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Hong J, Kang SK, Alberts I, Lu J, Sznitman R, Lee JS, Rominger A, Choi H, Shi K. Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET. Eur J Nucl Med Mol Imaging 2022; 49:3061-3072. [PMID: 35226120 PMCID: PMC9250490 DOI: 10.1007/s00259-021-05662-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 12/15/2021] [Indexed: 11/26/2022]
Abstract
Purpose Alzheimer’s disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE). Methods A total of 1080 [18F]Flortaucipir brain positron emission tomography (PET) images were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. VAE was built to compress the hidden features from tau images in latent space. Hierarchical agglomerative clustering and minimum spanning tree (MST) were applied to organize the features and calibrate them to the tau progression, thus deriving pseudo-time. The image-level tau trajectory was inferred by continuously sampling across the calibrated latent features. We assessed the pseudo-time with regard to tau standardized uptake value ratio (SUVr) in AD-vulnerable regions, amyloid deposit, glucose metabolism, cognitive scores, and clinical diagnosis. Results We identified four clusters that plausibly capture certain stages of AD and organized the clusters in the latent space. The inferred tau trajectory agreed with the Braak staging. According to the derived pseudo-time, tau first deposits in the parahippocampal and amygdala, and then spreads to the fusiform, inferior temporal lobe, and posterior cingulate. Prior to the regional tau deposition, amyloid accumulates first. Conclusion The spatiotemporal trajectory of tau progression inferred in this study was consistent with Braak staging. The profile of other biomarkers in disease progression agreed well with previous findings. We addressed that this approach additionally has the potential to quantify tau progression as a continuous variable by taking a whole-brain tau image into account. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05662-z.
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Affiliation(s)
- Jimin Hong
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
- ARTORG Center, University of Bern, Bern, Switzerland
| | - Seung Kwan Kang
- Department of Nuclear Medicine, Seoul National University Hospital, 28 Yeon Gun, Jong Ro, Seoul, Republic of Korea
| | - Ian Alberts
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
| | - Jiaying Lu
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Jae Sung Lee
- Department of Nuclear Medicine, Seoul National University Hospital, 28 Yeon Gun, Jong Ro, Seoul, Republic of Korea
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, 28 Yeon Gun, Jong Ro, Seoul, Republic of Korea
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010 Bern, Switzerland
- Department of Informatics, Technical University of Munich, Munich, Germany
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Ashton NJ, Benedet AL, Pascoal TA, Karikari TK, Lantero-Rodriguez J, Brum WS, Mathotaarachchi S, Therriault J, Savard M, Chamoun M, Stoops E, Francois C, Vanmechelen E, Gauthier S, Zimmer ER, Zetterberg H, Blennow K, Rosa-Neto P. Cerebrospinal fluid p-tau231 as an early indicator of emerging pathology in Alzheimer's disease. EBioMedicine 2022; 76:103836. [PMID: 35158308 PMCID: PMC8850760 DOI: 10.1016/j.ebiom.2022.103836] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 01/11/2022] [Accepted: 01/11/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Phosphorylated tau (p-tau) epitopes in cerebrospinal fluid (CSF) are accurate biomarkers for a pathological and clinical diagnosis of Alzheimer's disease (AD) and are seen to be increased in preclinical stage of the disease. However, it is unknown if these increases transpire earlier, prior to amyloid-beta (Aβ) positivity as determined by position emission tomography (PET), and if an ordinal sequence of p-tau epitopes occurs at this incipient phase METHODS: We measured CSF concentrations of p-tau181, p-tau217 and p-tau231 in 171 participants across the AD continuum who had undergone Aβ ([18F]AZD4694) and tau ([18F]MK6240) position emission tomography (PET) and clinical assessment FINDINGS: All CSF p-tau biomarkers were accurate predictors of cognitive impairment but CSF p-tau217 demonstrated the largest fold-changes in AD patients in comparison to non-AD dementias and cognitively unimpaired individuals. CSF p-tau231 and p-tau217 predicted Aβ and tau to a similar degree but p-tau231 attained abnormal levels first. P-tau231 was sensitive to the earliest changes of Aβ in the medial orbitofrontal, precuneus and posterior cingulate before global Aβ PET positivity was reached INTERPRETATION: We demonstrate that CSF p-tau231 increases early in development of AD pathology and is a principal candidate for detecting incipient Aβ pathology for therapeutic trial application FUNDING: Canadian Institutes of Health Research (CIHR), Canadian Consortium of Neurodegeneration and Aging, Weston Brain Institute, Brain Canada Foundation, the Fonds de Recherche du Québec.
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK; NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada; Department of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Department of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Melissa Savard
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Erik Stoops
- ADx NeuroSciences, Technologiepark 94, Ghent 9052, Belgium
| | - Cindy Francois
- ADx NeuroSciences, Technologiepark 94, Ghent 9052, Belgium
| | | | - Serge Gauthier
- McGill University Research Centre for Studies in Aging, Douglas Research Institute, Le Centre intégré universitaire de santé et de services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada; Department of Neurology and Neurosurgery, Director of the McGill University Research Centre for Studies in Aging, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Department of Pharmacology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, Director of the McGill University Research Centre for Studies in Aging, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada; Montreal Neurological Institute, Montreal, QC, Canada.
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Lim YY, Maruff P, Barthélemy NR, Goate A, Hassenstab J, Sato C, Fagan AM, Benzinger TLS, Xiong C, Cruchaga C, Levin J, Farlow MR, Graff-Radford NR, Laske C, Masters CL, Salloway S, Schofield PR, Morris JC, Bateman RJ, McDade E. Association of BDNF Val66Met With Tau Hyperphosphorylation and Cognition in Dominantly Inherited Alzheimer Disease. JAMA Neurol 2022; 79:261-270. [PMID: 35099506 PMCID: PMC8804973 DOI: 10.1001/jamaneurol.2021.5181] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
IMPORTANCE Allelic variation in the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism moderates increases in cerebrospinal fluid (CSF) levels of tau and phosphorylated tau 181 (p-tau181), measured using immunoassay, and cognitive decline in presymptomatic dominantly inherited Alzheimer disease (DIAD). Advances in mass spectrometry show that CSF tau phosphorylation occupancy at threonine 181 and 217 (p-tau181/tau181, p-tau217/tau217) increases with initial β-amyloid (Aβ) aggregation, while phosphorylation occupancy at threonine 205 (p-tau205/tau205) and level of total tau increase when brain atrophy and clinical symptoms become evident. OBJECTIVE To determine whether site-specific tau phosphorylation occupancy (ratio of phosphorylated to unphosphorylated tau) is associated with BDNF Val66Met in presymptomatic and symptomatic DIAD. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional cohort study included participants from the Dominantly Inherited Alzheimer Network (DIAN) and Aβ-positive cognitively normal older adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Data were collected from 2009 through 2018 at multicenter clinical sites in the United States, United Kingdom, and Australia, with no follow-up. DIAN participants provided a CSF sample and completed clinical and cognitive assessments. Data analysis was conducted between March 2020 and March 2021. MAIN OUTCOMES AND MEASURES Mass spectrometry analysis was used to determine site-specific tau phosphorylation level; tau levels were also measured using immunoassay. Episodic memory and global cognitive composites were computed. RESULTS Of 374 study participants, 144 were mutation noncarriers, 156 were presymptomatic mutation carriers, and 74 were symptomatic carriers. Of the 527 participants in the network, 153 were excluded because their CSF sample, BDNF status, or both were unavailable. Also included were 125 Aβ-positive cognitively normal older adults in the ADNI. The mean (SD) age of DIAD participants was 38.7 (10.9) years; 43% were women. The mean (SD) age of participants with preclinical sporadic AD was 74.8 (5.6) years; 52% were women. In presymptomatic mutation carriers, compared with Val66 homozygotes, Met66 carriers showed significantly poorer episodic memory (d = 0.62; 95% CI, 0.28-0.95), lower hippocampal volume (d = 0.40; 95% CI, 0.09-0.71), and higher p-tau217/tau217 (d = 0.64; 95% CI, 0.30-0.97), p-tau181/tau181 (d = 0.65; 95% CI, 0.32-0.99), and mass spectrometry total tau (d = 0.43; 95% CI, 0.10-0.76). In symptomatic mutation carriers, Met66 carriers showed significantly poorer global cognition (d = 1.17; 95% CI, 0.65-1.66) and higher p-tau217/tau217 (d = 0.53; 95% CI, 0.05-1.01), mass spectrometry total tau (d = 0.78; 95% CI, 0.28-1.25), and p-tau205/tau205 (d = 0.97; 95% CI, 0.46-1.45), when compared with Val66 homozygotes. In preclinical sporadic AD, Met66 carriers showed poorer episodic memory (d = 0.39; 95% CI, 0.00-0.77) and higher total tau (d = 0.45; 95% CI, 0.07-0.84) and p-tau181 (d = 0.46; 95% CI, 0.07-0.85). CONCLUSIONS AND RELEVANCE In DIAD, clinical disease stage and BDNF Met66 were associated with cognitive impairment and levels of site-specific tau phosphorylation. This suggests that pharmacological strategies designed to increase neurotrophic support in the presymptomatic stages of AD may be beneficial.
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Affiliation(s)
- Yen Ying Lim
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
| | - Paul Maruff
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia,Cogstate Ltd, Melbourne, Victoria, Australia
| | - Nicolas R. Barthélemy
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Alison Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Chihiro Sato
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Anne M. Fagan
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Tammie L. S. Benzinger
- Department of Radiology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany,German Center for Neurodegenerative Diseases, Munich, Germany,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | | | | | - Christoph Laske
- German Center for Neurodegenerative Diseases, Munich, Germany,Section for Dementia Research, Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Colin L. Masters
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
| | - Stephen Salloway
- Butler Hospital, Providence, Rhode Island,Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia,School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine in St Louis, St Louis, Missouri
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Differential associations between neocortical tau pathology and blood flow with cognitive deficits in early-onset vs late-onset Alzheimer's disease. Eur J Nucl Med Mol Imaging 2022; 49:1951-1963. [PMID: 34997294 PMCID: PMC9016024 DOI: 10.1007/s00259-021-05669-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/20/2021] [Indexed: 12/23/2022]
Abstract
Purpose Early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD. Methods Seventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n = 35, age-at-PET = 59 ± 5, MMSE = 23 ± 4; LOAD: n = 44, age-at-PET = 71 ± 5, MMSE = 23 ± 4) underwent a 130-min dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital, and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language, and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition. Results Both region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipitoparietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND − 0.76 ≤ stβ ≤ − 0.48 vs LOAD − 0.18 ≤ stβ ≤ − 0.02; EOAD R1 0.37 ≤ stβ ≤ 0.84 vs LOAD − 0.25 ≤ stβ ≤ 0.16). Conclusions Compared to LOAD, the degree of lateral temporal and occipitoparietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05669-6.
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Hubbard EE, Heil LR, Merrihew GE, Chhatwal JP, Farlow MR, McLean CA, Ghetti B, Newell KL, Frosch MP, Bateman RJ, Larson EB, Keene CD, Perrin RJ, Montine TJ, MacCoss MJ, Julian RR. Does Data-Independent Acquisition Data Contain Hidden Gems? A Case Study Related to Alzheimer's Disease. J Proteome Res 2022; 21:118-131. [PMID: 34818016 PMCID: PMC8741752 DOI: 10.1021/acs.jproteome.1c00558] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer's disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified.
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Affiliation(s)
- Evan E. Hubbard
- Department of Chemistry, University of California, Riverside, California 92521, United States
| | - Lilian R. Heil
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Gennifer E. Merrihew
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Jasmeer P. Chhatwal
- Harvard Medical School, Massachusetts General Hospital, Department of Neurology, 15 Parkman St, Suite 835, Boston MA 02114
| | - Martin R. Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, 46202
| | | | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Kathy L. Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Matthew P. Frosch
- C.S. Kubik Laboratory for Neuropathology, and Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA 02114
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, 63110, Missouri, USA
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute and Department of Medicine, University of Washington, Seattle WA
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, 98195, United States
| | - Richard J. Perrin
- Department of Pathology and Immunology, Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri 63110, United States
| | - Thomas J. Montine
- Department of Pathology, Stanford University, Stanford, CA, 94305, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, Seattle, Washington, 98195, United States
| | - Ryan R. Julian
- Department of Chemistry, University of California, Riverside, California 92521, United States,corresponding author:
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McEvoy LK. Disruption of White Matter Connectivity Precedes Development of Dementia in Alzheimer Disease. Radiology 2022; 302:151-152. [PMID: 34636642 PMCID: PMC8717686 DOI: 10.1148/radiol.2021212097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 08/23/2021] [Accepted: 08/26/2021] [Indexed: 01/03/2023]
Affiliation(s)
- Linda K. McEvoy
- From the Herbert Wertheim School of Public Health and Human Longevity
Science, Department of Radiology, School of Medicine, University of California
San Diego, 9500 Gilman Dr, MC 0841, La Jolla, CA 92093
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Golde TE. Disease-Modifying Therapies for Alzheimer's Disease: More Questions than Answers. Neurotherapeutics 2022; 19:209-227. [PMID: 35229269 PMCID: PMC8885119 DOI: 10.1007/s13311-022-01201-2] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2022] [Indexed: 12/17/2022] Open
Abstract
Scientific advances over the last four decades have steadily infused the Alzheimer's disease (AD) field with great optimism that therapies targeting Aβ, amyloid, tau, and innate immune activation states in the brain would provide disease modification. Unfortunately, this optimistic scenario has not yet played out. Though a recent approval of the anti-Aβ aggregate binding antibody, Aduhelm (aducanumab), as a "disease-modifying therapy for AD" is viewed by some as a breakthrough, many remain unconvinced by the data underlying this approval. Collectively, we have not succeeded in changing AD from a largely untreatable, inevitable, and incurable disease to a treatable, preventable, and curable one. Here, I will review the major foci of the AD "disease-modifying" therapeutic pipeline and some of the "open questions" that remain in terms of these therapeutic approaches. I will conclude the review by discussing how we, as a field, might adjust our approach, learning from our past failures to ensure future success.
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Affiliation(s)
- Todd E Golde
- Departments of Neuroscience and Neurology, Center for Translational Research in Neurodegenerative Disease, Evelyn F. and William L. McKnight Brain Institute, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA.
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Frisoni GB, Altomare D, Thal DR, Ribaldi F, van der Kant R, Ossenkoppele R, Blennow K, Cummings J, van Duijn C, Nilsson PM, Dietrich PY, Scheltens P, Dubois B. The probabilistic model of Alzheimer disease: the amyloid hypothesis revised. Nat Rev Neurosci 2022; 23:53-66. [PMID: 34815562 PMCID: PMC8840505 DOI: 10.1038/s41583-021-00533-w] [Citation(s) in RCA: 185] [Impact Index Per Article: 92.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/04/2021] [Indexed: 01/03/2023]
Abstract
The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.
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Affiliation(s)
- Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland.
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, University of Leuven, Leuven, Belgium
- Department of Pathology, University Hospital Leuven, Leuven, Belgium
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Centro S. Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Rik van der Kant
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Kaj Blennow
- Cinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences; University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Peter M Nilsson
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Life Science Partners, Amsterdam, Netherlands
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d'Alzheimer, IM2A, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France
- Institut du Cerveau et de la Moelle Épinière, UMR-S975, INSERM, Paris, France
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Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline. Nat Med 2022; 28:2381-2387. [PMID: 36357681 PMCID: PMC9671808 DOI: 10.1038/s41591-022-02049-x] [Citation(s) in RCA: 123] [Impact Index Per Article: 61.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/21/2022] [Indexed: 11/12/2022]
Abstract
A major unanswered question in the dementia field is whether cognitively unimpaired individuals who harbor both Alzheimer's disease neuropathological hallmarks (that is, amyloid-β plaques and tau neurofibrillary tangles) can preserve their cognition over time or are destined to decline. In this large multicenter amyloid and tau positron emission tomography (PET) study (n = 1,325), we examined the risk for future progression to mild cognitive impairment and the rate of cognitive decline over time among cognitively unimpaired individuals who were amyloid PET-positive (A+) and tau PET-positive (T+) in the medial temporal lobe (A+TMTL+) and/or in the temporal neocortex (A+TNEO-T+) and compared them with A+T- and A-T- groups. Cox proportional-hazards models showed a substantially increased risk for progression to mild cognitive impairment in the A+TNEO-T+ (hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9-33.7), A+TMTL+ (HR = 14.6, 95% CI = 8.1-26.4) and A+T- (HR = 2.4, 95% CI = 1.4-4.3) groups versus the A-T- (reference) group. Both A+TMTL+ (HR = 6.0, 95% CI = 3.4-10.6) and A+TNEO-T+ (HR = 7.9, 95% CI = 4.7-13.5) groups also showed faster clinical progression to mild cognitive impairment than the A+T- group. Linear mixed-effect models indicated that the A+TNEO-T+ (β = -0.056 ± 0.005, T = -11.55, P < 0.001), A+TMTL+ (β = -0.024 ± 0.005, T = -4.72, P < 0.001) and A+T- (β = -0.008 ± 0.002, T = -3.46, P < 0.001) groups showed significantly faster longitudinal global cognitive decline compared to the A-T- (reference) group (all P < 0.001). Both A+TNEO-T+ (P < 0.001) and A+TMTL+ (P = 0.002) groups also progressed faster than the A+T- group. In summary, evidence of advanced Alzheimer's disease pathological changes provided by a combination of abnormal amyloid and tau PET examinations is strongly associated with short-term (that is, 3-5 years) cognitive decline in cognitively unimpaired individuals and is therefore of high clinical relevance.
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Wu J, Dong Q, Zhang J, Su Y, Wu T, Caselli RJ, Reiman EM, Ye J, Lepore N, Chen K, Thompson PM, Wang Y. Federated Morphometry Feature Selection for Hippocampal Morphometry Associated Beta-Amyloid and Tau Pathology. Front Neurosci 2021; 15:762458. [PMID: 34899166 PMCID: PMC8655732 DOI: 10.3389/fnins.2021.762458] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 11/01/2021] [Indexed: 12/03/2022] Open
Abstract
Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer's disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. One of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research focuses in the AD pathophysiological progress. This work proposes a novel framework, Federated Morphometry Feature Selection (FMFS) model, to examine subtle aspects of hippocampal morphometry that are associated with Aβ/tau burden in the brain, measured using positron emission tomography (PET). FMFS is comprised of hippocampal surface-based feature calculation, patch-based feature selection, federated group LASSO regression, federated screening rule-based stability selection, and region of interest (ROI) identification. FMFS was tested on two Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts to understand hippocampal alterations that relate to Aβ/tau depositions. Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects. Experimental results demonstrated that FMFS achieves an 89× speedup compared to other published state-of-the-art methods under five independent hypothetical institutions. In addition, the subiculum and cornu ammonis 1 (CA1 subfield) were identified as hippocampal subregions where atrophy is strongly associated with abnormal Aβ/tau. As potential biomarkers for Aβ/tau pathology, the features from the identified ROIs had greater power for predicting cognitive assessment and for survival analysis than five other imaging biomarkers. All the results indicate that FMFS is an efficient and effective tool to reveal associations between Aβ/tau burden and hippocampal morphometry.
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Affiliation(s)
- Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Qunxi Dong
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
- Institute of Engineering Medicine, Beijing Institute of Technology, Beijing, China
| | - Jie Zhang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Teresa Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
| | - Richard J. Caselli
- Department of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Jieping Ye
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, CA, United States
| | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, United States
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
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Murchison AG. Hypothesis: Modulation of microglial phenotype in Alzheimer's disease drives neurodegeneration. Alzheimers Dement 2021; 18:1537-1544. [PMID: 34786841 DOI: 10.1002/alz.12503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 09/17/2021] [Accepted: 09/21/2021] [Indexed: 11/11/2022]
Abstract
The pathophysiology of Alzheimer's disease (AD) remains to be elucidated. The amyloid hypothesis holds explanatory power but has limitations. This article suggests that amyloid deposition and increased permeability of the blood-brain barrier are independent early events in the disease process, which together fashion a distinct microglial activation phenotype. Downstream events including, phagocytosis of synapses and persistent glutamate signaling through N-methyl-D-aspartate receptors drive neurodegeneration and tau pathology. This hypothesis draws on several strands of evidence and aims to illuminate several of the unexplained temporal and spatial features of AD.
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Wu J, Zhu W, Su Y, Gui J, Lepore N, Reiman EM, Caselli RJ, Thompson PM, Chen K, Wang Y. Predicting Tau Accumulation in Cerebral Cortex with Multivariate MRI Morphometry Measurements, Sparse Coding, and Correntropy. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2021; 12088:120880O. [PMID: 34961803 PMCID: PMC8710175 DOI: 10.1117/12.2607169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD) may be the key to prevention breakthroughs. One of the hallmarks of AD is the accumulation of tau plaques in the human brain. However, current methods to detect tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (Tau PET). In our previous work, structural MRI-based hippocampal multivariate morphometry statistics (MMS) showed superior performance as an effective neurodegenerative biomarker for preclinical AD and Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) has excellent ability to generate low-dimensional representations with strong statistical power for brain amyloid prediction. In this work, we apply this framework together with ridge regression models to predict Tau deposition in Braak12 and Braak34 brain regions separately. We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan which were collected at about the same times. Experimental results suggest that the representations from our MMS and PASCS-MP have stronger predictive power and their predicted Braak12 and Braak34 are closer to the real values compared to the measures derived from other approaches such as hippocampal surface area and volume, and shape morphometry features based on spherical harmonics (SPHARM).
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Affiliation(s)
- Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, USA
| | - Wenhui Zhu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Jie Gui
- School of Cyber Science and Engineering, Southeast University, Nanjing, China
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology Children’s Hospital Los Angeles, Los Angeles, USA
| | | | | | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, USA
| | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, USA
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Lucey BP, Wisch J, Boerwinkle AH, Landsness EC, Toedebusch CD, McLeland JS, Butt OH, Hassenstab J, Morris JC, Ances BM, Holtzman DM. Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease. Brain 2021; 144:2852-2862. [PMID: 34668959 PMCID: PMC8536939 DOI: 10.1093/brain/awab272] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 06/13/2021] [Accepted: 07/01/2021] [Indexed: 11/12/2022] Open
Abstract
Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.
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Affiliation(s)
- Brendan P Lucey
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Julie Wisch
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Anna H Boerwinkle
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Eric C Landsness
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Cristina D Toedebusch
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jennifer S McLeland
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Omar H Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
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Clark AL, Weigand AJ, Bangen KJ, Thomas KR, Eglit GM, Bondi MW, Delano‐Wood L. Higher cerebrospinal fluid tau is associated with history of traumatic brain injury and reduced processing speed in Vietnam-era veterans: A Department of Defense Alzheimer's Disease Neuroimaging Initiative (DOD-ADNI) study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12239. [PMID: 34692979 PMCID: PMC8515227 DOI: 10.1002/dad2.12239] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 12/02/2022]
Abstract
INTRODUCTION Our goal was to determine whether cognitive and cerebrospinal fluid (CSF) markers of tau and amyloid beta 1-42 (Aβ42) differ between Vietnam-era veterans with and without history of traumatic brain injury (TBI) and whether TBI moderates the association between CSF markers and neurocognitive functioning. METHODS A total of 102 male participants (52 TBI, 50 military controls [MCs]; mean age = 68) were included. Levels of CSF Aβ42, tau phosphorylated at the threonine 181 position (p-tau), and total tau (t-tau) were quantified. Group differences in CSF markers and cognition as well as the moderating effect of TBI on CSF and cognition associations were explored. RESULTS Relative to MCs, the TBI group showed significantly higher p-tau (P = .01) and t-tau (P = .02), but no differences in amyloid (P = .09). TBI history moderated the association between CSF tau and performance on a measure of processing speed (t-tau: P = .04; p-tau: P = .02). DISCUSSION Tau accumulation may represent a mechanism of dementia risk in older veterans with remote TBI.
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Affiliation(s)
- Alexandra L. Clark
- Department of PsychologyUniversity of Texas at AustinAustinTexasUSA
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Alexandra J. Weigand
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- San Diego (SDSU/UCSD) Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Katherine J. Bangen
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Kelsey R. Thomas
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Graham M.L. Eglit
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Mark W. Bondi
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
| | - Lisa Delano‐Wood
- Research and Psychology ServicesVA San Diego Healthcare System (VASDHS)La JollaCaliforniaUSA
- Department of Psychiatry, School of MedicineUniversity of California San DiegoSan DiegoCaliforniaUSA
- Center of Excellence for Stress and Mental HealthVASDHSLa JollaCaliforniaUSA
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Do Carmo S, Spillantini MG, Cuello AC. Editorial: Tau Pathology in Neurological Disorders. Front Neurol 2021; 12:754669. [PMID: 34630315 PMCID: PMC8497747 DOI: 10.3389/fneur.2021.754669] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 08/26/2021] [Indexed: 12/27/2022] Open
Affiliation(s)
- Sonia Do Carmo
- Department of Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Maria Grazia Spillantini
- Department of Clinical Neurosciences, Clifford Allbutt Building, University of Cambridge, Cambridge, United Kingdom
| | - A Claudio Cuello
- Department of Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.,Department of Anatomy and Cell Biology, McGill University, Montreal, QC, Canada.,Department of Pharmacology, Oxford University, Oxford, United Kingdom
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Rujeedawa T, Carrillo Félez E, Clare ICH, Fortea J, Strydom A, Rebillat AS, Coppus A, Levin J, Zaman SH. The Clinical and Neuropathological Features of Sporadic (Late-Onset) and Genetic Forms of Alzheimer's Disease. J Clin Med 2021; 10:4582. [PMID: 34640600 PMCID: PMC8509365 DOI: 10.3390/jcm10194582] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/17/2022] Open
Abstract
The purpose of this review is to compare and highlight the clinical and pathological aspects of genetic versus acquired Alzheimer's disease: Down syndrome-associated Alzheimer's disease in (DSAD) and Autosomal Dominant Alzheimer's disease (ADAD) are compared with the late-onset form of the disease (LOAD). DSAD and ADAD present in a younger population and are more likely to manifest with non-amnestic (such as dysexecutive function features) in the prodromal phase or neurological features (such as seizures and paralysis) especially in ADAD. The very large variety of mutations associated with ADAD explains the wider range of phenotypes. In the LOAD, age-associated comorbidities explain many of the phenotypic differences.
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Affiliation(s)
- Tanzil Rujeedawa
- Cambridge Intellectual & Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge CB2 8PQ, UK; (T.R.); (E.C.F.); (I.C.H.C.)
| | - Eva Carrillo Félez
- Cambridge Intellectual & Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge CB2 8PQ, UK; (T.R.); (E.C.F.); (I.C.H.C.)
| | - Isabel C. H. Clare
- Cambridge Intellectual & Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge CB2 8PQ, UK; (T.R.); (E.C.F.); (I.C.H.C.)
- Cambridgeshire and Peterborough Foundation NHS Trust, Fulbourn CB21 5EF, UK
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain;
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain
- Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, 08029 Barcelona, Spain
| | - Andre Strydom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK;
- South London and the Maudsley NHS Foundation Trust, The LonDowns Consortium, London SE5 8AZ, UK
| | | | - Antonia Coppus
- Department for Primary and Community Care, Department of Primary and Community Care (149 ELG), Radboud University Nijmegen Medical Center, P.O. Box 9101, 6525 GA Nijmegen, The Netherlands;
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, 80539 Munich, Germany;
- German Center for Neurodegenerative Diseases, Feodor-Lynen-Strasse 17, 81377 Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Strasse 17, 81377 Munich, Germany
| | - Shahid H. Zaman
- Cambridge Intellectual & Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge CB2 8PQ, UK; (T.R.); (E.C.F.); (I.C.H.C.)
- Cambridgeshire and Peterborough Foundation NHS Trust, Fulbourn CB21 5EF, UK
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O'Connor A, Karikari TK, Poole T, Ashton NJ, Lantero Rodriguez J, Khatun A, Swift I, Heslegrave AJ, Abel E, Chung E, Weston PSJ, Pavisic IM, Ryan NS, Barker S, Rossor MN, Polke JM, Frost C, Mead S, Blennow K, Zetterberg H, Fox NC. Plasma phospho-tau181 in presymptomatic and symptomatic familial Alzheimer's disease: a longitudinal cohort study. Mol Psychiatry 2021; 26:5967-5976. [PMID: 32665603 PMCID: PMC7612227 DOI: 10.1038/s41380-020-0838-x] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 06/23/2020] [Accepted: 07/02/2020] [Indexed: 01/05/2023]
Abstract
Blood biomarkers have great potential to advance clinical care and accelerate trials in Alzheimer's disease (AD). Plasma phospho-tau181 (p-tau181) is a promising blood biomarker however, it is unknown if levels increase in presymptomatic AD. Therefore, we investigated the timing of p-tau181 changes using 153 blood samples from 70 individuals in a longitudinal study of familial AD (FAD). Plasma p-tau181 was measured, using an in-house single molecule array assay. We compared p-tau181 between symptomatic carriers, presymptomatic carriers, and non-carriers, adjusting for age and sex. We examined the relationship between p-tau181 and neurofilament light and estimated years to/from symptom onset (EYO), as well as years to/from actual onset in a symptomatic subgroup. In addition, we studied associations between p-tau181 and clinical severity, as well testing for differences between genetic subgroups. Twenty-four were presymptomatic carriers (mean baseline EYO -9.6 years) while 27 were non-carriers. Compared with non-carriers, plasma p-tau181 concentration was higher in both symptomatic (p < 0.001) and presymptomatic mutation carriers (p < 0.001). Plasma p-tau181 showed considerable intra-individual variability but individual values discriminated symptomatic (AUC 0.93 [95% CI 0.85-0.98]) and presymptomatic (EYO ≥ -7 years) (AUC 0.86 [95% CI 0.72-0.94]) carriers from non-carriers of the same age and sex. From a fitted model there was evidence (p = 0.050) that p-tau181 concentrations were higher in mutation carriers than non-carriers from 16 years prior to estimated symptom onset. Our finding that plasma p-tau181 concentration is increased in symptomatic and presymptomatic FAD suggests potential utility as an easily accessible biomarker of AD pathology.
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Affiliation(s)
- Antoinette O'Connor
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Teresa Poole
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia, South London & Maudsley NHS Foundation, London, UK
| | - Juan Lantero Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Ayesha Khatun
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Imogen Swift
- UK Dementia Research Institute at UCL, London, UK
| | | | - Emily Abel
- UK Dementia Research Institute at UCL, London, UK
| | - Elisha Chung
- UK Dementia Research Institute at UCL, London, UK
| | - Philip S J Weston
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Ivanna M Pavisic
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Natalie S Ryan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Suzie Barker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Martin N Rossor
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - James M Polke
- Neurogenetics Laboratory, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
| | - Chris Frost
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Simon Mead
- National Prion Clinic, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UK
- MRC Prion Unit at UCL, UCL Institute of Prion Diseases, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, London, UK.
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK.
- UK Dementia Research Institute at UCL, London, UK.
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Provost K, La Joie R, Strom A, Iaccarino L, Edwards L, Mellinger TJ, Pham J, Baker SL, Miller BL, Jagust WJ, Rabinovici GD. Crossed cerebellar diaschisis on 18F-FDG PET: Frequency across neurodegenerative syndromes and association with 11C-PIB and 18F-Flortaucipir. J Cereb Blood Flow Metab 2021; 41:2329-2343. [PMID: 33691512 PMCID: PMC8393295 DOI: 10.1177/0271678x211001216] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 02/08/2021] [Accepted: 02/15/2021] [Indexed: 11/16/2022]
Abstract
We used 18F-FDG-PET to investigate the frequency of crossed cerebellar diaschisis (CCD) in 197 patients with various syndromes associated with neurodegenerative diseases. In a subset of 117 patients, we studied relationships between CCD and cortical asymmetry of Alzheimer's pathology (β-amyloid (11C-PIB) and tau (18F-Flortaucipir)). PET images were processed using MRIs to derive parametric SUVR images and define regions of interest. Indices of asymmetry were calculated in the cerebral cortex, basal ganglia and cerebellar cortex. Across all patients, cerebellar 18F-FDG asymmetry was associated with reverse asymmetry of 18F-FDG in the cerebral cortex (especially frontal and parietal areas) and basal ganglia. Based on our operational definition (cerebellar asymmetry >3% with contralateral supratentorial hypometabolism), significant CCD was present in 47/197 (24%) patients and was most frequent in corticobasal syndrome and semantic and logopenic variants of primary progressive aphasia. In β-amyloid-positive patients, mediation analyses showed that 18F-Flortaucipir cortical asymmetry was associated with cerebellar 18F-FDG asymmetry, but that cortical 18F-FDG asymmetry mediated this relationship. Analysis of 18F-FDG-SUVR values suggested that CCD might also occur in the absence of frank cerebellar 18F-FDG asymmetry due to symmetrical supratentorial degeneration resulting in a bilateral diaschisis process.
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Affiliation(s)
- Karine Provost
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Taylor J Mellinger
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | | | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - William J Jagust
- Lawrence Berkeley National Laboratory, Berkeley, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Lawrence Berkeley National Laboratory, Berkeley, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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69
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Schwarz CG, Therneau TM, Weigand SD, Gunter JL, Lowe VJ, Przybelski SA, Senjem ML, Botha H, Vemuri P, Kantarci K, Boeve BF, Whitwell JL, Josephs KA, Petersen RC, Knopman DS, Jack CR. Selecting software pipelines for change in flortaucipir SUVR: Balancing repeatability and group separation. Neuroimage 2021; 238:118259. [PMID: 34118395 PMCID: PMC8407434 DOI: 10.1016/j.neuroimage.2021.118259] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/26/2021] [Accepted: 06/08/2021] [Indexed: 12/11/2022] Open
Abstract
Since tau PET tracers were introduced, investigators have quantified them using a wide variety of automated methods. As longitudinal cohort studies acquire second and third time points of serial within-person tau PET data, determining the best pipeline to measure change has become crucial. We compared a total of 415 different quantification methods (each a combination of multiple options) according to their effects on a) differences in annual SUVR change between clinical groups, and b) longitudinal measurement repeatability as measured by the error term from a linear mixed-effects model. Our comparisons used MRI and Flortaucipir scans of 97 Mayo Clinic study participants who clinically either: a) were cognitively unimpaired, or b) had cognitive impairments that were consistent with Alzheimer's disease pathology. Tested methods included cross-sectional and longitudinal variants of two overarching pipelines (FreeSurfer 6.0, and an in-house pipeline based on SPM12), three choices of target region (entorhinal, inferior temporal, and a temporal lobe meta-ROI), five types of partial volume correction (PVC) (none, two-compartment, three-compartment, geometric transfer matrix (GTM), and a tau-specific GTM variant), seven choices of reference region (cerebellar crus, cerebellar gray matter, whole cerebellum, pons, supratentorial white matter, eroded supratentorial WM, and a composite of eroded supratentorial WM, pons, and whole cerebellum), two choices of region masking (GM or GM and WM), and two choices of statistic (voxel-wise mean vs. median). Our strongest findings were: 1) larger temporal-lobe target regions greatly outperformed entorhinal cortex (median sample size estimates based on a hypothetical clinical trial were 520-526 vs. 1740); 2) longitudinal processing pipelines outperformed cross-sectional pipelines (median sample size estimates were 483 vs. 572); and 3) reference regions including supratentorial WM outperformed traditional cerebellar and pontine options (median sample size estimates were 370 vs. 559). Altogether, our results favored longitudinally SUVR methods and a temporal-lobe meta-ROI that includes adjacent (juxtacortical) WM, a composite reference region (eroded supratentorial WM + pons + whole cerebellum), 2-class voxel-based PVC, and median statistics.
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Affiliation(s)
- Christopher G Schwarz
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA.
| | - Terry M Therneau
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA
| | - Scott A Przybelski
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Jennifer L Whitwell
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic and Foundation, 200 First Street SW, Rochester 55905, MN, USA
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70
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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71
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Strom A, Iaccarino L, Edwards L, Lesman-Segev OH, Soleimani-Meigooni DN, Pham J, Baker SL, Landau S, Jagust WJ, Miller BL, Rosen HJ, Gorno-Tempini ML, Rabinovici GD, La Joie R. Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease. Brain 2021; 145:713-728. [PMID: 34373896 PMCID: PMC9014741 DOI: 10.1093/brain/awab294] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 07/09/2021] [Accepted: 07/21/2021] [Indexed: 11/14/2022] Open
Abstract
Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.
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Affiliation(s)
- Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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72
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Kim HR, Jang JH, Ham H, Choo SH, Park J, Kang SH, Hwangbo S, Jang H, Na DL, Seo SW, Baek JH, Kim HJ. A Case of Early-Onset Alzheimer's Disease Mimicking Schizophrenia in a Patient with Presenilin 1 Mutation (S170P). J Alzheimers Dis 2021; 83:1025-1031. [PMID: 34366354 DOI: 10.3233/jad-210650] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Atypical psychological symptoms frequently occur in early-onset Alzheimer's disease (EOAD), which makes it difficult to differentiate it from other psychiatric disorders. We report the case of a 28-year-old woman with EOAD, carrying a presenilin-1 mutation (S170P), who was initially misdiagnosed with schizophrenia because of prominent psychiatric symptoms in the first 1-2 years of the disease. Amyloid-β positron emission tomography (PET) showed remarkably high tracer uptake in the striatum and thalamus. Tau PET showed widespread cortical uptake and relatively low uptake in the subcortical and medial temporal regions. Our case advocates for considering EOAD diagnosis for young patients with psychiatric and atypical cognitive symptoms.
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Affiliation(s)
- Hang-Rai Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea.,Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Ja Hyun Jang
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Honggi Ham
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
| | - Seung Ho Choo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeongho Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Song Hwangbo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.,Stem Cell & Regenerative Medicine Institute, Samsung Medical Center, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Ji Hyun Baek
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Samsung Medical Center, Seoul, Republic of Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
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73
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Fagan AM, Henson RL, Li Y, Boerwinkle AH, Xiong C, Bateman RJ, Goate A, Ances BM, Doran E, Christian BT, Lai F, Rosas HD, Schupf N, Krinsky-McHale S, Silverman W, Lee JH, Klunk WE, Handen BL, Allegri RF, Chhatwal JP, Day GS, Graff-Radford NR, Jucker M, Levin J, Martins RN, Masters CL, Mori H, Mummery CJ, Niimi Y, Ringman JM, Salloway S, Schofield PR, Shoji M, Lott IT. Comparison of CSF biomarkers in Down syndrome and autosomal dominant Alzheimer's disease: a cross-sectional study. Lancet Neurol 2021; 20:615-626. [PMID: 34302786 PMCID: PMC8496347 DOI: 10.1016/s1474-4422(21)00139-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 04/21/2021] [Accepted: 04/29/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND Due to trisomy of chromosome 21 and the resultant extra copy of the amyloid precursor protein gene, nearly all adults with Down syndrome develop Alzheimer's disease pathology by the age of 40 years and are at high risk for dementia given their increased life expectancy compared with adults with Down syndrome in the past. We aimed to compare CSF biomarker patterns in Down syndrome with those of carriers of autosomal dominant Alzheimer's disease mutations to enhance our understanding of disease mechanisms in these two genetic groups at high risk for Alzheimer's disease. METHODS We did a cross-sectional study using data from adults enrolled in the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study, a multisite longitudinal study of Alzheimer's disease in Down syndrome, as well as a cohort of carriers of autosomal dominant Alzheimer's disease mutations and non-carrier sibling controls enrolled in the Dominantly Inherited Alzheimer Network (DIAN) study. For ABC-DS, participants with baseline CSF, available clinical diagnosis, and apolipoprotein E genotype as of Jan 31, 2019, were included in the analysis. DIAN participants with baseline CSF, available clinical diagnosis, and apolipoprotein E genotype as of June 30, 2018, were evaluated as comparator groups. CSF samples obtained from adults with Down syndrome, similarly aged carriers of autosomal dominant Alzheimer's disease mutations, and non-carrier siblings (aged 30-61 years) were analysed for markers of amyloid β (Aβ1-40, Aβ1-42); tau phosphorylated at threonine 181-related processes; neuronal, axonal, or synaptic injury (total tau, visinin-like protein 1, neurofilament light chain [NfL], synaptosomal-associated protein 25); and astrogliosis and neuroinflammation (chitinase-3-like protein 1 [YKL-40]) via immunoassay. Biomarker concentrations were compared as a function of dementia status (asymptomatic or symptomatic), and linear regression was used to evaluate and compare the relationship between biomarker concentrations and age among groups. FINDINGS We assessed CSF samples from 341 individuals (178 [52%] women, 163 [48%] men, aged 30-61 years). Participants were adults with Down syndrome (n=41), similarly aged carriers of autosomal dominant Alzheimer's disease mutations (n=192), and non-carrier siblings (n=108). Individuals with Down syndrome had patterns of Alzheimer's disease-related CSF biomarkers remarkably similar to carriers of autosomal dominant Alzheimer's disease mutations, including reductions (all p<0·0080) in Aβ1-42 to Aβ1-40 ratio and increases in markers of phosphorylated tau-related processes; neuronal, axonal, and synaptic injury (p<0·080); and astrogliosis and neuroinflammation, with greater degrees of abnormality in individuals with dementia. Differences included overall higher concentrations of Aβ and YKL-40 (both p<0·0008) in Down syndrome and potential elevations in CSF tau (p<0·010) and NfL (p<0·0001) in the asymptomatic stage (ie, no dementia symptoms). FUNDING National Institute on Aging, Eunice Kennedy Shriver National Institute of Child Health and Human Development, German Center for Neurodegenerative Diseases, and Japan Agency for Medical Research and Development.
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Affiliation(s)
- Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA.
| | - Rachel L Henson
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Anna H Boerwinkle
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Alison Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Eric Doran
- Department of Pediatrics, UC Irvine School of Medicine, Irvine, CA, USA
| | - Bradley T Christian
- Department of Medical Physics, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Florence Lai
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - H Diana Rosas
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Nicole Schupf
- Department of Epidemiology, Columbia University Irving Medical Center, New York, NY, USA; Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Sharon Krinsky-McHale
- New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA
| | - Wayne Silverman
- Department of Pediatrics, UC Irvine School of Medicine, Irvine, CA, USA
| | - Joseph H Lee
- Department of Epidemiology, Columbia University Irving Medical Center, New York, NY, USA; Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Benjamin L Handen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ricardo F Allegri
- Department of Cognitive Neurology, Instituto Neurologico Fleni, Buenos Aires, Argentina
| | - Jasmeer P Chhatwal
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, USA
| | | | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases, Tübingen, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, German Center for Neurodegenerative Diseases, Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Ralph N Martins
- School of Medical Health and Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Colin L Masters
- Florey Institute, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Abenoku, Osaka, Japan
| | - Catherine J Mummery
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Yoshiki Niimi
- Unit for Early and Exploratory Clinical Development, University of Tokyo, Tokyo, Japan
| | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stephen Salloway
- Memory and Aging Program, Brown University, Butler Hospital, Providence, RI, USA
| | - Peter R Schofield
- Neuroscience Research Australia, School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Mikio Shoji
- Geriatrics Research Institute and Hospital, Maebashi, Gunma, Japan
| | - Ira T Lott
- Department of Pediatrics, UC Irvine School of Medicine, Irvine, CA, USA
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Ge X, Zhang D, Qiao Y, Zhang J, Xu J, Zheng Y. Association of Tau Pathology With Clinical Symptoms in the Subfields of Hippocampal Formation. Front Aging Neurosci 2021; 13:672077. [PMID: 34335226 PMCID: PMC8317580 DOI: 10.3389/fnagi.2021.672077] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 05/20/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: To delineate the relationship between clinical symptoms and tauopathy of the hippocampal subfields under different amyloid statuses. Methods: One hundred and forty-three subjects were obtained from the ADNI project, including 87 individuals with normal cognition, 46 with mild cognitive impairment, and 10 with Alzheimer's disease (AD). All subjects underwent the tau PET, amyloid PET, T1W, and high-resolution T2W scans. Clinical symptoms were assessed by the Neuropsychiatric Inventory (NPI) total score and Alzheimer's Disease Assessment Scale cognition 13 (ADAS-cog-13) total score, comprising memory and executive function scores. The hippocampal subfields including Cornu Ammonis (CA1-3), subiculum (Sub), and dentate gyrus (DG), as well as the adjacent para-hippocampus (PHC) and entorhinal cortex (ERC), were segmented automatically using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. The relationship between tauopathy/volume of the hippocampal subfields and assessment scores was calculated using partial correlation analysis under different amyloid status, by controlling age, gender, education, apolipoprotein E (APOE) allele ɛ4 carrier status, and, time interval between the acquisition time of tau PET and amyloid PET scans. Results: Compared with amyloid negative (A-) group, individuals from amyloid positive (A+) group are more impaired based on the Mini-mental State Examination (MMSE; p = 3.82e-05), memory (p = 6.30e-04), executive function (p = 0.0016), and ADAS-cog-13 scores (p = 5.11e-04). Significant decrease of volume (CA1, DG, and Sub) and increase of tau deposition (CA1, Sub, ERC, and PHC) of the hippocampal subfields of both hemispheres were observed for the A+ group compared to the A- group. Tauopathy of ERC is significantly associated with memory score for the A- group, and the associated regions spread into Sub and PHC for the A+ group. The relationship between the impairment of behavior or executive function and tauopathy of the hippocampal subfield was discovered within the A+ group. Leftward asymmetry was observed with the association between assessment scores and tauopathy of the hippocampal subfield, which is more prominent for the NPI score for the A+ group. Conclusion: The associations of tauopathy/volume of the hippocampal subfields with clinical symptoms provide additional insight into the understanding of local changes of the human HF during the AD continuum and can be used as a reference for future studies.
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Affiliation(s)
- Xinting Ge
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- School of Medical Imaging, Xuzhou Medical University, Xuzhou, China
| | - Dan Zhang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Yuchuan Qiao
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Jiong Zhang
- Laboratory of Neuro Imaging (LONI), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Junhai Xu
- College of Intelligence and Computing, Tianjin Key Lab of Cognitive Computing and Application, Tianjin University, Tianjin, China
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
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Keret O, Staffaroni AM, Ringman JM, Cobigo Y, Goh SM, Wolf A, Allen IE, Salloway S, Chhatwal J, Brickman AM, Reyes‐Dumeyer D, Bateman RJ, Benzinger TL, Morris JC, Ances BM, Joseph‐Mathurin N, Perrin RJ, Gordon BA, Levin J, Vöglein J, Jucker M, la Fougère C, Martins RN, Sohrabi HR, Taddei K, Villemagne VL, Schofield PR, Brooks WS, Fulham M, Masters CL, Ghetti B, Saykin AJ, Jack CR, Graff‐Radford NR, Weiner M, Cash DM, Allegri RF, Chrem P, Yi S, Miller BL, Rabinovici GD, Rosen HJ. Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12197. [PMID: 34258377 PMCID: PMC8256623 DOI: 10.1002/dad2.12197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 04/13/2021] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. METHODS We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. RESULTS Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. DISCUSSION Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.
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Affiliation(s)
- Ophir Keret
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Adam M. Staffaroni
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - John M. Ringman
- Alzheimer's Disease Research Center, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Yann Cobigo
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Sheng‐Yang M. Goh
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Amy Wolf
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Isabel Elaine Allen
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Stephen Salloway
- Warren Alpert Medical SchoolBrown UniversityProvidenceRhode IslandUSA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School BostonBostonMassachusettsUSA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
| | - Dolly Reyes‐Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainColumbia UniversityNew YorkNew YorkUSA
| | - Randal J. Bateman
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Tammie L.S. Benzinger
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
| | - John C. Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Beau M. Ances
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Nelly Joseph‐Mathurin
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Richard J. Perrin
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Brian A. Gordon
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
- Department of RadiologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Neuropathology, Department of Pathology & ImmunologyWashington University School of MedicineSt. LouisMissouriUSA
- Division of Biostatistics, Department of PsychiatryWashington University in St. Louis School of MedicineSt. LouisMissouriUSA
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
- Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
| | - Christian la Fougère
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
- Institute for Nuclear Medicine and Clinical Molecular ImagingEberhard Karls UniversityTübingenGermany
| | - Ralph N. Martins
- Department of Biomedical SciencesMacquarie UniversityNorth RydeNew South WalesAustralia
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- School of Psychiatry and Clinical NeurosciencesUniversity of Western AustraliaCrawleyWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
- The Cooperative Research Centre for Mental HealthCarlton SouthVictoriaAustralia
| | - Hamid R. Sohrabi
- Department of Biomedical SciencesMacquarie UniversityNorth RydeNew South WalesAustralia
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- School of Psychiatry and Clinical NeurosciencesUniversity of Western AustraliaCrawleyWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
- The Cooperative Research Centre for Mental HealthCarlton SouthVictoriaAustralia
| | - Kevin Taddei
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health SciencesEdith Cowan UniversityJoondalupWestern AustraliaAustralia
- Australian Alzheimer's Research FoundationNedlandsWestern AustraliaAustralia
| | - Victor L. Villemagne
- Department of Molecular Imaging and TherapyAustin HealthMelbourneVictoriaAustralia
| | - Peter R. Schofield
- Neuroscience Research Australia, RandwickSydneyNew South WalesAustralia
- School of Medical SciencesUNSW SydneySydneyNew South WalesAustralia
| | - William S. Brooks
- Neuroscience Research Australia, RandwickSydneyNew South WalesAustralia
- Prince of Wales Hospital Clinical SchoolUNSW SydneySydneyNew South WalesAustralia
| | - Michael Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Sydney Medical SchoolUniversity of SydneyCamperdownNew South WalesAustralia
| | - Colin L. Masters
- The Florey InstituteUniversity of MelbourneParkvilleVictoriaAustralia
| | - Bernardino Ghetti
- Department of Pathology and Laboratory MedicineIndiana University School of MedicineIndianapolisIndianaUSA
| | - Andrew J. Saykin
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of RadiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | | | | | - Michael Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - David M. Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Ricardo F. Allegri
- Department of Cognitive Neurology, Neuropsychiatry and NeuropsychologyInstituto de InvestigacionesNeurológicas FLENIBuenos AiresArgentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Neuropsychiatry and NeuropsychologyInstituto de InvestigacionesNeurológicas FLENIBuenos AiresArgentina
| | - Su Yi
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Bruce L. Miller
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Howard J. Rosen
- Global Brain Health InstituteUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Neurology, Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
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A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer's disease. Nat Med 2021; 27:1187-1196. [PMID: 34155411 PMCID: PMC8988051 DOI: 10.1038/s41591-021-01369-8] [Citation(s) in RCA: 176] [Impact Index Per Article: 58.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/23/2021] [Indexed: 02/06/2023]
Abstract
Dominantly inherited Alzheimer's disease (DIAD) causes predictable biological changes decades before the onset of clinical symptoms, enabling testing of interventions in the asymptomatic and symptomatic stages to delay or slow disease progression. We conducted a randomized, placebo-controlled, multi-arm trial of gantenerumab or solanezumab in participants with DIAD across asymptomatic and symptomatic disease stages. Mutation carriers were assigned 3:1 to either drug or placebo and received treatment for 4-7 years. The primary outcome was a cognitive end point; secondary outcomes included clinical, cognitive, imaging and fluid biomarker measures. Fifty-two participants carrying a mutation were assigned to receive gantenerumab, 52 solanezumab and 40 placebo. Both drugs engaged their Aβ targets but neither demonstrated a beneficial effect on cognitive measures compared to controls. The solanezumab-treated group showed a greater cognitive decline on some measures and did not show benefits on downstream biomarkers. Gantenerumab significantly reduced amyloid plaques, cerebrospinal fluid total tau, and phospho-tau181 and attenuated increases of neurofilament light chain. Amyloid-related imaging abnormalities edema was observed in 19.2% (3 out of 11 were mildly symptomatic) of the gantenerumab group, 2.5% of the placebo group and 0% of the solanezumab group. Gantenerumab and solanezumab did not slow cognitive decline in symptomatic DIAD. The asymptomatic groups showed no cognitive decline; symptomatic participants had declined before reaching the target doses.
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Ossenkoppele R, Leuzy A, Cho H, Sudre CH, Strandberg O, Smith R, Palmqvist S, Mattsson-Carlgren N, Olsson T, Jögi J, Stormrud E, Ryu YH, Choi JY, Boxer AL, Gorno-Tempini ML, Miller BL, Soleimani-Meigooni D, Iaccarino L, La Joie R, Borroni E, Klein G, Pontecorvo MJ, Devous MD, Villeneuve S, Lyoo CH, Rabinovici GD, Hansson O. The impact of demographic, clinical, genetic, and imaging variables on tau PET status. Eur J Nucl Med Mol Imaging 2021; 48:2245-2258. [PMID: 33215319 PMCID: PMC8131404 DOI: 10.1007/s00259-020-05099-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 10/27/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI) are tau PET-negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET-positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. METHODS We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. RESULTS Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. CONCLUSION We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.
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Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Antoine Leuzy
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Centre for Medical Image Computing, Department of Medical Physics, University College London, London, UK
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | | | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | - Tomas Olsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
| | - Erik Stormrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jae Yong Choi
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
- Division of applied RI, Korea Institute Radiological and Medical Sciences, Seoul, South Korea
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | - Maria L Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | - David Soleimani-Meigooni
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | - Leonardo Iaccarino
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, USA
| | | | | | | | | | - Sylvia Villeneuve
- Departments of Psychiatry and Neurology & Neurosurgery, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Gil D Rabinovici
- F. Hoffmann-La Roche Ltd, Basel, Switzerland
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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Aghakhanyan G, Saur D, Rullmann M, Weise CM, Schroeter ML, Marek K, Jamra RA, Tiepolt S, Strauss M, Scherlach C, Hoffmann KT, Sabri O, Classen J, Barthel H. PET/MRI Delivers Multimodal Brain Signature in Alzheimer's Disease with De Novo PSEN1 Mutation. Curr Alzheimer Res 2021; 18:178-184. [PMID: 33855944 DOI: 10.2174/1567205018666210414111536] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 02/27/2021] [Accepted: 03/17/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Little is known so far about the brain phenotype and the spatial interplay of different Alzheimer's disease (AD) biomarkers with structural and functional brain connectivity in the early phase of autosomal-dominant AD (ADAD). Multimodal PET/MRI might be suitable to fill this gap. MATERIAL AND METHODS We presented a 31-year-old male patient without a family history of dementia with progressive worsening of memory and motor function. Two separate sessions of 3T PET/MRI acquisitions were arranged with the ß-amyloid tracer [18F]Florbetaben and the secondgeneration tau tracer [18F]PI-2620. Simultaneously acquired MRI consisted of high-resolution 3D T1, diffusion-tensor imaging (DTI), and resting-state fMRI. PET/MRI data were compared with ten age-matched healthy controls. RESULTS Widespread β-amyloid depositions were found in cortical regions, and striatum (Thal stage III) along with tau pathology restricted to the mesial-temporal structures (Braak stage III/IV). Volumetric/shape analysis of subcortical structures revealed atrophy of the hippocampal-amygdala complex. In addition, cortical thinning was detected in the right middle temporal pole. Alterations of multiple DTI indices were noted in the major white matter fiber bundles, together with disruption of default mode and sensory-motor network functional connectivity. Molecular genetic analysis by next-generation sequencing revealed a heterozygote missense pathogenic variant of the PSEN1 (Met233Val). CONCLUSION Multimodal PET/MR imaging is able to deliver, in a one-stop-shop approach, an array of molecular, structural and functional brain information in AD due to de novo pathogenic variant, which can be studied for spatial interplay and might provide a rationale for initiating anti- amyloid/tau therapeutic approaches.
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Affiliation(s)
| | - Dorothee Saur
- Department of Neurology, University of Leipzig, Leipzig, Germany
| | - Michael Rullmann
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | | | - Matthias L Schroeter
- Max Planck Institute for Human Cognitive and Brain Sciences, Clinic for Cognitive Neurology, University of Leipzig, Leipzig, Germany
| | - Ken Marek
- Invicro, New Haven, CT, United States
| | - Rami Abou Jamra
- Institute for Human Genetics, University Hospital Leipzig, Leipzig, Germany
| | - Solveig Tiepolt
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Maria Strauss
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Cordula Scherlach
- Department of Neuroradiology, University Hospital Leipzig, Leipzig, Germany
| | | | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Joseph Classen
- Department of Neurology, University of Leipzig, Leipzig, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
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Novak P, Kovacech B, Katina S, Schmidt R, Scheltens P, Kontsekova E, Ropele S, Fialova L, Kramberger M, Paulenka-Ivanovova N, Smisek M, Hanes J, Stevens E, Kovac A, Sutovsky S, Parrak V, Koson P, Prcina M, Galba J, Cente M, Hromadka T, Filipcik P, Piestansky J, Samcova M, Prenn-Gologranc C, Sivak R, Froelich L, Fresser M, Rakusa M, Harrison J, Hort J, Otto M, Tosun D, Ondrus M, Winblad B, Novak M, Zilka N. ADAMANT: a placebo-controlled randomized phase 2 study of AADvac1, an active immunotherapy against pathological tau in Alzheimer's disease. NATURE AGING 2021; 1:521-534. [PMID: 37117834 DOI: 10.1038/s43587-021-00070-2] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 04/28/2021] [Indexed: 04/30/2023]
Abstract
Alzheimer's disease (AD) pathology is partly characterized by accumulation of aberrant forms of tau protein. Here we report the results of ADAMANT, a 24-month double-blinded, parallel-arm, randomized phase 2 multicenter placebo-controlled trial of AADvac1, an active peptide vaccine designed to target pathological tau in AD (EudraCT 2015-000630-30). Eleven doses of AADvac1 were administered to patients with mild AD dementia at 40 μg per dose over the course of the trial. The primary objective was to evaluate the safety and tolerability of long-term AADvac1 treatment. The secondary objectives were to evaluate immunogenicity and efficacy of AADvac1 treatment in slowing cognitive and functional decline. A total of 196 patients were randomized 3:2 between AADvac1 and placebo. AADvac1 was safe and well tolerated (AADvac1 n = 117, placebo n = 79; serious adverse events observed in 17.1% of AADvac1-treated individuals and 24.1% of placebo-treated individuals; adverse events observed in 84.6% of AADvac1-treated individuals and 81.0% of placebo-treated individuals). The vaccine induced high levels of IgG antibodies. No significant effects were found in cognitive and functional tests on the whole study sample (Clinical Dementia Rating-Sum of the Boxes scale adjusted mean point difference -0.360 (95% CI -1.306, 0.589)), custom cognitive battery adjusted mean z-score difference of 0.0008 (95% CI -0.169, 0.172). We also present results from exploratory and post hoc analyses looking at relevant biomarkers and clinical outcomes in specific subgroups. Our results show that AADvac1 is safe and immunogenic, but larger stratified studies are needed to better evaluate its potential clinical efficacy and impact on disease biomarkers.
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Affiliation(s)
- Petr Novak
- AXON Neuroscience CRM Services SE, Bratislava, Slovakia.
| | | | | | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University Graz, Graz, Austria
| | - Philip Scheltens
- Alzheimer Center, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | | | - Stefan Ropele
- Clinical Division of General Neurology, Department of Neurology, Medical University Graz, Graz, Austria
| | | | - Milica Kramberger
- Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | | | | | - Jozef Hanes
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
| | - Eva Stevens
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
| | - Andrej Kovac
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
| | - Stanislav Sutovsky
- 1st Department of Neurology, Faculty of Medicine, Comenius University and University Hospital, Bratislava, Slovakia
| | | | - Peter Koson
- AXON Neuroscience CRM Services SE, Bratislava, Slovakia
| | - Michal Prcina
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
| | | | - Martin Cente
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
| | - Tomas Hromadka
- Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
| | | | | | - Maria Samcova
- AXON Neuroscience CRM Services SE, Bratislava, Slovakia
| | | | - Roman Sivak
- AXON Neuroscience CRM Services SE, Bratislava, Slovakia
| | - Lutz Froelich
- Department of Geriatric Psychiatry, Zentralinstitut für Seelische Gesundheit, Medical Faculty Mannheim University of Heidelberg, Heidelberg, Germany
| | | | - Martin Rakusa
- Department of Neurological Diseases, University Medical Centre Maribor, Maribor, Slovenia
| | - John Harrison
- Alzheimer Center, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Charles University, 2nd Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
| | - Markus Otto
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Matej Ondrus
- AXON Neuroscience CRM Services SE, Bratislava, Slovakia
| | - Bengt Winblad
- Division of Neurogeriatrics, Center for Alzheimer Research, Karolinska Institutet, Solna, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | | | - Norbert Zilka
- AXON Neuroscience R&D Services SE, Bratislava, Slovakia
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80
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Pichet Binette A, Theaud G, Rheault F, Roy M, Collins DL, Levin J, Mori H, Lee JH, Farlow MR, Schofield P, Chhatwal JP, Masters CL, Benzinger T, Morris J, Bateman R, Breitner JC, Poirier J, Gonneaud J, Descoteaux M, Villeneuve S. Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease. eLife 2021; 10:62929. [PMID: 33983116 PMCID: PMC8169107 DOI: 10.7554/elife.62929] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 05/12/2021] [Indexed: 12/12/2022] Open
Abstract
Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.
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Affiliation(s)
- Alexa Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - François Rheault
- Electrical Engineering, Vanderbilt University, Nashville, United States
| | - Maggie Roy
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Osaka, Japan
| | - Jae Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | | | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, UNSW Sydney, Sydney, Australia
| | - Jasmeer P Chhatwal
- Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Tammie Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - Randall Bateman
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Cs Breitner
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Judes Poirier
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Julie Gonneaud
- Douglas Mental Health University Institute, Montreal, Canada.,Normandie Univ, UNICAEN, INSERM, U1237, Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Sylvia Villeneuve
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
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81
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Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer's disease. Alzheimers Dement 2021; 17:1998-2008. [PMID: 33984177 DOI: 10.1002/alz.12356] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/22/2021] [Accepted: 03/28/2021] [Indexed: 11/07/2022]
Abstract
The recent development of several tau positron emission tomography (PET) tracers represents a major milestone for the Alzheimer's disease (AD) field. These tau PET tracers bind tau neurofibrillary tangles, a key neuropathological characteristic of AD that is tightly linked to synaptic loss, brain atrophy, and cognitive decline. It is notable that these tau PET tracers show low uptake in most non-AD tauopathies and other neurodegenerative disorders, resulting in a diagnostic specificity that is superior to that of amyloid beta (Aβ) PET and biofluid markers, especially at an older age when incidental Aβ pathology is common. Furthermore, tau PET tracers diagnostically outperform widely used MRI markers. Given its excellent diagnostic performance due to the combination of high sensitivity and specificity for detecting tau pathology in AD dementia, we hypothesize that tau PET can become an important diagnostic tool in specialized clinics for the differential diagnosis of dementia syndromes where AD is among the major possible underlying diseases.
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Affiliation(s)
- Rik Ossenkoppele
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Oskar Hansson
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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82
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Guzmán-Vélez E, Zetterberg H, Fox-Fuller JT, Vila-Castelar C, Sanchez JS, Baena A, Garcia-Ospina G, Aguillon D, Pardilla-Delgado E, Gatchel J, Sperling RA, Johnson K, Reiman EM, Blennow K, Lopera F, Quiroz YT. Associations between plasma neurofilament light, in vivo brain pathology, and cognition in non-demented individuals with autosomal-dominant Alzheimer's disease. Alzheimers Dement 2021; 17:813-821. [PMID: 33527648 PMCID: PMC8158654 DOI: 10.1002/alz.12248] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/20/2020] [Accepted: 10/29/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Neurofilament light (NfL) is a promising biomarker of early neurodegeneration in Alzheimer's disease (AD). We examined whether plasma NfL was associated with in vivo amyloid beta and tau, and cognitive performance in non-demented presenilin-1 (PSEN1) E280A mutation carriers. METHODS Twenty-five mutation carriers and 19 non-carriers (age range: 28 to 49 years) were included in this study. Participants underwent 11C Pittsburgh compound B (PiB)-PET (positron emission tomography), flortaucipir-PET, blood sampling, and cognitive testing. RESULTS Mutation carriers exhibited higher plasma NfL levels than non-carriers. In carriers, higher NfL levels were related to greater regional tau burden and worse cognition, but not amyloid beta load. When we adjusted for age, a proxy of disease progression, elevated plasma NfL levels were only correlated with worse memory recall. CONCLUSIONS Findings support an association between plasma NfL, cognition, and tau pathology in non-demented individuals at genetic risk for developing AD dementia. Plasma NfL may be useful for selecting individuals at increased risk and tracking disease progression in AD.
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Affiliation(s)
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal Campus, Sweden
- UK Dementia Research Institute at UCL, London, United Kingdom
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
| | - Joshua T. Fox-Fuller
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | | | - Justin S. Sanchez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ana Baena
- Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellin, Colombia
| | - Gloria Garcia-Ospina
- Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellin, Colombia
| | - David Aguillon
- Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellin, Colombia
| | | | - Jennifer Gatchel
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Division of Geriatric Psychiatry and Psychiatric Neurotherapeutics, McLean Hospital, Belmont, MA, USA
| | - Reisa A. Sperling
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Eric M. Reiman
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
- University of Arizona, Phoenix, AZ, USA
- Arizona State University, Phoenix, AZ, USA
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal Campus, Sweden
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellin, Colombia
| | - Yakeel T. Quiroz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Grupo de Neurociencias de Antioquia of Universidad de Antioquia, Medellin, Colombia
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83
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Horie K, Barthélemy NR, Sato C, Bateman RJ. CSF tau microtubule binding region identifies tau tangle and clinical stages of Alzheimer's disease. Brain 2021; 144:515-527. [PMID: 33283854 DOI: 10.1093/brain/awaa373] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 08/08/2020] [Accepted: 08/19/2020] [Indexed: 12/14/2022] Open
Abstract
Tau is a microtubule associated protein in the brain that aggregates in Alzheimer's disease to form pathological tangles and neurites. Insoluble tau aggregates composed of the microtubule binding region (MTBR) of tau are highly associated with the cognitive and clinical symptoms of Alzheimer's disease. In contrast, levels of soluble forms of tau, such as CSF total tau and phosphorylated tau-181 and tau-217, increase prior to tau aggregation in Alzheimer's disease, but these biomarkers do not measure the MTBR of tau. Thus, how CSF MTBR-tau is altered in Alzheimer's disease remains unclear. In this study, we used sequential immunoprecipitation and chemical extraction methods followed by mass spectrometry to analyse MTBR-tau species in Alzheimer's disease and control CSF. We quantified MTBR-tau-specific regions in the CSF and identified that species containing the region beginning at residue 243 were the most highly correlated with tau PET and cognitive measures. This finding suggests that CSF level of tau species containing the upstream region of MTBR may reflect changes in tau pathology that occur in Alzheimer's disease and could serve as biomarkers to stage Alzheimer's disease and track the development of tau-directed therapeutics.
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Affiliation(s)
- Kanta Horie
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicolas R Barthélemy
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Chihiro Sato
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.,Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
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84
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Buckley RF. Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease. Neurotherapeutics 2021; 18:709-727. [PMID: 33782864 PMCID: PMC8423933 DOI: 10.1007/s13311-021-01026-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 12/25/2022] Open
Abstract
Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.
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Affiliation(s)
- Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital & Brigham and Women's, Harvard Medical School, Boston, MA, USA.
- Melbourne School of Psychological Sciences and Florey Institutes, University of Melbourne, Melbourne, VIC, Australia.
- Department of Neurology, Massachusetts General Hospital, 149 13th St, Charlestown, MA, 02129, USA.
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85
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Montal V, Vilaplana E, Pegueroles J, Bejanin A, Alcolea D, Carmona-Iragui M, Clarimón J, Levin J, Cruchaga C, Graff-Radford NR, Noble JM, Lee JH, Allegri R, Karch CM, Laske C, Schofield P, Salloway S, Ances B, Benzinger T, McDale E, Bateman R, Blesa R, Sánchez-Valle R, Lleó A, Fortea J. Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease. Alzheimers Dement 2021; 17:618-628. [PMID: 33196147 PMCID: PMC8043974 DOI: 10.1002/alz.12224] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/20/2020] [Accepted: 10/09/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials. METHODS In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network. RESULTS In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations. DISCUSSION These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.
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Affiliation(s)
- Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alex Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - María Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
| | - Jordi Clarimón
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | | | - James M Noble
- Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, BuenosAires, Argentina
| | - Celeste M. Karch
- Department of Psychiatry, Washington University School of Medicine, Saint Lous, MO, USA
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Stephen Salloway
- Neurology and the Memory and Aging Program, Butler Hospital, Providence, RI, USA
| | - Beau Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Tammie Benzinger
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Eric McDale
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Randall Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Raquel Sánchez-Valle
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
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86
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Stefanovski L, Meier JM, Pai RK, Triebkorn P, Lett T, Martin L, Bülau K, Hofmann-Apitius M, Solodkin A, McIntosh AR, Ritter P. Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain. Front Neuroinform 2021; 15:630172. [PMID: 33867964 PMCID: PMC8047422 DOI: 10.3389/fninf.2021.630172] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 03/08/2021] [Indexed: 12/18/2022] Open
Abstract
Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.
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Affiliation(s)
- Leon Stefanovski
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Jil Mona Meier
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Roopa Kalsank Pai
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Paul Triebkorn
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France
| | - Tristram Lett
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Leon Martin
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Konstantin Bülau
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Martin Hofmann-Apitius
- Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany
| | - Ana Solodkin
- Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States
| | | | - Petra Ritter
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
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87
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Ayodele T, Rogaeva E, Kurup JT, Beecham G, Reitz C. Early-Onset Alzheimer's Disease: What Is Missing in Research? Curr Neurol Neurosci Rep 2021; 21:4. [PMID: 33464407 PMCID: PMC7815616 DOI: 10.1007/s11910-020-01090-y] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE OF REVIEW Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward. RECENT FINDINGS EOAD cases make up 5-10% of AD cases but only 10-15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear. While great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.
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Affiliation(s)
- Temitope Ayodele
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, 60 Leonard Avenue, Toronto, ON, M5T 0S8, Canada
| | - Jiji T Kurup
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
| | - Gary Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
| | - Christiane Reitz
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA.
- Department of Neurology, Columbia University, New York, NY, USA.
- Department of Epidemiology, Sergievsky Center, Taub Institute for Research on the Aging Brain, Columbia University, 630 W 168th Street, New York, NY, 10032, USA.
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88
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Sanchez JS, Hanseeuw BJ, Lopera F, Sperling RA, Baena A, Bocanegra Y, Aguillon D, Guzmán-Vélez E, Pardilla-Delgado E, Ramirez-Gomez L, Vila-Castelar C, Martinez JE, Fox-Fuller JT, Ramos C, Ochoa-Escudero M, Alvarez S, Jacobs HIL, Schultz AP, Gatchel JR, Becker JA, Katz SR, Mayblyum DV, Price JC, Reiman EM, Johnson KA, Quiroz YT. Longitudinal amyloid and tau accumulation in autosomal dominant Alzheimer's disease: findings from the Colombia-Boston (COLBOS) biomarker study. Alzheimers Res Ther 2021; 13:27. [PMID: 33451357 PMCID: PMC7811244 DOI: 10.1186/s13195-020-00765-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 12/26/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Neuroimaging studies of autosomal dominant Alzheimer's disease (ADAD) enable characterization of the trajectories of cerebral amyloid-β (Aβ) and tau accumulation in the decades prior to clinical symptom onset. Longitudinal rates of regional tau accumulation measured with positron emission tomography (PET) and their relationship with other biomarker and cognitive changes remain to be fully characterized in ADAD. METHODS Fourteen ADAD mutation carriers (Presenilin-1 E280A) and 15 age-matched non-carriers from the Colombian kindred underwent 2-3 sessions of Aβ (11C-Pittsburgh compound B) and tau (18F-flortaucipir) PET, structural magnetic resonance imaging, and neuropsychological evaluation over a 2-4-year follow-up period. Annualized rates of change for imaging and cognitive variables were compared between carriers and non-carriers, and relationships among baseline measurements and rates of change were assessed within carriers. RESULTS Longitudinal measurements were consistent with a sequence of ADAD-related changes beginning with Aβ accumulation (16 years prior to expected symptom onset, EYO), followed by entorhinal cortex (EC) tau (9 EYO), neocortical tau (6 EYO), hippocampal atrophy (6 EYO), and cognitive decline (4 EYO). Rates of tau accumulation among carriers were most rapid in parietal neocortex (~ 9%/year). EC tau PET signal at baseline was a significant predictor of subsequent neocortical tau accumulation and cognitive decline within carriers. CONCLUSIONS Our results are consistent with the sequence of biological changes in ADAD implied by cross-sectional studies and highlight the importance of EC tau as an early biomarker and a potential link between Aβ burden and neocortical tau accumulation in ADAD.
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Affiliation(s)
- Justin S Sanchez
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - Bernard J Hanseeuw
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia
| | - Reisa A Sperling
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hoospital, Harvard Medical School, Boston, MA, USA
| | - Ana Baena
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia
| | - Yamile Bocanegra
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia
| | - David Aguillon
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia
| | | | | | | | | | - Jairo E Martinez
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - Joshua T Fox-Fuller
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
- Boston University, Boston, MA, USA
| | - Claudia Ramos
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia
| | | | | | - Heidi I L Jacobs
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Aaron P Schultz
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - Jennifer R Gatchel
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - J Alex Becker
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | - Samantha R Katz
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | | | - Julie C Price
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
| | | | - Keith A Johnson
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hoospital, Harvard Medical School, Boston, MA, USA
| | - Yakeel T Quiroz
- Massachusetts General Hoospital, Harvard Medical School, Boston, MA, USA.
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, Colombia.
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89
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Yu L, Wen G, Zhu S, Hu X, Huang C, Yang Y. Abnormal phosphorylation of tau protein and neuroinflammation induced by laparotomy in an animal model of postoperative delirium. Exp Brain Res 2021; 239:867-880. [PMID: 33409674 DOI: 10.1007/s00221-020-06007-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 12/05/2020] [Indexed: 10/22/2022]
Abstract
Postoperative delirium (POD) is an acute neuropsychological disturbance after surgery, whose prevalence is related with advancing age. Neuroinflammation and abnormal tau phosphorylation that commonly presenting in Alzheimer's disease (AD) may contribute to the progression and duration of POD. To study the acute influence of surgery on cognitive function, wild type male C57BL/6 N mice were randomly divided into three groups: Control (CON), Laparotomy at 4 h and 24 h (LAP-4 h, LAP-24 h), then subjected to laparotomy under sevoflurane anaesthesia. The cognitive performance, peripheral and central inflammatory responses and tau phosphorylation levels were evaluated at 4 h and 24 h postoperatively. When LAP4-hrs displayed anxiety behaviors with high mRNA levels of inflammatory cytokines, such as interleukin-1β (IL-1β), IL-6, IL-8, TNF-α and MCP-1 in the liver, and IL-8 in the hippocampus, results at 24 h were different. In the liver, only IL-10 protein was obviously elevated, but in the hippocampus, both pro- and anti-inflammatory cytokines were significantly decreased whilst the elimination of anxiety. The activity of major related kinases and phosphatases was remarkably changed which may contribute to the dephosphorylated tau protein. With tremendous neuropathological changes and significant numbers of activated microglias and astrocytes observed in the sub-regions of hippocampus, the memory impairment existed at both 4 h and 24 h. Since the association of dephosphorylated tau with POD, these findings may supply novel implications for the understanding of tauopathies and as a theoretical basis for preventions from the postoperative cognitive dysfunction (POCD).
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Affiliation(s)
- Le Yu
- Department of Pharmacology, School of Basic Medical Sciences, Key Laboratory of Anti-Inflammatory and Immunopharmacology, Ministry of Education, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230001, People's Republic of China.,Department of Anesthesiology and Perioperative Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230001, People's Republic of China.,Key Laboratory of Anesthesiology and Perioperative Medicine of Anhui Higher Education Institutes, Hefei, Anhui, People's Republic of China
| | - Guanghua Wen
- Department of Pharmacology, School of Basic Medical Sciences, Key Laboratory of Anti-Inflammatory and Immunopharmacology, Ministry of Education, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230001, People's Republic of China
| | - Shoufeng Zhu
- Department of Anesthesiology and Perioperative Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230001, People's Republic of China.,Key Laboratory of Anesthesiology and Perioperative Medicine of Anhui Higher Education Institutes, Hefei, Anhui, People's Republic of China
| | - Xianwen Hu
- Department of Anesthesiology and Perioperative Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230001, People's Republic of China.,Key Laboratory of Anesthesiology and Perioperative Medicine of Anhui Higher Education Institutes, Hefei, Anhui, People's Republic of China
| | - Chunxia Huang
- Department of Anesthesiology and Perioperative Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230001, People's Republic of China. .,Key Laboratory of Anesthesiology and Perioperative Medicine of Anhui Higher Education Institutes, Hefei, Anhui, People's Republic of China.
| | - Yan Yang
- Department of Pharmacology, School of Basic Medical Sciences, Key Laboratory of Anti-Inflammatory and Immunopharmacology, Ministry of Education, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230001, People's Republic of China.
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90
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Ayton S, Bush AI. β-amyloid: The known unknowns. Ageing Res Rev 2021; 65:101212. [PMID: 33188924 DOI: 10.1016/j.arr.2020.101212] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 11/04/2020] [Accepted: 11/06/2020] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease (AD) stands out as a major disease without any form of preventative or disease modifying therapy. This is not for lack of trying. 33 phase 3 clinical trials of drugs targeting amyloid beta (Aβ) have failed to slow cognitive decline in AD. The field is at a cross-roads about whether to continue anti-Aβ therapy or more actively pursue alternative targets. With the burden of this disease to patients, families, and healthcare budgets growing yearly, the need for disease modifying AD therapies has become one of the highest priorities in all of medicine. While pathology, genetic and biochemical data offer a popular narrative for the causative role of Aβ, there are alternative explanations, and dissenting findings that, now more than ever, warrant thorough reanalysis. This review questions the major assumptions about Aβ on which therapies for AD were premised, and invites renewed interrogation into AD pathogenesis.
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Affiliation(s)
- Scott Ayton
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, 3052, Australia.
| | - Ashley I Bush
- Melbourne Dementia Research Centre, The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, 3052, Australia.
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91
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Bocanegra Y, Fox-Fuller JT, Baena A, Guzmán-Vélez E, Vila-Castelar C, Martínez J, Torrico-Teave H, Lopera F, Quiroz YT. Association Between Visual Memory and In Vivo Amyloid and Tau Pathology in Preclinical Autosomal Dominant Alzheimer's Disease. J Int Neuropsychol Soc 2021; 27:47-55. [PMID: 32762790 PMCID: PMC8101259 DOI: 10.1017/s1355617720000673] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Visual memory (ViM) declines early in Alzheimer's disease (AD). However, it is unclear whether ViM impairment is evident in the preclinical stage and relates to markers of AD pathology. We examined the relationship between ViM performance and in vivo markers of brain pathology in individuals with autosomal dominant AD (ADAD). METHODS Forty-five cognitively unimpaired individuals from a Colombian kindred with the Presenilin 1 (PSEN1) E280A ADAD mutation (19 carriers and 26 noncarriers) completed the Rey-Osterrieth Complex Figure immediate recall test, a measure of ViM. Cortical amyloid burden and regional tau deposition in the entorhinal cortex (EC) and inferior temporal cortex (IT) were measured using 11C-Pittsburgh compound B positron emission tomography (PET) and 11F-flortaucipir PET, respectively. RESULTS Cognitively unimpaired carriers and noncarriers did not differ on ViM performance. Compared to noncarriers, carriers had higher levels of cortical amyloid and regional tau in both the EC and IT. In cognitively unimpaired carriers, greater cortical amyloid burden, higher levels of regional tau, and greater age were associated with worse ViM performance. Only a moderate correlation between regional tau and ViM performance remained after adjusting for verbal memory scores. None of these correlations were observed in noncarriers. CONCLUSIONS Results suggest that AD pathology and greater age are associated with worse ViM performance in ADAD before the onset of clinical symptoms. Further investigation with larger samples and longitudinal follow-up is needed to examine the utility of ViM measures for identifying individuals at high risk of developing dementia later in life.
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Affiliation(s)
- Yamile Bocanegra
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Joshua T. Fox-Fuller
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Boston University, Boston, MA, USA
| | - Ana Baena
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Edmarie Guzmán-Vélez
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Clara Vila-Castelar
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jairo Martínez
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Heirangi Torrico-Teave
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Yakeel T. Quiroz
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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92
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Insel PS, Donohue MC, Berron D, Hansson O, Mattsson-Carlgren N. Time between milestone events in the Alzheimer's disease amyloid cascade. Neuroimage 2020; 227:117676. [PMID: 33359337 DOI: 10.1016/j.neuroimage.2020.117676] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 10/29/2020] [Accepted: 12/15/2020] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE Estimate the time-course of the spread of key pathological markers and the onset of cognitive dysfunction in Alzheimer's disease. METHODS In a cohort of 335 older adults, ranging in cognitive functioning, we estimated the time of initial changes of Aβ, tau, and decreases in cognition with respect to the time of Aβ-positivity. RESULTS Small effect sizes of change in CSF Aβ42 and regional Aβ PET were estimated to occur several decades before Aβ-positivity. Increases in CSF tau occurred 7-8 years before Aβ-positivity. Temporoparietal tau PET showed increases 4-5 years before Aβ-positivity. Subtle cognitive dysfunction was observed 4-6 years before Aβ-positivity. CONCLUSIONS Increases in tau and cognitive dysfunction occur years before commonly used thresholds for Aβ-positivity. Explicit estimates of the time for these events provide a clearer picture of the time-course of the amyloid cascade and identify potential windows for specific treatments.
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Affiliation(s)
- Philip S Insel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, United States.
| | - Michael C Donohue
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, United States
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden; Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
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93
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Chen CD, Holden TR, Gordon BA, Franklin EE, Li Y, Coble DW, Luo H, Bateman RJ, Ances BM, Perrin RJ, Benzinger TLS, Cairns NJ, Morris JC. Ante- and postmortem tau in autosomal dominant and late-onset Alzheimer's disease. Ann Clin Transl Neurol 2020; 7:2475-2480. [PMID: 33150749 PMCID: PMC7732239 DOI: 10.1002/acn3.51237] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 09/29/2020] [Accepted: 10/12/2020] [Indexed: 12/14/2022] Open
Abstract
Antemortem tau positron emission tomography imaging suggests elevated tau pathology in autosomal dominant versus late-onset Alzheimer's disease at equivalent clinical stages, but does not implicate the specific tau pathologies responsible. Here we made stereological measurements of tau neurofibrillary tangles, neuritic plaques, and neuropil threads and found compared to late-onset Alzheimer's disease, autosomal dominant Alzheimer's disease showed even greater tangle and thread burdens. Regional tau burden resembled that observed in tau imaging of a separate cohort at earlier clinical stages. Finally, our results suggest tau imaging measures total tau burden in Alzheimer's disease, composed predominantly of tangle and thread pathology.
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Affiliation(s)
- Charles D. Chen
- Mallinckrodt Institute of RadiologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Timothy R. Holden
- Department of MedicineDivision of Geriatrics and Nutritional ScienceWashington University in St. LouisSt. LouisMissouriUSA
| | - Brian A. Gordon
- Mallinckrodt Institute of RadiologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Erin E. Franklin
- Department of Pathology and ImmunologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Yan Li
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Dean W. Coble
- Division of BiostatisticsWashington University in St. LouisSt. LouisMissouriUSA
| | - Hongbo Luo
- Department of NeurologyFifth Affiliated Hospital of Zunyi Medical UniversityZhuhaiChina
| | - Randall J. Bateman
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | | | - Beau M. Ances
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Richard J. Perrin
- Department of Pathology and ImmunologyWashington University in St. LouisSt. LouisMissouriUSA
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Tammie L. S. Benzinger
- Mallinckrodt Institute of RadiologyWashington University in St. LouisSt. LouisMissouriUSA
| | | | - John C. Morris
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
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94
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Suárez-Calvet M, Karikari TK, Ashton NJ, Lantero Rodríguez J, Milà-Alomà M, Gispert JD, Salvadó G, Minguillon C, Fauria K, Shekari M, Grau-Rivera O, Arenaza-Urquijo EM, Sala-Vila A, Sánchez-Benavides G, González-de-Echávarri JM, Kollmorgen G, Stoops E, Vanmechelen E, Zetterberg H, Blennow K, Molinuevo JL. Novel tau biomarkers phosphorylated at T181, T217 or T231 rise in the initial stages of the preclinical Alzheimer's continuum when only subtle changes in Aβ pathology are detected. EMBO Mol Med 2020; 12:e12921. [PMID: 33169916 PMCID: PMC7721364 DOI: 10.15252/emmm.202012921] [Citation(s) in RCA: 210] [Impact Index Per Article: 52.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 09/09/2020] [Accepted: 09/09/2020] [Indexed: 01/01/2023] Open
Abstract
In Alzheimer's disease (AD), tau phosphorylation in the brain and its subsequent release into cerebrospinal fluid (CSF) and blood is a dynamic process that changes during disease evolution. The main aim of our study was to characterize the pattern of changes in phosphorylated tau (p-tau) in the preclinical stage of the Alzheimer's continuum. We measured three novel CSF p-tau biomarkers, phosphorylated at threonine-181 and threonine-217 with an N-terminal partner antibody and at threonine-231 with a mid-region partner antibody. These were compared with an automated mid-region p-tau181 assay (Elecsys) as the gold standard p-tau measure. We demonstrate that these novel p-tau biomarkers increase more prominently in preclinical Alzheimer, when only subtle changes of amyloid-β (Aβ) pathology are detected, and can accurately differentiate Aβ-positive from Aβ-negative cognitively unimpaired individuals. Moreover, we show that the novel plasma N-terminal p-tau181 biomarker is mildly but significantly increased in the preclinical stage. Our results support the idea that early changes in neuronal tau metabolism in preclinical Alzheimer, likely in response to Aβ exposure, can be detected with these novel p-tau assays.
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Affiliation(s)
- Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Wallenberg Centre for Molecular and Translational Medicine, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK.,NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Juan Lantero Rodríguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Eider M Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aleix Sala-Vila
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - José Maria González-de-Echávarri
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de sFragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
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Dincer A, Gordon BA, Hari-Raj A, Keefe SJ, Flores S, McKay NS, Paulick AM, Shady Lewis KE, Feldman RL, Hornbeck RC, Allegri R, Ances BM, Berman SB, Brickman AM, Brooks WS, Cash DM, Chhatwal JP, Farlow MR, la Fougère C, Fox NC, Fulham MJ, Jack CR, Joseph-Mathurin N, Karch CM, Lee A, Levin J, Masters CL, McDade EM, Oh H, Perrin RJ, Raji C, Salloway SP, Schofield PR, Su Y, Villemagne VL, Wang Q, Weiner MW, Xiong C, Yakushev I, Morris JC, Bateman RJ, L S Benzinger T. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease. NEUROIMAGE-CLINICAL 2020; 28:102491. [PMID: 33395982 PMCID: PMC7689410 DOI: 10.1016/j.nicl.2020.102491] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 09/18/2020] [Accepted: 10/30/2020] [Indexed: 11/30/2022]
Abstract
Cortical signatures selective to AD could provide an early MRI biomarker. Autosomal dominant Alzheimer disease (ADAD) may model an ideal AD signature. ADAD and late-onset maps overlap in parietal cortex but contain unique features. Signatures predicted increasing amyloid within their own, but not across cohorts. These results indicate atrophy in AD can take multiple spatial patterns.
Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.
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Affiliation(s)
- Aylin Dincer
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amrita Hari-Raj
- The Ohio State University College of Medicine, Columbus, OH, USA
| | - Sarah J Keefe
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Shaney Flores
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Nicole S McKay
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Angela M Paulick
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Kristine E Shady Lewis
- Sanders Brown Center on Aging & Alzheimer's, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Rebecca L Feldman
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Russ C Hornbeck
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Neuropsychology and Neuropsychiatry, FLENI, Buenos Aires, Argentina
| | - Beau M Ances
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology and Clinical & Translational Science, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain and Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - William S Brooks
- Neuroscience Research Australia, Sydney, NSW, Australia; Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - David M Cash
- Dementia Research Centre and UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martin R Farlow
- Department of Neurology, Department of Radiology and Imaging Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Christian la Fougère
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany; Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital of Tübingen, Tübingen, Germany
| | - Nick C Fox
- Dementia Research Centre and UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Michael J Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital and University of Sydney, Sydney, NSW, Australia
| | | | - Nelly Joseph-Mathurin
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Celeste M Karch
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Athene Lee
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Eric M McDade
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Hwamee Oh
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Richard J Perrin
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Cyrus Raji
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stephen P Salloway
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Department of Medicine, Austin Health, University of Melbourne, Melbourne, VIC, Australia
| | - Qing Wang
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Michael W Weiner
- Department of Radiology and Biomedical Imaging, School of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Chengjie Xiong
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Igor Yakushev
- Department of Nuclear Medicine, Technical University of Munich, Munich, Germany
| | - John C Morris
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Randall J Bateman
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA.
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96
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Chang JF, Liu HC, Chen H, Chen WP, Juang JL, Wang PN, Yang SY. Effect of Times to Blood Processing on the Stability of Blood Proteins Associated with Dementia. Dement Geriatr Cogn Disord 2020; 49:303-311. [PMID: 32784295 PMCID: PMC9677837 DOI: 10.1159/000509358] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 06/09/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The stability of proteins in the collecting tubes after blood draw is critical to the measured concentrations of the proteins. Although the guidelines issued by the Clinical and Laboratory Standards Institute (CLSI) suggest centrifugation should take place within 2 h of drawing blood, it is very difficult to follow these guidelines in hospitals or clinics. It is necessary to study the effect of times to blood processing on the stability of the proteins of interest. METHODS In this work, the plasma proteins of interest were those relevant to dementia, such as amyloid β 1-40 (Aβ1-40), Aβ1-42, Tau protein (Tau), and α-synuclein. The times to blood processing after blood draw ranged from 0.5 to 8 h. The storage temperatures of blood were room temperature (approx. 25°C) and 30°C. After storage, blood samples were centrifuged at room temperature to obtain plasma samples. Ultrasensitive immunomagnetic reduction was applied to assay these proteins in the plasma. RESULTS The levels of plasma Aβ1-40, Tau, and α-synuclein did not significantly change until 8 h after blood draw when stored at room temperature. Plasma Aβ1-42 levels did not change significantly after 8 h of storage at room temperature before blood processing. Higher storage temperatures, such as 30°C, for blood samples accelerated the significant variations in the measured concentrations of Aβ1-40, Tau, and α-synuclein in plasma. CONCLUSION According to these results, for clinical practice, it is suggested that blood samples be stored at room temperature for no longer than 4.5 h after blood draw until centrifugation for the assay of dementia biomarkers in plasma.
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Affiliation(s)
| | | | - H.H. Chen
- MagQu Co., Ltd., New Taipei City, Taiwan
| | | | | | - Pei-Ning Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan,Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Shieh-Yueh Yang
- MagQu Co., Ltd., New Taipei City, Taiwan, .,MagQu LLC, Surprise, Arizona, USA,
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97
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Chipika RH, Siah WF, McKenna MC, Li Hi Shing S, Hardiman O, Bede P. The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface? J Neurol 2020; 268:4607-4629. [PMID: 33130950 DOI: 10.1007/s00415-020-10289-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 10/18/2020] [Accepted: 10/20/2020] [Indexed: 02/06/2023]
Abstract
Presymptomatic studies in ALS have consistently captured considerable disease burden long before symptom manifestation and contributed important academic insights. With the emergence of genotype-specific therapies, however, there is a pressing need to address practical objectives such as the estimation of age of symptom onset, phenotypic prediction, informing the optimal timing of pharmacological intervention, and identifying a core panel of biomarkers which may detect response to therapy. Existing presymptomatic studies in ALS have adopted striking different study designs, relied on a variety of control groups, used divergent imaging and electrophysiology methods, and focused on different genotypes and demographic groups. We have performed a systematic review of existing presymptomatic studies in ALS to identify common themes, stereotyped shortcomings, and key learning points for future studies. Existing presymptomatic studies in ALS often suffer from sample size limitations, lack of disease controls and rarely follow their cohort until symptom manifestation. As the characterisation of presymptomatic processes in ALS serves a multitude of academic and clinical purposes, the careful review of existing studies offers important lessons for future initiatives.
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Affiliation(s)
- Rangariroyashe H Chipika
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland.
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98
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Reitz C, Rogaeva E, Beecham GW. Late-onset vs nonmendelian early-onset Alzheimer disease: A distinction without a difference? NEUROLOGY-GENETICS 2020; 6:e512. [PMID: 33225065 PMCID: PMC7673282 DOI: 10.1212/nxg.0000000000000512] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 08/07/2020] [Indexed: 12/21/2022]
Abstract
There is mounting evidence that only a small fraction of early-onset Alzheimer disease cases (onset <65 years) are explained by known mutations. Even multiplex families with early onset often also have late-onset cases, suggesting that the commonly applied categorization of Alzheimer disease into early- and late-onset forms may not reflect distinct underlying etiology. Nevertheless, this categorization continues to govern today's research and the design of clinical trials. The aim of this review is to evaluate this categorization by providing a comprehensive, critical review of reported clinical, neuropathologic, and genomic characteristics of both onset-based subtypes and explore potential overlap between both categories. The article will lay out the need to comprehensively assess the phenotypic, neuropathologic, and molecular variability in Alzheimer disease and identify factors explaining the observed significant variation in onset age in persons with and without known mutations. The article will critically review ongoing large-scale genomic efforts in Alzheimer disease research (e.g., Alzheimer Disease Sequencing Project, Dominantly Inherited Alzheimer Network, Alzheimer Disease Neuroimaging Initiative) and their shortcomings to disentangle the delineation of unexplained nonmendelian early-onset from late-onset and mendelian forms of Alzheimer disease. In addition, it will outline specific approaches including epigenetic research through which a comprehensive characterization of this delineation can be achieved.
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Affiliation(s)
- Christiane Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain (C.R.), Gertrude H. Sergievsky Center (C.R.), Department of Neurology (C.R.), and Department of Epidemiology (C.R.), College of Physicians and Surgeons, Columbia University, New York, NY; Tanz Centre for Research in Neurodegenerative Disease (E.R.), University of Toronto, ON, Canada; and The John P. Hussman Institute for Human Genomics (G.W.B.), University of Miami, FL
| | - Ekaterina Rogaeva
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain (C.R.), Gertrude H. Sergievsky Center (C.R.), Department of Neurology (C.R.), and Department of Epidemiology (C.R.), College of Physicians and Surgeons, Columbia University, New York, NY; Tanz Centre for Research in Neurodegenerative Disease (E.R.), University of Toronto, ON, Canada; and The John P. Hussman Institute for Human Genomics (G.W.B.), University of Miami, FL
| | - Gary W Beecham
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain (C.R.), Gertrude H. Sergievsky Center (C.R.), Department of Neurology (C.R.), and Department of Epidemiology (C.R.), College of Physicians and Surgeons, Columbia University, New York, NY; Tanz Centre for Research in Neurodegenerative Disease (E.R.), University of Toronto, ON, Canada; and The John P. Hussman Institute for Human Genomics (G.W.B.), University of Miami, FL
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99
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Jack CR, Wiste HJ, Weigand SD, Therneau TM, Lowe VJ, Knopman DS, Botha H, Graff-Radford J, Jones DT, Ferman TJ, Boeve BF, Kantarci K, Vemuri P, Mielke MM, Whitwell J, Josephs K, Schwarz CG, Senjem ML, Gunter JL, Petersen RC. Predicting future rates of tau accumulation on PET. Brain 2020; 143:3136-3150. [PMID: 33094327 PMCID: PMC7586089 DOI: 10.1093/brain/awaa248] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 06/08/2020] [Accepted: 06/24/2020] [Indexed: 12/14/2022] Open
Abstract
Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer's clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer's disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.
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Affiliation(s)
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Tanis J Ferman
- Department of Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Michelle M Mielke
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Keith Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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100
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Vöglein J, Ricard I, Noachtar S, Kukull WA, Dieterich M, Levin J, Danek A. Seizures in Alzheimer's disease are highly recurrent and associated with a poor disease course. J Neurol 2020; 267:2941-2948. [PMID: 32488295 PMCID: PMC7501095 DOI: 10.1007/s00415-020-09937-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 05/18/2020] [Accepted: 05/19/2020] [Indexed: 11/18/2022]
Abstract
BACKGROUND Seizures are an important comorbidity in Alzheimer's disease (AD). Conflicting results regarding clinical parameters associated with seizures in AD were previously reported. Data on seizure recurrence risk, a crucial parameter for treatment decisions, are lacking. METHODS National Alzheimer's Coordinating Center data were analyzed. Seizure prevalence in AD and an association with disease duration were investigated. Associations of seizures with age of AD onset and with cognitive and functional performance, and seizure recurrence risk were studied. RESULTS 20,745 individuals were investigated. In AD dementia, seizure recurrence risk was 70.4% within 7.5 months. Seizure history was associated with an earlier age of onset of cognitive symptoms (seizures vs. no seizures: 64.7 vs. 70.4 years; p < 0.0001) and worse cognitive and functional performance (mean MMSE score: 16.6 vs. 19.6; mean CDR-sum of boxes score: 9.3 vs. 6.8; p < 0.0001; adjusted for disease duration and age). Seizure prevalence increased with duration of AD dementia (standardized OR = 1.55, 95% CI = 1.39-1.73, p < 0.0001), rising from 1.51% at 4.8 years to 5.43% at 11 years disease duration. Seizures were more frequent in AD dementia compared to normal controls (active seizures: 1.51% vs. 0.35%, p < 0.0001, OR = 4.34, 95% CI = 3.01-6.27; seizure history: 3.14% vs. 1.57%, p < 0.0001, OR = 2.03, 95% CI = 1.67-2.46). CONCLUSION Seizures in AD dementia feature an exceptionally high recurrence risk and are associated with a poor course of cognitive symptoms. AD patients are at an increased risk for seizures, particularly in later disease stages. Our findings emphasize a need for seizure history assessment in AD, inform individual therapeutic decisions and underline the necessity of systematic treatment studies of AD-associated epilepsy.
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Affiliation(s)
- Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Straße 17, 81377, Munich, Germany
- Department of Neurology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany
| | - Ingrid Ricard
- Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany
| | - Soheyl Noachtar
- Department of Neurology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany
| | - Walter A Kukull
- Department of Epidemiology, University of Washington School of Public Health, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Marianne Dieterich
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Straße 17, 81377, Munich, Germany
- Department of Neurology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Straße 17, 81377, Munich, Germany
- German Center for Vertigo and Balance Disorders, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Straße 17, 81377, Munich, Germany.
- Department of Neurology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Straße 17, 81377, Munich, Germany.
| | - Adrian Danek
- German Center for Neurodegenerative Diseases (DZNE), Feodor-Lynen-Straße 17, 81377, Munich, Germany.
- Department of Neurology, Ludwig-Maximilians University, Marchioninistraße 15, 81377, Munich, Germany.
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