts and 21 MCI and 25 AD from AIBL cohort. ANCOVA models were utilized to assess the differences in plasma proteins implicated in heme/iron metabolism, while multiple regression modeling (and partial correlation) was performed to examine the association between heme and iron proteins, structural neuroimaging, and cognitive measures. Results Of the plasma proteins implicated in iron and heme metabolism, hemoglobin subunit β (p = 0.001) was significantly increased in AD compared to CN individuals. Multiple regression modeling adjusted for age, sex, APOEε4 genotype, and disease status in the AIBL cohort revealed lower levels of transferrin but higher levels of hemopexin associated with augmented brain amyloid deposition. Meanwhile, transferrin was positively associated with hippocampal volume and MMSE performance, and hemopexin was negatively associated with CDR scores. Partial correlation analysis revealed lack of significant associations between heme/iron proteins in the CN individuals progressing to cognitive impairment. Conclusions In conclusion, heme and iron dyshomeostasis appears to be a feature of AD. The causal relationship between heme/iron metabolism and AD warrants further investigation.
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183
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Burrell JR, Foxe D, Leyton C, Piguet O, Hodges JR. What to make of equivocal amyloid imaging results. Neurocase 2020; 26:137-146. [PMID: 32412323 DOI: 10.1080/13554794.2020.1764056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Six patients with equivocal amyloid-PET results are discussed. METHODS Patients underwent clinical/neuropsychological assessment, MRI, and amyloid-PET. Equivocal amyloid-PET was defined as cortical ligand binding with SUVR < 1.40. Follow-up for up to 5 years is presented. RESULTS 6 patients (4 males, 2 females, mean age 71.8 +/- 2.5 years) with equivocal amyloid-PET were included from 136 patients who underwent amyloid-PET (4.4% of cases). Patients had variable language, behavioral, and cognitive deficits. Progression varied from no deterioration to residential care within 3 years. DISCUSSION Equivocal amyloid-PET should be interpreted cautiously. Improved biomarkers of AD and other neurodegenerative diseases are needed.
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Affiliation(s)
- James R Burrell
- Neurosciences, Concord General Hospital , Sydney, Australia.,Brain and Mind Centre, The University of Sydney , Sydney, Australia.,Concord Clinical School, The University of Sydney , Sydney, Australia
| | - David Foxe
- Brain and Mind Centre, The University of Sydney , Sydney, Australia.,School of Psychology, The University of Sydney , Sydney, Australia.,ARC Centre of Excellence in Cognition and Its Disorders , Sydney, Australia
| | - Cristian Leyton
- Brain and Mind Centre, The University of Sydney , Sydney, Australia.,ARC Centre of Excellence in Cognition and Its Disorders , Sydney, Australia.,Faculty of Health Sciences, The University of Sydney , Sydney, Australia
| | - Olivier Piguet
- Brain and Mind Centre, The University of Sydney , Sydney, Australia.,School of Psychology, The University of Sydney , Sydney, Australia.,ARC Centre of Excellence in Cognition and Its Disorders , Sydney, Australia
| | - John R Hodges
- Brain and Mind Centre, The University of Sydney , Sydney, Australia.,ARC Centre of Excellence in Cognition and Its Disorders , Sydney, Australia
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184
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Decreased cerebrospinal fluid neuronal pentraxin receptor is associated with PET-Aβ load and cerebrospinal fluid Aβ in a pilot study of Alzheimer's disease. Neurosci Lett 2020; 731:135078. [PMID: 32450185 DOI: 10.1016/j.neulet.2020.135078] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/29/2020] [Accepted: 05/20/2020] [Indexed: 12/12/2022]
Abstract
Multifactorial pathological processes of Alzheimer's disease (AD) begin decades prior to clinical onset. Early identification of patients at risk of developing AD using biomarkers reflecting various aspects of pathogenesis is necessary for prevention and early intervention. Cortical β-amyloid (Aβ) burden assessed by positron emission tomography (PET) or cerebrospinal fluid (CSF) levels of Aβ42 are validated biomarkers for early identification. Recently, alterations in levels of neuronal proteins, neuronal pentraxin receptor (NPTXR) and neurofilament light (NfL), in the CSF have emerged as promising AD biomarkers. However, their association with Aβ deposition is not well understood. In this pilot study, we evaluate whether CSF NfL and NPTXR are associated with PET-Aβ imaging and core CSF biomarkers (Aβ42, T-tau, and P-tau). CSF samples were collected from a sub-cohort of participants from the Australian Imaging Biomarkers and Lifestyle study of aging (AIBL) and categorized as either PET-Aβ positive (n = 15) or negative (n = 15). NPTXR was significantly lower in PET-Aβ positive than negative individuals (p = 0.04), and correlated with Aβ42 (rho = 0.69, p < 0.0001), T-tau (rho = 0.45, p = 0.01), and P-tau (rho = 0.51, p = 0.004). However, CSF NfL was not significantly different between PET-Aβ positive and negative individuals and did not correlate with any of the core CSF biomarkers. Similar associations of NPTXR and the core CSF biomarkers persisted in the cognitively normal individuals. Together, NPTXR concentration in CSF may be more sensitive NfL to identify AD risk during the preclinical stage, warranting further investigation into its contribution to AD pathogenesis.
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185
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Dang C, Harrington KD, Lim YY, Ames D, Hassenstab J, Laws SM, Yassi N, Hickey M, Rainey-Smith SR, Robertson J, Rowe CC, Sohrabi HR, Salvado O, Weinborn M, Villemagne VL, Masters CL, Maruff P. Superior Memory Reduces 8-year Risk of Mild Cognitive Impairment and Dementia But Not Amyloid β-Associated Cognitive Decline in Older Adults. Arch Clin Neuropsychol 2020; 34:585-598. [PMID: 30272115 DOI: 10.1093/arclin/acy078] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 08/20/2018] [Accepted: 09/11/2018] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE To prospectively examine 8-year risk of clinical disease progression to mild cognitive impairment (MCI)/dementia in older adults ≥60 with superior episodic memory (SuperAgers) compared to those cognitively normal for their age (CNFA). Additionally, to determine the extent to which SuperAgers were resilient to the negative effects of elevated amyloid-beta (Aβ+) on cognition. METHOD Participants were classified as SuperAgers based on episodic memory performance consistent with younger adults aged 30-44 and no impairment on non-memory tests (n = 179), and were matched with CNFA on age, sex, education, and follow-up time (n = 179). Subdistribution hazard models examined risk of clinical progression to MCI/dementia. Linear mixed models assessed the effect of Aβ on cognition over time. RESULTS Prevalence of Aβ+ and APOE ε4 was equivalent between SuperAgers and CNFA. SuperAgers had 69%-73% reduced risk of clinical progression to MCI/dementia compared to CNFA (HR: 0.27-0.31, 95% CI: 0.11-0.73, p < .001). Aβ+ was associated with cognitive decline in verbal memory and executive function, regardless of SuperAger/CNFA classification. In the absence of Aβ+, equivalent age-related changes in cognition were observed between SuperAgers and CNFA. CONCLUSIONS SuperAgers displayed resilience against clinical progression to MCI/dementia compared to CNFA despite equivalent risk for Alzheimer's disease (AD); however, SuperAgers had no greater protection from Aβ+ than CNFA. The deleterious effects of Aβ on cognition persist regardless of baseline cognitive ability. Thus, superior cognitive performance does not reflect resistance against the neuropathological processes associated with AD, and the observed resilience for SuperAgers may instead reflect neuropsychological criteria for cognitive impairment.
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Affiliation(s)
- Christa Dang
- Department of Obstetrics and Gynaecology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia.,The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Karra D Harrington
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,Cooperative Research Centre for Mental Health, Parkville, Victoria, Australia
| | - Yen Ying Lim
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - David Ames
- Academic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia.,National Ageing Research Institute, Parkville, Victoria, Australia
| | - Jason Hassenstab
- Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - Simon M Laws
- Cooperative Research Centre for Mental Health, Parkville, Victoria, Australia.,Collaborative Genomics Group, Centre of Excellence for Alzheimer's Disease Research and Care, School of Exercise, Biomedical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia.,School of Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Western Australia, Australia
| | - Nawaf Yassi
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,Department of Medicine and Neurology, Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Martha Hickey
- Department of Obstetrics and Gynaecology, Melbourne Medical School, The University of Melbourne, Parkville, Victoria, Australia
| | - Stephanie R Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia
| | - Joanne Robertson
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Victoria, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Hamid R Sohrabi
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Department of Biomedical Sciences, Macquarie University, Sydney, Australia
| | - Olivier Salvado
- CSIRO Health and Biosecurity, the Australian eHealth Research Centre, Brisbane, Queensland, Australia
| | - Michael Weinborn
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia.,Australian Alzheimer's Research Foundation, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, Western Australia, Australia.,School of Psychological Science, University of Western Australia, Crawley, Western Australia, Australia
| | - Victor L Villemagne
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Victoria, Australia.,Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Paul Maruff
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia.,CogState Ltd., Melbourne, Victoria, Australia
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186
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Huang SY, Zhu JX, Shen XN, Xu W, Ma YH, Li HQ, Dong Q, Tan L, Yu JT. Prevalence of the Preclinical Stages of Alzheimer's Disease in Cognitively Intact Older Adults: The CABLE Study. J Alzheimers Dis 2020; 75:483-492. [PMID: 32310174 DOI: 10.3233/jad-200059] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The National Institute on Aging and Alzheimer's Association proposed an ATN classification system which divided Alzheimer's disease biomarkers into three binary classes: amyloid deposition (A), tauopathy (T), and neurodegeneration or neuronal injury (N). OBJECTIVE To estimate the prevalence of each profile and to describe the demographic characteristics of each group in Chinese cognitively intact older adults. METHODS In this cross-sectional study, 561 cognitively intact participants from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) study were classified into eight groups using cerebrospinal fluid amyloid-β 42/40 as A, phosphorylated tau as T, and total tau as N. Multinomial models were used to determine the estimated prevalence of the eight groups. RESULTS The number and proportion of 561 participants in each ATN profile were 254 A-T-N- (45.3%), 28 A-T+N- (5.0%), 21 A-T-N+ (3.7%), 71 A-T+N+ (12.7%), 78 A + T-N- (13.9%), 14 A + T+N- (2.5%), 21 A + T-N+ (3.7%), and 74 A + T+N+ (13.2%). Individuals in N+ groups tend to be older than N- groups. A+ groups included more female individuals. The prevalence of A-T-N- profile declined with age, while that of A + T+N+ increased continuously. CONCLUSION This is the first work to estimate the prevalence of each ATN profile and describe the demographic characteristics of ATN profiles based on a Chinese cohort. The clinical implications of our findings need to be scrutinized further in longitudinal studies of the ATN classification system.
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Affiliation(s)
- Shu-Yi Huang
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun-Xia Zhu
- Department of Prevention and Health Protection, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hong-Qi Li
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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187
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Parker TD, Cash DM, Lane CA, Lu K, Malone IB, Nicholas JM, James S, Keshavan A, Murray‐Smith H, Wong A, Buchanan SM, Keuss SE, Sudre CH, Thomas DL, Crutch SJ, Fox NC, Richards M, Schott JM. Amyloid β influences the relationship between cortical thickness and vascular load. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12022. [PMID: 32313829 PMCID: PMC7163924 DOI: 10.1002/dad2.12022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/30/2019] [Accepted: 01/02/2020] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (Aβ) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear. METHODS We investigated the influences of Aβ status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness. RESULTS Higher WMHV, but not Aβ status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when Aβ-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region. DISCUSSION WMHV may differentially influence cortical thickness depending on the presence or absence of Aβ, potentially reflecting different pathological mechanisms.
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Affiliation(s)
- Thomas D. Parker
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - David M. Cash
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Christopher A. Lane
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Kirsty Lu
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Ian B. Malone
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Jennifer M. Nicholas
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- Department of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUK
| | | | - Ashvini Keshavan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Heidi Murray‐Smith
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCLLondonUK
| | - Sarah M. Buchanan
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Sarah E. Keuss
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Carole H. Sudre
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of Medical Physics and Biomedical EngineeringUCLLondonUK
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Queen Square Institute of NeurologyUCLLondonUK
- Neuroradiological Academic Unit, Department of Brain Repair and RehabilitationUCL Queen Square Institute of NeurologyLondonUK
| | - Sebastian J. Crutch
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | - Nick C. Fox
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
| | | | - Jonathan M. Schott
- Department of Neurodegenerative DiseaseThe Dementia Research Centre, UCL Queen Square Institute of NeurologyLondonUK
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188
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Ma LZ, Tan L, Bi YL, Shen XN, Xu W, Ma YH, Li HQ, Dong Q, Yu JT. Dynamic changes of CSF sTREM2 in preclinical Alzheimer's disease: the CABLE study. Mol Neurodegener 2020; 15:25. [PMID: 32276587 PMCID: PMC7149923 DOI: 10.1186/s13024-020-00374-8] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 04/02/2020] [Indexed: 02/06/2023] Open
Abstract
Background Loss of function of triggering receptor expressed on myeloid cell 2 (TREM2), a key receptor selectively expressed by microglia in the brain, contributes to the development of Alzheimer’s disease (AD). Whether TREM2 levels are pathologically altered during the preclinical phase, and whether cerebrospinal fluid (CSF) soluble TREM2 protein (sTREM2) has a relationship with major pathological processes including Aβ and tau deposition are still unclear. Methods According to the NIA-AA criteria, 659 cognitively normal participants from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) cohort were divided into four groups, stage 0 (normal Aβ1–42, T-tau and P-tau), stage 1 (low Aβ1–42, normal T-tau and P-tau), stage 2 (low Aβ1–42 and high T-tau or P-tau), and suspected non-AD pathology (SNAP) (normal Aβ1–42 and high T-tau or P-tau), to examine changes of CSF sTREM2 in the preclinical AD. Biomarker cut-off was based on the assumption that one-third of adults with normal cognition have AD pathology. Results The level of CSF sTREM2 in the stage 1 decreased compared with the stage 0 (P < 0.001), and then increased in the stage 2 (P = 0.008). SNAP individuals also had significantly increased CSF sTREM2 (P < 0.001). Results of multiple linear regressions also showed positive correlations of CSF sTREM2 with Aβ1–42 (β = 0.192, P < 0.001), T-tau (β = 0.215, P < 0.001) and P-tau (β = 0.123, P < 0.001). Conclusion CSF sTREM2 levels are dynamic in preclinical AD. Aβ pathology is associated with a decrease in CSF sTREM2 in the absence of tau deposition and neurodegeneration. However, tau pathology and neurodegeneration are associated with an increase in CSF sTREM2.
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Affiliation(s)
- Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan-Lin Bi
- Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hong-Qi Li
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, WHO Collaborating Center for Research and Training in Neurosciences, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China.
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189
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Doecke JD, Ward L, Burnham SC, Villemagne VL, Li QX, Collins S, Fowler CJ, Manuilova E, Widmann M, Rainey-Smith SR, Martins RN, Masters CL. Elecsys CSF biomarker immunoassays demonstrate concordance with amyloid-PET imaging. ALZHEIMERS RESEARCH & THERAPY 2020; 12:36. [PMID: 32234072 PMCID: PMC7110644 DOI: 10.1186/s13195-020-00595-5] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 03/09/2020] [Indexed: 12/17/2022]
Abstract
Background β-amyloid (Aβ) positron emission tomography (PET) imaging is currently the only Food and Drug Administration-approved method to support clinical diagnosis of Alzheimer’s disease (AD). However, numerous research studies support the use of cerebrospinal fluid (CSF) biomarkers, as a cost-efficient, quick and equally valid method to define AD pathology. Methods Using automated Elecsys® assays (Roche Diagnostics) for Aβ (1–42) (Aβ42), Aβ (1–40) (Aβ40), total tau (tTau) and phosphorylated tau (181P) (pTau), we examined CSF samples from 202 participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing cohort, to demonstrate the concordance with pathological AD via PET imaging. Results Ratios Aβ42/Aβ40, tTau/Aβ42 and pTau/Aβ42 had higher receiver operator characteristic—area under the curve (all 0.94), and greater concordance with Aβ-PET (overall percentage agreement ~ 90%), compared with individual biomarkers. Conclusion Strong concordance between CSF biomarkers and Aβ-PET status was observed overall, including for cognitively normal participants, further strengthening the association between these markers of AD neuropathological burden for both developmental research studies and for use in clinical trials. Supplementary information The online version of this article (10.1186/s13195-020-00595-5).
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Affiliation(s)
- James D Doecke
- Cooperative Research Council for Mental Health, Melbourne, Victoria, 3052, Australia. .,Australian E-Health Research Centre, CSIRO Health & Biosecurity, Level 5, 901/16 Royal Brisbane & Women's Hospital, Brisbane, Queensland, 4029, Australia.
| | - Larry Ward
- Cooperative Research Council for Mental Health, Melbourne, Victoria, 3052, Australia
| | - Samantha C Burnham
- Australian E-Health Research Centre, CSIRO, Parkville, Melbourne, Victoria, 3052, Australia
| | - Victor L Villemagne
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia.,Department of Molecular Imaging and Therapy, Center for PET, Austin Health, Heidelberg, Victoria, 3084, Australia
| | - Qiao-Xin Li
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
| | - Steven Collins
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia.,Department of Medicine (RMH), The University of Melbourne, Parkville, Melbourne, Victoria, 3052, Australia
| | - Christopher J Fowler
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
| | | | - Monika Widmann
- Roche Diagnostics GmbH, Sandhoferstrasse 116, 68305, Mannheim, Germany
| | - Stephanie R Rainey-Smith
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
| | - Ralph N Martins
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, 2113, Australia.,School of Psychiatry and Clinical Neurosciences, University of Western Australia, Crawley, Western Australia, 6009, Australia
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia
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190
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Alber J, Maruff P, Santos CY, Ott BR, Salloway SP, Yoo DC, Noto RB, Thompson LI, Goldfarb D, Arthur E, Song A, Snyder PJ. Disruption of cholinergic neurotransmission, within a cognitive challenge paradigm, is indicative of Aβ-related cognitive impairment in preclinical Alzheimer's disease after a 27-month delay interval. Alzheimers Res Ther 2020; 12:31. [PMID: 32209123 PMCID: PMC7093953 DOI: 10.1186/s13195-020-00599-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 03/11/2020] [Indexed: 11/12/2022]
Abstract
BACKGROUND Abnormal beta-amyloid (Aβ) is associated with deleterious changes in central cholinergic tone in the very early stages of Alzheimer's disease (AD), which may be unmasked by a cholinergic antagonist (J Prev Alzheimers Dis 1:1-4, 2017). Previously, we established the scopolamine challenge test (SCT) as a "cognitive stress test" screening measure to identify individuals at risk for AD (Alzheimer's & Dementia 10(2):262-7, 2014) (Neurobiol. Aging 36(10):2709-15, 2015). Here we aim to demonstrate the potential of the SCT as an indicator of cognitive change and neocortical amyloid aggregation after a 27-month follow-up interval. METHODS Older adults (N = 63, aged 55-75 years) with self-reported memory difficulties and first-degree family history of AD completed the SCT and PET amyloid imaging at baseline and were then seen for cognitive testing at 9, 18, and 27 months post-baseline. Repeat PET amyloid imaging was completed at the time of the 27-month exam. RESULTS Significant differences in both cognitive performance and in Aβ neocortical burden were observed between participants who either failed vs. passed the SCT at baseline, after a 27-month follow-up period. CONCLUSIONS Cognitive response to the SCT (Alzheimer's & Dementia 10(2):262-7, 2014) at baseline is related to cognitive change and PET amyloid imaging results, over the course of 27 months, in preclinical AD. The SCT may be a clinically useful screening tool to identify individuals who are more likely to both have positive evidence of amyloidosis on PET imaging and to show measurable cognitive decline over several years.
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Affiliation(s)
- Jessica Alber
- Department of Biological & Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, 75 Lower College Road, 2nd Floor, Kingston, RI USA
- Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI USA
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI USA
| | - Paul Maruff
- Cogstate Ltd., Melbourne, Victoria Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria Australia
| | - Cláudia Y. Santos
- Department of Biological & Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, 75 Lower College Road, 2nd Floor, Kingston, RI USA
| | - Brian R. Ott
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI USA
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI USA
| | - Stephen P. Salloway
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI USA
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI USA
| | - Don C. Yoo
- Department of Radiology, Warren Alpert Medical School of Brown University, Providence, RI USA
| | - Richard B. Noto
- Department of Radiology, Warren Alpert Medical School of Brown University, Providence, RI USA
| | - Louisa I. Thompson
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI USA
| | | | - Edmund Arthur
- Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI USA
| | - Alex Song
- Brown University, Providence, RI USA
| | - Peter J. Snyder
- Department of Biological & Pharmaceutical Sciences, College of Pharmacy, University of Rhode Island, 75 Lower College Road, 2nd Floor, Kingston, RI USA
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, RI USA
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191
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Papp KV, Buckley R, Mormino E, Maruff P, Villemagne VL, Masters C, Johnson KA, Rentz DM, Sperling RA, Amariglio RE, collaborators from the Harvard Aging Brain Study, the Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging, Biomarker and Lifestyle study of aging. Clinical meaningfulness of subtle cognitive decline on longitudinal testing in preclinical AD. Alzheimers Dement 2020; 16:552-560. [PMID: 31759879 PMCID: PMC7067681 DOI: 10.1016/j.jalz.2019.09.074] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Demonstrating the "clinical meaningfulness" of slowing early cognitive decline in clinically normal (CN) older adults with elevated amyloid-β (Aβ+) is critical for Alzheimer's disease secondary prevention trials and for understanding early cognitive progression. METHODS Cox regression analyses were used to determine whether 3-year slopes on the preclinical Alzheimer's cognitive composite predicted MCI diagnosis and global Clinical Dementia Rating>0 in 267 Aβ+ CN individuals participating in the Harvard Aging Brain Study, Australian Imaging, Biomarker and Lifestyle Study, and Alzheimer's Disease Neuroimaging Initiative. RESULTS Steeper preclinical Alzheimer's cognitive composite decline over 3 years was associated with increased risk for MCI diagnosis and global Clinical Dementia Rating>0 in the following years across all cohorts. Hazard ratios using meta-analytic estimates were 5.47 (95% CI: 3.25-9.18) for MCI diagnosis and 4.49 (95% CI: 2.84-7.09) for Clinical Dementia Rating>0 in those with subtle decline (>-.14 to -.26 preclinical Alzheimer's cognitive composite standard deviations/year) on longitudinal cognitive testing. DISCUSSION Early "subtle cognitive decline" among Aβ+ CN on a sensitive cognitive composite demonstrably increases risk for imminent clinical disease progression and functional impairment.
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Affiliation(s)
- Kathryn V. Papp
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel Buckley
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
- CogState, Ltd, Melbourne, Victoria, Australia
| | - Victor L. Villemagne
- Department of Nuclear Medicine and Centre for PET, Austin Health, Victoria, Australia
| | - Colin Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - Keith A. Johnson
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Dorene M. Rentz
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Reisa A. Sperling
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rebecca E. Amariglio
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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192
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Dhiman K, Gupta VB, Villemagne VL, Eratne D, Graham PL, Fowler C, Bourgeat P, Li Q, Collins S, Bush AI, Rowe CC, Masters CL, Ames D, Hone E, Blennow K, Zetterberg H, Martins RN. Cerebrospinal fluid neurofilament light concentration predicts brain atrophy and cognition in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12005. [PMID: 32211500 PMCID: PMC7085283 DOI: 10.1002/dad2.12005] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 10/16/2019] [Accepted: 11/01/2019] [Indexed: 12/22/2022]
Abstract
INTRODUCTION This study assessed the utility of cerebrospinal fluid (CSF) neurofilament light (NfL) in Alzheimer's disease (AD) diagnosis, its association with amyloid and tau pathology, as well as its potential to predict brain atrophy, cognition, and amyloid accumulation. METHODS CSF NfL concentration was measured in 221 participants from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL). RESULTS CSF NfL levels as well as NfL/amyloid β (Aβ42) were significantly elevated in AD compared to healthy controls (HC; P < .001), and in mild cognitive impairment (MCI) compared to HC (P = .008 NfL; P < .001 NfL/Aβ42). CSF NfL and NfL/Aβ42 differentiated AD from HC with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.84 and 0.90, respectively. CSF NfL and NfL/Aβ42 predicted cortical amyloid load, brain atrophy, and cognition. DISCUSSION CSF NfL is a biomarker of neurodegeneration, correlating with cognitive impairment and brain neuropathology.
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Affiliation(s)
- Kunal Dhiman
- Centre of Excellence in Alzheimer's Disease Research and CareSchool of Medical and Health SciencesEdith Cowan UniversityJoondalupWAAustralia
| | - Veer Bala Gupta
- Centre of Excellence in Alzheimer's Disease Research and CareSchool of Medical and Health SciencesEdith Cowan UniversityJoondalupWAAustralia
- School of MedicineDeakin UniversityVictoriaAustralia
| | - Victor L. Villemagne
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
- Department of Molecular Imaging & Therapy and Centre for PET, Austin HealthHeidelbergVictoriaAustralia
- Department of MedicineUniversity of MelbourneMelbourneVictoriaAustralia
| | - Dhamidhu Eratne
- Melbourne Neuropsychiatry CentreUniversity of Melbourne and NorthWestern Mental HealthParkvilleVictoriaAustralia
| | - Petra L. Graham
- Centre for Economic Impacts of Genomic Medicine (GenIMPACT)Macquarie UniversitySydneyNSWAustralia
| | - Christopher Fowler
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
| | | | - Qiao‐Xin Li
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
| | - Steven Collins
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
- Department of MedicineUniversity of MelbourneMelbourneVictoriaAustralia
| | - Ashley I. Bush
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
- Co‐operative Research Centre for Mental HealthCarltonVictoriaAustralia
| | - Christopher C. Rowe
- Department of Molecular Imaging & Therapy and Centre for PET, Austin HealthHeidelbergVictoriaAustralia
- Department of MedicineUniversity of MelbourneMelbourneVictoriaAustralia
| | - Colin L. Masters
- Florey Institute of Neuroscience and Mental HealthParkvilleVictoriaAustralia
| | - David Ames
- National Ageing Research InstituteParkvilleVictoriaAustralia
- Academic Unit for Psychiatry of Old ageSt. George's HospitalThe University of MelbourneAustralia
| | - Eugene Hone
- Centre of Excellence in Alzheimer's Disease Research and CareSchool of Medical and Health SciencesEdith Cowan UniversityJoondalupWAAustralia
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
| | - Ralph N. Martins
- Centre of Excellence in Alzheimer's Disease Research and CareSchool of Medical and Health SciencesEdith Cowan UniversityJoondalupWAAustralia
- Co‐operative Research Centre for Mental HealthCarltonVictoriaAustralia
- Australian Alzheimer's Research FoundationRalph and Patricia Sarich Neuroscience Research InstituteNedlandsWAAustralia
- Department of Biomedical SciencesMacquarie UniversitySydneyNSWAustralia
- School of Psychiatry and Clinical NeurosciencesUniversity of Western AustraliaPerthWAAustralia
- KaRa Institute of Neurological DiseasesSydneyNSWAustralia
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193
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Radiolabeling of [ 11C]FPS-ZM1, a receptor for advanced glycation end products-targeting positron emission tomography radiotracer, using a [ 11C]CO 2-to-[ 11C]CO chemical conversion. Future Med Chem 2020; 12:511-521. [PMID: 32100545 DOI: 10.4155/fmc-2019-0329] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Aim: The receptor for advanced glycation end products (RAGE) is a viable target for early Alzheimer's disease (AD) diagnosis using positron emission tomography (PET) as RAGE overexpression precedes Aβ plaque formation. The development of a carbon-11 analog of FPS-ZM1 (N-benzyl-4-chloro-N-cyclohexylbenzamide, [11C]FPS-ZM1), possessing nanomolar affinity for RAGE, may enable the imaging of RAGE for early AD detection. Methodology & results: Herein we report an optimized [11C]CO2-to-[11C]CO chemical conversion for the synthesis of [11C]FPS-ZM1 and in vitro brain autoradiography. The [11C]CO2-to-[11C]CO conversion via 11C-silanecarboxylate derivatives was achieved with a 57% yield within 30 s from end of [11C]CO2 delivery. [11C]FPS-ZM1 was obtained with a decay-corrected isolated radiochemical yield of 9.5%. Conclusion: [11C]FPS-ZM1 distribution in brain tissues of wild-type versus transgenic AD model mice showed no statistically significant difference and high nondisplaceable binding.
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194
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Buckley RF, Mormino EC, Rabin JS, Hohman TJ, Landau S, Hanseeuw BJ, Jacobs HIL, Papp KV, Amariglio RE, Properzi MJ, Schultz AP, Kirn D, Scott MR, Hedden T, Farrell M, Price J, Chhatwal J, Rentz DM, Villemagne VL, Johnson KA, Sperling RA. Sex Differences in the Association of Global Amyloid and Regional Tau Deposition Measured by Positron Emission Tomography in Clinically Normal Older Adults. JAMA Neurol 2020; 76:542-551. [PMID: 30715078 DOI: 10.1001/jamaneurol.2018.4693] [Citation(s) in RCA: 232] [Impact Index Per Article: 46.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Importance Mounting evidence suggests that sex differences exist in the pathologic trajectory of Alzheimer disease. Previous literature shows elevated levels of cerebrospinal fluid tau in women compared with men as a function of apolipoprotein E (APOE) ε4 status and β-amyloid (Aβ). What remains unclear is the association of sex with regional tau deposition in clinically normal individuals. Objective To examine sex differences in the cross-sectional association between Aβ and regional tau deposition as measured with positron emission tomography (PET). Design, Setting and Participants This is a study of 2 cross-sectional, convenience-sampled cohorts of clinically normal individuals who received tau and Aβ PET scans. Data were collected between January 2016 and February 2018 from 193 clinically normal individuals from the Harvard Aging Brain Study (age range, 55-92 years; 118 women [61%]) who underwent carbon 11-labeled Pittsburgh Compound B and flortaucipir F18 PET and 103 clinically normal individuals from the Alzheimer's Disease Neuroimaging Initiative (age range, 63-94 years; 55 women [51%]) who underwent florbetapir and flortaucipir F 18 PET. Main Outcomes and Measures A main association of sex with regional tau in the entorhinal cortices, inferior temporal lobe, and a meta-region of interest, which was a composite of regions in the temporal lobe. Associations between sex and global Aβ as well as sex and APOE ε4 on these regions after controlling for age were also examined. Results The mean (SD) age of all individuals was 74.2 (7.6) years (81 APOE ε4 carriers [31%]; 89 individuals [30%] with high Aβ). There was no clear association of sex with regional tau that was replicated across studies. However, in both cohorts, clinically normal women exhibited higher entorhinal cortical tau than men (meta-analytic estimate: β [male] = -0.11 [0.05]; 95% CI, -0.21 to -0.02; P = .02), which was associated with individuals with higher Aβ burden. A sex by APOE ε4 interaction was not associated with regional tau (meta-analytic estimate: β [male, APOE ε4+] = -0.15 [0.09]; 95% CI, -0.32 to 0.01; P = .07). Conclusions and Relevance Early tau deposition was elevated in women compared with men in individuals on the Alzheimer disease trajectory. These findings lend support to a growing body of literature that highlights a biological underpinning for sex differences in Alzheimer disease risk.
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Affiliation(s)
- Rachel F Buckley
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.,The Florey Institute, The University of Melbourne, Victoria, Australia.,Melbourne School of Psychological Science, University of Melbourne, Victoria, Australia
| | | | - Jennifer S Rabin
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley
| | - Bernard J Hanseeuw
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Department of Neurology, Cliniques Universitaires St-Luc, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Heidi I L Jacobs
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Kathryn V Papp
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Rebecca E Amariglio
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Michael J Properzi
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Aaron P Schultz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Dylan Kirn
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Matthew R Scott
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Trey Hedden
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Michelle Farrell
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Julie Price
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Jasmeer Chhatwal
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Dorene M Rentz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Victor L Villemagne
- Department of Nuclear Medicine and Centre for PET, Austin Health, Victoria, Australia
| | - Keith A Johnson
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Reisa A Sperling
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
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195
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Koscik RL, Betthauser TJ, Jonaitis EM, Allison SL, Clark LR, Hermann BP, Cody KA, Engle JW, Barnhart TE, Stone CK, Chin NA, Carlsson CM, Asthana S, Christian BT, Johnson SC. Amyloid duration is associated with preclinical cognitive decline and tau PET. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12007. [PMID: 32211502 PMCID: PMC7085284 DOI: 10.1002/dad2.12007] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 11/20/2019] [Indexed: 12/12/2022]
Abstract
INTRODUCTION This study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age-heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden. METHODS Cognitively unimpaired participants (n = 257) underwent one to four amyloid PET scans (Pittsburgh Compound B, PiB). Group-based trajectory modeling was applied to participants with longitudinal scans (n = 171) to identify and model amyloid trajectory groups, which were combined with Bayes theorem to estimate age and chronicity of amyloid positivity. Relationships between chronicity, cognition, clinical progression, and tau PET (MK-6240) were investigated using regression models. RESULTS Chronicity explained more heterogeneity in amyloid burden than age and binary amyloid status. Chronicity was associated with faster cognitive decline, increased risk of abnormal cognition, and higher entorhinal tau. DISCUSSION Amyloid chronicity provides unique information about cognitive decline and neurofibrillary tangle development and may be useful to investigate preclinical Alzheimer's disease.
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Affiliation(s)
- Rebecca L. Koscik
- Wisconsin Alzheimer's InstituteUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Tobey J. Betthauser
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Erin M. Jonaitis
- Wisconsin Alzheimer's InstituteUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Samantha L. Allison
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsin
| | - Lindsay R. Clark
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsin
| | - Bruce P. Hermann
- Wisconsin Alzheimer's InstituteUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of NeurologyUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Karly A. Cody
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Jonathan W. Engle
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Todd E. Barnhart
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Charles K. Stone
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Nathaniel A. Chin
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer's InstituteUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsin
| | - Sanjay Asthana
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsin
| | - Bradley T. Christian
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsin
- Waisman Laboratory for Brain Imaging and BehaviorUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Sterling C. Johnson
- Wisconsin Alzheimer's InstituteUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Department of MedicineUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Wisconsin Alzheimer's Disease Research CenterUniversity of WisconsinSchool of Medicine and Public HealthMadisonWisconsin
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsin
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196
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Yassi N, Hilal S, Xia Y, Lim YY, Watson R, Kuijf H, Fowler C, Yates P, Maruff P, Martins R, Ames D, Chen C, Rowe CC, Villemagne VL, Salvado O, Desmond PM, Masters CL. Influence of Comorbidity of Cerebrovascular Disease and Amyloid-β on Alzheimer’s Disease. J Alzheimers Dis 2020; 73:897-907. [DOI: 10.3233/jad-191028] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Nawaf Yassi
- Departments of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Saima Hilal
- Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Ying Xia
- The Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia
| | - Yen Ying Lim
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Rosie Watson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
| | - Hugo Kuijf
- Image Sciences Institute, University Medical Center, Utrecht, Utrecht, Netherlands
| | - Christopher Fowler
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Paul Yates
- Department of Aged Care Services, Austin Health, Heidelberg, Australia
- Department of Medicine, Austin Hospital, University of Melbourne, Heidelberg, Australia
| | | | - Ralph Martins
- Centre of Excellence for Alzheimer’s Disease Research and Care, Edith Cowan University, Perth, Australia
| | - David Ames
- Academic Unit for Psychiatry of Old Age, University of Melbourne, Parkville, Australia
- National Ageing Research Institute, Parkville, Australia
| | - Christopher Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore
| | - Christopher C. Rowe
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Victor L. Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia
| | - Olivier Salvado
- Data61, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia
| | - Patricia M. Desmond
- Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
| | - Colin L. Masters
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
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197
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Apolipoprotein E ε4 Allele is Associated With Plasma Amyloid Beta and Amyloid Beta Transporter Levels: A Cross-sectional Study in a Rural Area of Xi'an, China. Am J Geriatr Psychiatry 2020; 28:194-204. [PMID: 31350163 DOI: 10.1016/j.jagp.2019.06.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 06/21/2019] [Accepted: 06/24/2019] [Indexed: 11/23/2022]
Abstract
OBJECTIVE The effects of the Apolipoprotein E (ApoE) genotype on peripheral amyloid beta (Aβ) and Aβ transporter levels are still unclear. Soluble low-density lipoprotein receptor-related protein-1 (sLRP1) and soluble receptor of advanced glycation end products (sRAGE) are the major transporter for Aβ, which can prevent plasma Aβ from flowing into brain. The aim of this study was to investigate the relationships between the ApoE genotype and plasma Aβ, sLRP1, sRAGE levels. DESIGN Cross-sectional study. SETTING The committee office of the village. PARTICIPANTS Residents lived in the village for more than 3 years, aged 40-85 years (n = 1,119, 63.5% women). MEASUREMENTS Plasma biomarkers include ApoE genotype, Aβ, sLRP1, sRAGE, fasting blood-glucose, and blood lipids. General information, medical history, living habits, and cognitive status (cognitive impairment or not) were also collected. RESULTS After controlling for all possible covariates, multiple linear regression analysis showed that the plasma level of Aβ42 was higher and log-transformed sLRP1 was lower in ApoE ε4 carriers than that in noncarriers (βAβ42 = 1.214, 95% confidence interval: 0.105-2.316, pAβ42 = 0.031; βsLRP1 = -0.075, 95% confidence interval: -0.129 to -0.021, psLRP1 = 0.006, respectively). Partial correlation analysis showed that plasma Aβ40 was positively correlated with log-transformed sLRP1 and log-transformed sRAGE (rsLRP1 = 0.116, psLRP1 <0.001; rsRAGE = 0.078, psLRP1 = 0.009, respectively). Plasma Aβ42 was positively correlated with log-transformed sRAGE (r = 0.072, p = 0.017). CONCLUSION ApoE ε4 carriers had higher plasma Aβ42 levels and lower sLRP1 levels. These data indicated that the ApoE ε4 allele may also contribute to the pathogenesis of Alzheimer's disease through its effects on peripheral Aβ42 and sLRP1 levels, but it needs to be further elucidated.
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198
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Elias A, Cummins T, Lamb F, Tyrrell R, Dore V, Williams R, Rosenfeld JV, Hopwood M, Villemagne VL, Rowe CC. Amyloid-β, Tau, and 18F-Fluorodeoxyglucose Positron Emission Tomography in Posttraumatic Stress Disorder. J Alzheimers Dis 2020; 73:163-173. [DOI: 10.3233/jad-190913] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Alby Elias
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Tia Cummins
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Fiona Lamb
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Regan Tyrrell
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Vincent Dore
- Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia
| | - Rob Williams
- Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Jeffrey V. Rosenfeld
- Department of Surgery, Monash University, VIC, Australia
- Department of Neurosurgery, Alfred Hospital, Melbourne, VIC, Australia
| | - Malcolm Hopwood
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Victor L. Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Christopher C. Rowe
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
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199
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Betthauser TJ, Koscik RL, Jonaitis EM, Allison SL, Cody KA, Erickson CM, Rowley HA, Stone CK, Mueller KD, Clark LR, Carlsson CM, Chin NA, Asthana S, Christian BT, Johnson SC. Amyloid and tau imaging biomarkers explain cognitive decline from late middle-age. Brain 2020; 143:320-335. [PMID: 31886494 PMCID: PMC6935717 DOI: 10.1093/brain/awz378] [Citation(s) in RCA: 118] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 09/23/2019] [Accepted: 10/11/2019] [Indexed: 11/14/2022] Open
Abstract
This study investigated differences in retrospective cognitive trajectories between amyloid and tau PET biomarker stratified groups in initially cognitively unimpaired participants sampled from the Wisconsin Registry for Alzheimer's Prevention. One hundred and sixty-seven initially unimpaired individuals (baseline age 59 ± 6 years; 115 females) were stratified by elevated amyloid-β and tau status based on 11C-Pittsburgh compound B (PiB) and 18F-MK-6240 PET imaging. Mixed effects models were used to determine if longitudinal cognitive trajectories based on a composite of cognitive tests including memory and executive function differed between biomarker groups. Secondary analyses investigated group differences for a variety of cross-sectional health and cognitive tests, and associations between 18F-MK-6240, 11C-PiB, and age. A significant group × age interaction was observed with post hoc comparisons indicating that the group with both elevated amyloid and tau pathophysiology were declining approximately three times faster in retrospective cognition compared to those with just one or no elevated biomarkers. This result was robust against various thresholds and medial temporal lobe regions defining elevated tau. Participants were relatively healthy and mostly did not differ between biomarker groups in health factors at the beginning or end of study, or most cognitive measures at study entry. Analyses investigating association between age, MK-6240 and PiB indicated weak associations between age and 18F-MK-6240 in tangle-associated regions, which were negligible after adjusting for 11C-PiB. Strong associations, particularly in entorhinal cortex, hippocampus and amygdala, were observed between 18F-MK-6240 and global 11C-PiB in regions associated with Braak neurofibrillary tangle stages I-VI. These results suggest that the combination of pathological amyloid and tau is detrimental to cognitive decline in preclinical Alzheimer's disease during late middle-age. Within the Alzheimer's disease continuum, middle-age health factors likely do not greatly influence preclinical cognitive decline. Future studies in a larger preclinical sample are needed to determine if and to what extent individual contributions of amyloid and tau affect cognitive decline. 18F-MK-6240 shows promise as a sensitive biomarker for detecting neurofibrillary tangles in preclinical Alzheimer's disease.
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Affiliation(s)
- Tobey J Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca L Koscik
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Samantha L Allison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Karly A Cody
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Claire M Erickson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Howard A Rowley
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Charles K Stone
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Kimberly D Mueller
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
| | - Lindsay R Clark
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Cynthia M Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Nathaniel A Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Veterans Hospital, Madison, WI, USA
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Chandra A, Valkimadi PE, Pagano G, Cousins O, Dervenoulas G, Politis M. Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment. Hum Brain Mapp 2019; 40:5424-5442. [PMID: 31520513 PMCID: PMC6864887 DOI: 10.1002/hbm.24782] [Citation(s) in RCA: 119] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2019] [Revised: 07/29/2019] [Accepted: 08/18/2019] [Indexed: 02/06/2023] Open
Abstract
Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease-modifying therapeutic interventions. This review provides an overview of the current status and applications of in vivo molecular imaging of AD pathology, specifically amyloid, tau, and microglial activation. PET imaging studies were included and evaluated as potential biomarkers and for monitoring disease progression. Although the majority of radiotracers showed the ability to discriminate AD and MCI patients from healthy controls, they had various limitations that prevent the recommendation of a single technique or tracer as an optimal biomarker. Newer research examining amyloid, tau, and microglial PET imaging in combination suggest an alternative approach in studying the disease process.
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Affiliation(s)
- Avinash Chandra
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Polytimi-Eleni Valkimadi
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Gennaro Pagano
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Oliver Cousins
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - George Dervenoulas
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Marios Politis
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
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