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Groot C, Smith R, Collij LE, Mastenbroek SE, Stomrud E, Binette AP, Leuzy A, Palmqvist S, Mattsson-Carlgren N, Strandberg O, Cho H, Lyoo CH, Frisoni GB, Peretti DE, Garibotto V, La Joie R, Soleimani-Meigooni DN, Rabinovici G, Ossenkoppele R, Hansson O. Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment. JAMA Neurol 2024; 81:845-856. [PMID: 38857029 PMCID: PMC11165418 DOI: 10.1001/jamaneurol.2024.1612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 04/09/2024] [Indexed: 06/11/2024]
Abstract
Importance An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression. Objective To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia. Design, Setting, and Participants This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-β (Aβ) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study. Exposures Tau PET, Aβ PET, and MRI. Main Outcomes and Measures Positive results on tau PET (temporal meta-region of interest), Aβ PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics. Results In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aβ PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia. Conclusions and Relevance In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.
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Affiliation(s)
- Colin Groot
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Lyduine E. Collij
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, De Boelelaan, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Sophie E. Mastenbroek
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, De Boelelaan, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Giovanni B. Frisoni
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
- Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
| | - Debora E. Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Center for Biomedical Imaging, Geneva, Switzerland
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - David N. Soleimani-Meigooni
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Gil Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
- Associate Editor, JAMA Neurology
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Karlsson L, Vogel J, Arvidsson I, Åström K, Strandberg O, Seidlitz J, Bethlehem RAI, Stomrud E, Ossenkoppele R, Ashton NJ, Zetterberg H, Blennow K, Palmqvist S, Smith R, Janelidze S, La Joie R, Rabinovici GD, Binette AP, Mattsson-Carlgren N, Hansson O. A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.31.24308264. [PMID: 38853877 PMCID: PMC11160861 DOI: 10.1101/2024.05.31.24308264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.
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Affiliation(s)
- Linda Karlsson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jacob Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden
| | - Ida Arvidsson
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Kalle Åström
- Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Jakob Seidlitz
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104 USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA, 19104 USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Richard A. I. Bethlehem
- University of Cambridge, Department of Psychology, Cambridge Biomedical Campus, Cambridge, CB2 3EB, UK
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience, King’s College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, 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
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Jarek DJ, Mizerka H, Nuszkiewicz J, Szewczyk-Golec K. Evaluating p-tau217 and p-tau231 as Biomarkers for Early Diagnosis and Differentiation of Alzheimer's Disease: A Narrative Review. Biomedicines 2024; 12:786. [PMID: 38672142 PMCID: PMC11048667 DOI: 10.3390/biomedicines12040786] [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: 02/15/2024] [Revised: 03/26/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
The escalating prevalence of Alzheimer's disease (AD) highlights the urgent need to develop reliable biomarkers for early diagnosis and intervention. AD is characterized by the pathological accumulation of amyloid-beta plaques and tau neurofibrillary tangles. Phosphorylated tau (p-tau) proteins, particularly p-tau217 and p-tau231, have been identified as promising biomarker candidates to differentiate the disease progression from preclinical stages. This narrative review is devoted to a critical evaluation of the diagnostic accuracy, sensitivity, and specificity of p-tau217 and p-tau231 levels in the detection of AD, measured in plasma, serum, and cerebrospinal fluid, compared to established biomarkers. Additionally, the efficacy of these markers in distinguishing AD from other neurodegenerative disorders is examined. The significant advances offered by p-tau217 and p-tau231 in AD diagnostics are highlighted, demonstrating their unique utility in early detection and differential diagnosis. This comprehensive analysis not only confirms the excellent diagnostic capabilities of these markers, but also deepens the understanding of the molecular dynamics of AD, contributing to the broader scientific discourse on neurodegenerative diseases. This review is aimed to provide key information for researchers and clinicians across disciplines, filling interdisciplinary gaps and highlighting the role of p-tau proteins in revolutionizing AD research and clinical practice.
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Affiliation(s)
- Dorian Julian Jarek
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Hubert Mizerka
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Jarosław Nuszkiewicz
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Karolina Szewczyk-Golec
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
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Jiang GQ, He YK, Li TF, Qin QR, Wang DN, Huang F, Sun YH, Li J. Association of psychological resilience and cognitive function in older adults: Based on the Ma' anshan Healthy Aging Cohort Study. Arch Gerontol Geriatr 2024; 116:105166. [PMID: 37639840 DOI: 10.1016/j.archger.2023.105166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 08/17/2023] [Accepted: 08/20/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVES The purpose of this study was to explore whether psychological resilience can influence changes in cognitive function in older adults and provide clues and rationale for improving cognitive function and preventing the onset of dementia in the geriatric population. METHODS A total of 2495 older adults aged 60 years or older from the Ma' anshan Healthy Aging Cohort were included in the study. Participants' cognitive functioning and psychological resilience were measured using the MMSE (mini-mental state examination) scale and the SRQS (stress resilience quotient scale) scale during the 5 years of follow-up, and the association was explored. Those with MMSE scores ≤ 17 in the illiterate group, ≤ 20 in the elementary school group, and ≤ 24 in the secondary school and above group were considered cognitive impairment. RESULTS The prevalence of cognitive impairment increased from 6.89% to 14.30% during the five years of follow-up. At 5-year follow-up, the group with the highest psychological resilience had 41 (6.83%) individuals whose cognitive functioning changed from normal to cognitive impairment, while the group with the worst psychological resilience had 114 (18.33%) individuals. The study also found a significant effect of different levels of psychological resilience on changes in cognitive functioning after adjusting for potential confounders. Compared with Q1 (the reference group), the Odds ratio of cognitive decline in Q2, Q3 and Q4 groups were 0.51(0.42,0.64), 0.37(0.29,0.47) and 0.19(0.13,0.27), respectively. CONCLUSIONS Improving the level of psychological resilience in older adults may be one way to prevent the incidence of cognitive impairment.
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Affiliation(s)
- Guo-Qing Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Ye-Ke He
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Teng-Fei Li
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Qi-Rong Qin
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Ma'anshan Center for Disease Control and prevention, Ma'anshan, Anhui, 243011, China
| | - Dan-Ni Wang
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Fen Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Ye-Huan Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, 230032, China
| | - Jie Li
- School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China.
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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Coomans EM, de Koning LA, Rikken RM, Verfaillie SCJ, Visser D, den Braber A, Tomassen J, van de Beek M, Collij LE, Lemstra AW, Windhorst AD, Barkhof F, Golla SSV, Visser PJ, Scheltens P, van der Flier WM, Ossenkoppele R, van Berckel BNM, van de Giessen E. Performance of a [ 18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies. Neurology 2023; 101:e1850-e1862. [PMID: 37748892 PMCID: PMC10663007 DOI: 10.1212/wnl.0000000000207794] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/24/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables. METHODS We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE). RESULTS We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91-0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (β = -0.52, CI -0.74 to -0.30, p < 0.001) and participants with AD (β = -0.30, CI -0.58 to -0.02, p = 0.04). DISCUSSION The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.
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Affiliation(s)
- Emma M Coomans
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - Lotte A de Koning
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Roos M Rikken
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sander C J Verfaillie
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Denise Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Anouk den Braber
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Jori Tomassen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Marleen van de Beek
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Lyduine E Collij
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Afina W Lemstra
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Albert D Windhorst
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sandeep S V Golla
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Pieter Jelle Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Wiesje M van der Flier
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Bart N M van Berckel
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Elsmarieke van de Giessen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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7
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Kim HB, Kim SH, Um YH, Wang SM, Kim REY, Choe YS, Lee J, Kim D, Lim HK, Lee CU, Kang DW. Modulation of associations between education years and cortical volume in Alzheimer's disease vulnerable brain regions by Aβ deposition and APOE ε4 carrier status in cognitively normal older adults. Front Aging Neurosci 2023; 15:1248531. [PMID: 37829142 PMCID: PMC10565031 DOI: 10.3389/fnagi.2023.1248531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/05/2023] [Indexed: 10/14/2023] Open
Abstract
Background Education years, as a measure of cognitive reserve, have been shown to affect the progression of Alzheimer's disease (AD), both pathologically and clinically. However, inconsistent results have been reported regarding the association between years of education and intermediate structural changes in AD-vulnerable brain regions, particularly when AD risk factors were not considered during the preclinical phase. Objective This study aimed to examine how Aβ deposition and APOE ε4 carrier status moderate the relationship between years of education and cortical volume in AD-vulnerable regions among cognitively normal older adults. Methods A total of 121 participants underwent structural MRI, [18F] flutemetamol PET-CT imaging, and neuropsychological battery assessment. Multiple regression analysis was conducted to examine the interaction between years of education and the effects of potential modifiers on cortical volume. The associations between cortical volume and neuropsychological performance were further explored in subgroups categorized based on AD risk factors. Results The cortical volume of the left lateral occipital cortex and bilateral fusiform gyrus demonstrated a significant differential association with years of education, depending on the presence of Aβ deposition and APOE ε4 carrier status. Furthermore, a significant relationship between the cortical volume of the bilateral fusiform gyrus and AD-nonspecific cognitive function was predominantly observed in individuals without AD risk factors. Conclusion AD risk factors exerted varying influences on the association between years of education and cortical volume during the preclinical phase. Further investigations into the long-term implications of these findings would enhance our understanding of cognitive reserves in the preclinical stages of AD.
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Affiliation(s)
- Hak-Bin Kim
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung-Hwan Kim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | - Yeong Sim Choe
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Jiyeon Lee
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Donghyeon Kim
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- Research Institute, NEUROPHET Inc., Seoul, Republic of Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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8
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Quattrini G, Ferrari C, Pievani M, Geviti A, Ribaldi F, Scheffler M, Frisoni GB, Garibotto V, Marizzoni M. Unsupervised [ 18F]Flortaucipir cutoffs for tau positivity and staging in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:3265-3275. [PMID: 37272955 PMCID: PMC10542510 DOI: 10.1007/s00259-023-06280-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 05/19/2023] [Indexed: 06/06/2023]
Abstract
PURPOSE Several [18F]Flortaucipir cutoffs have been proposed for tau PET positivity (T+) in Alzheimer's disease (AD), but none were data-driven. The aim of this study was to establish and validate unsupervised T+ cutoffs by applying Gaussian mixture models (GMM). METHODS Amyloid negative (A-) cognitively normal (CN) and amyloid positive (A+) AD-related dementia (ADRD) subjects from ADNI (n=269) were included. ADNI (n=475) and Geneva Memory Clinic (GMC) cohorts (n=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating. RESULTS GMM-based cutoffs classified less subjects as T+, mainly in the A- CN (<3.4% vs >28.5%) and A+ CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs. CONCLUSION We provided reliable data-driven [18F]Flortaucipir cutoffs for in vivo T+ detection in AD. These cutoffs might be useful to select participants in clinical and research studies.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, 25123, Brescia, Italy
| | - Clarissa Ferrari
- FONDAZIONE POLIAMBULANZA ISTITUTO OSPEDALIERO via Bissolati, 57, 25124, Brescia, Italy
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Andrea Geviti
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy
| | - Federica Ribaldi
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Giovanni B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, 1205, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocentre, Faculty of Medicine, University of Geneva, 1205, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, 1205, Geneva, Switzerland
- Centre for Biomedical Imaging (CIBM), 1205, Geneva, Switzerland
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
- Biological Psychiatric Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25125, Brescia, Italy.
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9
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Wagatsuma K, Miwa K, Akamatsu G, Yamao T, Kamitaka Y, Sakurai M, Fujita N, Hanaoka K, Matsuda H, Ishii K. Toward standardization of tau PET imaging corresponding to various tau PET tracers: a multicenter phantom study. Ann Nucl Med 2023; 37:494-503. [PMID: 37243882 DOI: 10.1007/s12149-023-01847-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/17/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Tau positron emission tomography (PET) imaging is a recently developed non-invasive tool that can detect the density and extension of tau neurofibrillary tangles. Tau PET tracers have been validated to harmonize and accelerate their development and implementation in clinical practice. Whereas standard protocols including injected dose, uptake time, and duration have been determined for tau PET tracers, reconstruction parameters have not been standardized. The present study conducted phantom experiments based on tau pathology to standardize quantitative tau PET imaging parameters and optimize reconstruction conditions of PET scanners at four Japanese sites according to the results of phantom experiments. METHODS The activity of 4.0 and 2.0 kBq/mL for Hoffman 3D brain and cylindrical phantoms, respectively, was estimated from published studies of brain activity using [18F]flortaucipir, [18F]THK5351, and [18F]MK6240. We developed an original tau-specific volume of interest template for the brain based on pathophysiological tau distribution in the brain defined as Braak stages. We acquired brain and cylindrical phantom images using four PET scanners. Iteration numbers were determined as contrast and recover coefficients (RCs) in gray (GM) and white (WM) matter, and the magnitude of the Gaussian filter was determined from image noise. RESULTS Contrast and RC converged at ≥ 4 iterations, the error rates of RC for GM and WM were < 15% and 1%, respectively, and noise was < 10% in Gaussian filters of 2-4 mm in images acquired using the four scanners. Optimizing the reconstruction conditions for phantom tau PET images acquired by each scanner improved contrast and image noise. CONCLUSIONS The phantom activity was comprehensive for first- and second-generation tau PET tracers. The mid-range activity that we determined could be applied to later tau PET tracers. We propose an analytical tau-specific VOI template based on tau pathophysiological changes in patients with AD to standardize tau PET imaging. Phantom images reconstructed under the optimized conditions for tau PET imaging achieved excellent image quality and quantitative accuracy.
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Affiliation(s)
- Kei Wagatsuma
- School of Allied Health Sciences, Kitasato University, 1-15-1 Kitazato, Minami-Ku, Sagamihara, Kanagawa, 252-0373, Japan.
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan.
| | - Kenta Miwa
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima City, Fukushima, 960-1295, Japan
| | - Go Akamatsu
- Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage-Ku, Chiba, 263-8555, Japan
| | - Tensho Yamao
- Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Fukushima City, Fukushima, 960-1295, Japan
| | - Yuto Kamitaka
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan
| | - Minoru Sakurai
- Clinical Imaging Center for Healthcare, Nippon Medical School, 1-12-15, Sendagi, Bunkyo-Ku, Tokyo, 113-0022, Japan
| | - Naotoshi Fujita
- Department of Radiological Technology, Nagoya University Hospital, 65 Tsurumai-Cho, Showa-Ku, Nagoya, 466-8560, Japan
| | - Kohei Hanaoka
- Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, 377-2 Onohigashi, Osakasayama, Osaka, 589-8511, Japan
| | - Hiroshi Matsuda
- Department of Biofunctional Imaging, Fukushima Medical University, 1 Hikarigaoka, Fukushima City, Fukushima, 960-1295, Japan
- Drug Discovery and Cyclotron Research Center, Southern Tohoku Research Institute for Neuroscience, 7-115, Yatsuyamada, Koriyama, 963-8052, Japan
| | - Kenji Ishii
- Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 35-2, Sakae-Cho, Itabashi-Ku, Tokyo, 173-0015, Japan
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10
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Bocancea DI, Svenningsson AL, van Loenhoud AC, Groot C, Barkhof F, Strandberg O, Smith R, La Joie R, Rosen HJ, Pontecorvo MJ, Rabinovici GD, van der Flier WM, Hansson O, Ossenkoppele R. Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis. Brain 2023; 146:3719-3734. [PMID: 36967222 PMCID: PMC10473572 DOI: 10.1093/brain/awad100] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 02/03/2023] [Accepted: 02/23/2023] [Indexed: 09/03/2023] Open
Abstract
Mechanisms of resilience against tau pathology in individuals across the Alzheimer's disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer's disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer's disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.
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Affiliation(s)
- Diana I Bocancea
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | | | - Anna C van Loenhoud
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - Colin Groot
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, 211 46 Lund, Sweden
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Center for Medical Image Computing, University College London, London WC1N 3BG, UK
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, 211 46 Lund, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, 211 46 Lund, Sweden
- Department of Neurology, Skåne University Hospital, 221 84 Lund, Sweden
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
| | | | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, 211 46 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 214 28 Malmö, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, 211 46 Lund, Sweden
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11
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Carosi JM, Sargeant TJ. Rapamycin and Alzheimer disease: a hypothesis for the effective use of rapamycin for treatment of neurodegenerative disease. Autophagy 2023; 19:2386-2390. [PMID: 36727410 PMCID: PMC10351443 DOI: 10.1080/15548627.2023.2175569] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/26/2023] [Accepted: 01/30/2023] [Indexed: 02/03/2023] Open
Abstract
In 2019 we summarized work relating to the potential use of rapamycin for treating Alzheimer disease (AD). We considered the commentary necessary because use of rapamycin in people with AD is a very real prospect and we wanted to present a balanced view of the likely consequences of MTOR (mechanistic target of rapamycin kinase) inhibition in the AD brain. We concluded that use of rapamycin, an MTOR inhibitor that increases macroautophagy/autophagy, could hold promise for prevention of AD if used early enough. However, MTOR inhibition appeared ineffectual in resolving existing amyloid pathology in AD mouse models. In this View article, we update these observations with new studies that have used rapamycin in AD models and provide evidence both for and against its use in AD. We also discuss rapamycin in the light of new research that describes rapamycin-induced autophagic stress in the aging brain and autophagic stress as the origin of the amyloid plaque itself. We conclude that rapamycin will have complex effects on the brain in AD. Further, we hypothesize that lysosomal degradative capacity in the brain will likely determine how effective or detrimental rapamycin will be as a treatment of AD.Abbreviations: AD: Alzheimer disease; APP: amyloid beta precursor protein; MAPT/tau: microtubule associated protein tau; MTOR: mechanistic target of rapamycin kinase; MTORC1: mechanistic target of rapamycin kinase complex 1.
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Affiliation(s)
- Julian M Carosi
- Lysosomal Health in Ageing, Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia
| | - Timothy J Sargeant
- Lysosomal Health in Ageing, Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia
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12
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Lamontagne-Kam D, Ulfat AK, Hervé V, Vu TM, Brouillette J. Implication of tau propagation on neurodegeneration in Alzheimer's disease. Front Neurosci 2023; 17:1219299. [PMID: 37483337 PMCID: PMC10360202 DOI: 10.3389/fnins.2023.1219299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 06/07/2023] [Indexed: 07/25/2023] Open
Abstract
Propagation of tau fibrils correlate closely with neurodegeneration and memory deficits seen during the progression of Alzheimer's disease (AD). Although it is not well-established what drives or attenuates tau spreading, new studies on human brain using positron emission tomography (PET) have shed light on how tau phosphorylation, genetic factors, and the initial epicenter of tau accumulation influence tau accumulation and propagation throughout the brain. Here, we review the latest PET studies performed across the entire AD continuum looking at the impact of amyloid load on tau pathology. We also explore the effects of structural, functional, and proximity connectivity on tau spreading in a stereotypical manner in the brain of AD patients. Since tau propagation can be quite heterogenous between individuals, we then consider how the speed and pattern of propagation are influenced by the starting localization of tau accumulation in connected brain regions. We provide an overview of some genetic variants that were shown to accelerate or slow down tau spreading. Finally, we discuss how phosphorylation of certain tau epitopes affect the spreading of tau fibrils. Since tau pathology is an early event in AD pathogenesis and is one of the best predictors of neurodegeneration and memory impairments, understanding the process by which tau spread from one brain region to another could pave the way to novel therapeutic avenues that are efficient during the early stages of the disease, before neurodegeneration induces permanent brain damage and severe memory loss.
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13
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Li B, Shi K, Ren C, Kong M, Ba M. Detection of Tau-PET Positivity in Clinically Diagnosed Mild Cognitive Impairment with Multidimensional Features. J Alzheimers Dis 2023:JAD230180. [PMID: 37334600 DOI: 10.3233/jad-230180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
BACKGROUND The way to evaluate brain tau pathology in vivo is tau positron emission tomography (tau-PET) or cerebrospinal fluid (CSF) analysis. In the clinically diagnosed mild cognitive impairment (MCI), a significant proportion of tau-PET are negative. Interest in less expensive and convenient ways to detect tau pathology in Alzheimer's disease has increased due to the high cost of tau-PET and the invasiveness of lumbar puncture, which typically slows down the cost and enrollment of clinical trials. OBJECTIVE We aimed to investigate one simple and effective method in predicting tau-PET status in MCI individuals. METHODS The sample included 154 individuals which were dichotomized into tau-PET (+) and tau-PET (-) using a cut-off of >1.33. We used stepwise regression to select the unitary or combination of variables that best predicted tau-PET. The receiver operating characteristic curve was used to assess the accuracy of single and multiple clinical markers. RESULTS The combined performance of three variables [Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-Cog13), Mini-Mental State Examination (MMSE), ADNI-Memory summary score (ADNI-MEM)] in neurocognitive measures demonstrated good predictive accuracy of tau-PET status [accuracy = 85.7%, area under the curve (AUC) = 0.879]. The combination of clinical markers model (APOEɛ4, neurocognitive measures and structural MRI imaging of middle temporal) had the best discriminative power (AUC = 0.946). CONCLUSION As a noninvasive test, the combination of APOEɛ4, neurocognitive measures and structural MRI imaging of middle temporal accurately predicts tau-PET status. The finding may provide a non-invasive, cost-effective tool for clinical application in predicting tau pathology among MCI individuals.
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Affiliation(s)
- Bingyu Li
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Kening Shi
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Chao Ren
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai, Shandong, China
| | - Maowen Ba
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
- Yantai Regional Sub Center of National Center for Clinical Medical Research of Neurological Diseases, Shandong, China
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Beach TG, Sue LI, Scott S, Intorcia AJ, Walker JE, Arce RA, Glass MJ, Borja CI, Cline MP, Hemmingsen SJ, Qiji S, Stewart A, Martinez KN, Krupp A, McHattie R, Mariner M, Lorenzini I, Kuramoto A, Long KE, Tremblay C, Caselli RJ, Woodruff BK, Rapscak SZ, Belden CM, Goldfarb D, Choudhury P, Driver-Dunckley ED, Mehta SH, Sabbagh MN, Shill HA, Atri A, Adler CH, Serrano GE. Cerebral white matter rarefaction has both neurodegenerative and vascular causes and may primarily be a distal axonopathy. J Neuropathol Exp Neurol 2023; 82:457-466. [PMID: 37071794 PMCID: PMC10209646 DOI: 10.1093/jnen/nlad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023] Open
Abstract
Cerebral white matter rarefaction (CWMR) was considered by Binswanger and Alzheimer to be due to cerebral arteriolosclerosis. Renewed attention came with CT and MR brain imaging, and neuropathological studies finding a high rate of CWMR in Alzheimer disease (AD). The relative contributions of cerebrovascular disease and AD to CWMR are still uncertain. In 1181 autopsies by the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), large-format brain sections were used to grade CWMR and determine its vascular and neurodegenerative correlates. Almost all neurodegenerative diseases had more severe CWMR than the normal control group. Multivariable logistic regression models indicated that Braak neurofibrillary stage was the strongest predictor of CWMR, with additional independently significant predictors including age, cortical and diencephalic lacunar and microinfarcts, body mass index, and female sex. It appears that while AD and cerebrovascular pathology may be additive in causing CWMR, both may be solely capable of this. The typical periventricular pattern suggests that CWMR is primarily a distal axonopathy caused by dysfunction of the cell bodies of long-association corticocortical projection neurons. A consequence of these findings is that CWMR should not be viewed simply as "small vessel disease" or as a pathognomonic indicator of vascular cognitive impairment or vascular dementia.
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Affiliation(s)
- Thomas G Beach
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Lucia I Sue
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Sarah Scott
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | | | - Richard A Arce
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Michael J Glass
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Madison P Cline
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Sanaria Qiji
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Analisa Stewart
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Addison Krupp
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Rylee McHattie
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Monica Mariner
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Angela Kuramoto
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Kathy E Long
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | | | | | | | | | | | | | | | - Shyamal H Mehta
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona, USA
| | | | - Holly A Shill
- Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
- Harvard Medical School & Brigham & Women’s Hospital, Boston, Massachusetts, USA
| | - Charles H Adler
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Geidy E Serrano
- Banner Sun Health Research Institute, Sun City, Arizona, USA
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15
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Santillo AF, Leuzy A, Honer M, Landqvist Waldö M, Tideman P, Harper L, Ohlsson T, Moes S, Giannini L, Jögi J, Groot C, Ossenkoppele R, Strandberg O, van Swieten J, Smith R, Hansson O. [ 18F]RO948 tau positron emission tomography in genetic and sporadic frontotemporal dementia syndromes. Eur J Nucl Med Mol Imaging 2023; 50:1371-1383. [PMID: 36513817 PMCID: PMC10027632 DOI: 10.1007/s00259-022-06065-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 11/28/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE To examine [18F]RO948 retention in FTD, sampling the underlying protein pathology heterogeneity. METHODS A total of 61 individuals with FTD (n = 35), matched cases of AD (n = 13) and Aβ-negative cognitively unimpaired individuals (n = 13) underwent [18F]RO948PET and MRI. FTD included 21 behavioral variant FTD (bvFTD) cases, 11 symptomatic C9orf72 mutation carriers, one patient with non-genetic bvFTD-ALS, one individual with bvFTD due to a GRN mutation, and one due to a MAPT mutation (R406W). Tracer retention was examined using a region-of-interest and voxel-wise approaches. Two individuals (bvFTD due to C9orf72) underwent postmortem neuropathological examination. Tracer binding was additionally assessed in vitro using [3H]RO948 autoradiography in six separate cases. RESULTS [18F]RO948 retention across ROIs was clearly lower than in AD and comparable to that in Aβ-negative cognitively unimpaired individuals. Only minor loci of tracer retention were seen in bvFTD; these did not overlap with the observed cortical atrophy in the cases, the expected pattern of atrophy, nor the expected or verified protein pathology distribution. Autoradiography analyses showed no specific [3H]RO948 binding. The R406W MAPT mutation carriers were clear exceptions with AD-like retention levels and specific in-vitro binding. CONCLUSION [18F]RO948 uptake is not significantly increased in the majority of FTD patients, with a clear exception being specific MAPT mutations.
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Affiliation(s)
- Alexander F Santillo
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden.
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden.
| | - Antoine Leuzy
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Michael Honer
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Maria Landqvist Waldö
- Clinical Sciences Helsingborg, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Pontus Tideman
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Luke Harper
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Tomas Ohlsson
- Radiation Physics, Skane University Hospital, Scania, Sweden
| | - Svenja Moes
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche, Basel, Switzerland
| | - Lucia Giannini
- Alzheimer Center, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jonas Jögi
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Colin Groot
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Rik Ossenkoppele
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Olof Strandberg
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - John van Swieten
- Alzheimer Center, Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ruben Smith
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Oskar Hansson
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden
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16
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Young CB, Johns E, Kennedy G, Belloy ME, Insel PS, Greicius MD, Sperling RA, Johnson KA, Poston KL, Mormino EC. APOE effects on regional tau in preclinical Alzheimer's disease. Mol Neurodegener 2023; 18:1. [PMID: 36597122 PMCID: PMC9811772 DOI: 10.1186/s13024-022-00590-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 12/14/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND APOE variants are strongly associated with abnormal amyloid aggregation and additional direct effects of APOE on tau aggregation are reported in animal and human cell models. The degree to which these effects are present in humans when individuals are clinically unimpaired (CU) but have abnormal amyloid (Aβ+) remains unclear. METHODS We analyzed data from CU individuals in the Anti-Amyloid Treatment in Asymptomatic AD (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies. Amyloid PET data were available for 4486 participants (3163 Aβ-, 1323 Aβ+) and tau PET data were available for a subset of 447 participants (55 Aβ-, 392 Aβ+). Linear models examined APOE (number of e2 and e4 alleles) associations with global amyloid and regional tau burden in medial temporal lobe (entorhinal, amygdala) and early neocortical regions (inferior temporal, inferior parietal, precuneus). Consistency of APOE4 effects on regional tau were examined in 220 Aβ + CU and mild cognitive impairment (MCI) participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS APOE2 and APOE4 were associated with lower and higher amyloid positivity rates, respectively. Among Aβ+ CU, e2 and e4 were associated with reduced (-12 centiloids per allele) and greater (+15 centiloids per allele) continuous amyloid burden, respectively. APOE2 was associated with reduced regional tau in all regions (-0.05 to -0.09 SUVR per allele), whereas APOE4 was associated with greater regional tau (+0.02 to +0.07 SUVR per allele). APOE differences were confirmed by contrasting e3/e3 with e2/e3 and e3/e4. Mediation analyses among Aβ+ s showed that direct effects of e2 on regional tau were present in medial temporal lobe and early neocortical regions, beyond an indirect pathway mediated by continuous amyloid burden. For e4, direct effects on regional tau were only significant in medial temporal lobe. The magnitude of protective e2 effects on regional tau was consistent across brain regions, whereas detrimental e4 effects were greatest in medial temporal lobe. APOE4 patterns were confirmed in Aβ+ ADNI participants. CONCLUSIONS APOE influences early regional tau PET burden, above and beyond effects related to cross-sectional amyloid PET burden. Therapeutic strategies targeting underlying mechanisms related to APOE may modify tau accumulation among Aβ+ individuals.
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Affiliation(s)
- Christina B Young
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA.
| | - Emily Johns
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Gabriel Kennedy
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Michael E Belloy
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Philip S Insel
- University of California San Francisco, San Francisco, CA, USA
| | - Michael D Greicius
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Reisa A Sperling
- Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Keith A Johnson
- Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Kathleen L Poston
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Elizabeth C Mormino
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
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17
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Pascoal TA, Leuzy A, Therriault J, Chamoun M, Lussier F, Tissot C, Strandberg O, Palmqvist S, Stomrud E, Ferreira PCL, Ferrari‐Souza JP, Smith R, Benedet AL, Gauthier S, Hansson O, Rosa‐Neto P. Discriminative accuracy of the A/T/N scheme to identify cognitive impairment due to Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12390. [PMID: 36733847 PMCID: PMC9886860 DOI: 10.1002/dad2.12390] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/09/2022] [Accepted: 11/29/2022] [Indexed: 02/03/2023]
Abstract
Introduction The optimal combination of amyloid-β/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear. Methods We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non-AD neurodegenerative diseases in the TRIAD, BioFINDER-1 and BioFINDER-2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC). Results For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90-0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non-AD neurodegenerative diseases (AUC range; A biomarker: 0.84-1; T biomarker: 0.83-1). Discussion In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy.
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Affiliation(s)
- Tharick A. Pascoal
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Antoine Leuzy
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
| | - Joseph Therriault
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Mira Chamoun
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Firoza Lussier
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Cecile Tissot
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
| | - Olof Strandberg
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Sebastian Palmqvist
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Erik Stomrud
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Pamela C. L. Ferreira
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - João Pedro Ferrari‐Souza
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do SulPorto AlegreRSBrazil
| | - Ruben Smith
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Andrea Lessa Benedet
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Serge Gauthier
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Pedro Rosa‐Neto
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
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18
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Harrison TM, Ward TJ, Murphy A, Baker SL, Dominguez PA, Koeppe R, Vemuri P, Lockhart SN, Jung Y, Harvey DJ, Lovato L, Toga AW, Masdeu J, Oh H, Gitelman DR, Aggarwal N, Snyder HM, Baker LD, DeCarli C, Jagust WJ, Landau SM. Optimizing quantification of MK6240 tau PET in unimpaired older adults. Neuroimage 2023; 265:119761. [PMID: 36455762 PMCID: PMC9957642 DOI: 10.1016/j.neuroimage.2022.119761] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 10/28/2022] [Accepted: 11/21/2022] [Indexed: 11/29/2022] Open
Abstract
Accurate measurement of Alzheimer's disease (AD) pathology in older adults without significant clinical impairment is critical to assessing intervention strategies aimed at slowing AD-related cognitive decline. The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (POINTER) is a 2-year randomized controlled trial to evaluate the effect of multicomponent risk reduction strategies in older adults (60-79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting tau-PET ([18F]MK6240), beta-amyloid (Aβ)-PET ([18F]florbetaben [FBB]) and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at-risk sample. Here 481 participants (70.0±5.0; 66% F) with baseline MK6240, FBB and structural MRI scans were included. PET scans were coregistered to the structural MRI which was used to create FreeSurfer-defined reference regions and target regions of interest (ROIs). We also created off-target signal (OTS) ROIs to examine the magnitude and distribution of MK6240 OTS across the brain as well as relationships between OTS and age, sex, and race. OTS was unimodally distributed, highly correlated across OTS ROIs and related to younger age and sex but not race. Aiming to identify an optimal processing approach for MK6240 that would reduce the influence of OTS, we compared our previously validated MRI-guided standard PET processing and 6 alternative approaches. The alternate approaches included combinations of reference region erosion and meningeal OTS masking before spatial smoothing as well as partial volume correction. To compare processing approaches we examined relationships between target ROIs (entorhinal cortex (ERC), hippocampus or a temporal meta-ROI (MetaROI)) SUVR and age, sex, race, Aβ and a general cognitive status measure, the Modified Telephone Interview for Cognitive Status (TICSm). Overall, the processing approaches performed similarly, and none showed a meaningful improvement over standard processing. Across processing approaches we observed previously reported relationships with MK6240 target ROIs including positive associations with age, an Aβ+> Aβ- effect and negative associations with cognition. In sum, we demonstrated that different methods for minimizing effects of OTS, which is highly correlated across the brain within subject, produced no substantive change in our performance metrics. This is likely because OTS contaminates both reference and target regions and this contamination largely cancels out in SUVR data. Caution should be used when efforts to reduce OTS focus on target or reference regions in isolation as this may exacerbate OTS contamination in SUVR data.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - William J Jagust
- University of California Berkeley, USA; Lawrence Berkeley National Laboratory, USA
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Toledo JB, Rashid T, Liu H, Launer L, Shaw LM, Heckbert SR, Weiner M, Seshadri S, Habes M. SPARE-Tau: A flortaucipir machine-learning derived early predictor of cognitive decline. PLoS One 2022; 17:e0276392. [PMID: 36327215 PMCID: PMC9632811 DOI: 10.1371/journal.pone.0276392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/05/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Recently, tau PET tracers have shown strong associations with clinical outcomes in individuals with cognitive impairment and cognitively unremarkable elderly individuals. flortaucipir PET scans to measure tau deposition in multiple brain areas as the disease progresses. This information needs to be summarized to evaluate disease severity and predict disease progression. We, therefore, sought to develop a machine learning-derived index, SPARE-Tau, which successfully detects pathology in the earliest disease stages and accurately predicts progression compared to a priori-based region of interest approaches (ROI). METHODS 587 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort had flortaucipir scans, structural MRI scans, and an Aβ biomarker test (CSF or florbetapir PET) performed on the same visit. We derived the SPARE-Tau index in a subset of 367 participants. We evaluated associations with clinical measures for CSF p-tau, SPARE-MRI, and flortaucipir PET indices (SPARE-Tau, meta-temporal, and average Braak ROIs). Bootstrapped multivariate adaptive regression splines linear regression analyzed the association between the biomarkers and baseline ADAS-Cog13 scores. Bootstrapped multivariate linear regression models evaluated associations with clinical diagnosis. Cox-hazards and mixed-effects models investigated clinical progression and longitudinal ADAS-Cog13 changes. The Aβ positive cognitively unremarkable participants, not included in the SPARE-Tau training, served as an independent validation group. RESULTS Compared to CSF p-tau, meta-temporal, and averaged Braak tau PET ROIs, SPARE-Tau showed the strongest association with baseline ADAS-cog13 scores and diagnosis. SPARE-Tau also presented the strongest association with clinical progression in cognitively unremarkable participants and longitudinal ADAS-Cog13 changes. Results were confirmed in the Aβ+ cognitively unremarkable hold-out sample participants. CSF p-tau showed the weakest cross-sectional associations and longitudinal prediction. DISCUSSION Flortaucipir indices showed the strongest clinical association among the studied biomarkers (flortaucipir, florbetapir, structural MRI, and CSF p-tau) and were predictive in the preclinical disease stages. Among the flortaucipir indices, the machine-learning derived SPARE-Tau index was the most sensitive clinical progression biomarker. The combination of different biomarker modalities better predicted cognitive performance.
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Affiliation(s)
- Jon B. Toledo
- Department of Neurology, University of Florida College of Medicine, Gainesville, Florida, United States of America
- Department of Neurology Houston Methodist Hospital, Houston, Texas, United States of America
| | - Tanweer Rashid
- Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), San Antonio, Texas, United States of America
| | - Hangfan Liu
- Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), San Antonio, Texas, United States of America
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, Maryland, United States of America
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Susan R. Heckbert
- Department of Epidemiology and Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States of America
| | - Michael Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, United States of America
- Department of Radiology, University of California, San Francisco, California, United States of America
- Department of Medicine, University of California, San Francisco, California, United States of America
- Department of Psychiatry, University of California, San Francisco, California, United States of America
- Department of Neurology, University of California, San Francisco, California, United States of America
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, Texas, United States of America
| | - Mohamad Habes
- Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center San Antonio (UTHSCSA), San Antonio, Texas, United States of America
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, Texas, United States of America
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20
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Kim SE, Kim HJ, Jang H, Weiner MW, DeCarli C, Na DL, Seo SW. Interaction between Alzheimer's Disease and Cerebral Small Vessel Disease: A Review Focused on Neuroimaging Markers. Int J Mol Sci 2022; 23:10490. [PMID: 36142419 PMCID: PMC9499680 DOI: 10.3390/ijms231810490] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/07/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan 48108, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, CA 94121, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA 95616, USA
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06355, Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul 06351, Korea
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21
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Young CB, Winer JR, Younes K, Cody KA, Betthauser TJ, Johnson SC, Schultz A, Sperling RA, Greicius MD, Cobos I, Poston KL, Mormino EC. Divergent Cortical Tau Positron Emission Tomography Patterns Among Patients With Preclinical Alzheimer Disease. JAMA Neurol 2022; 79:592-603. [PMID: 35435938 PMCID: PMC9016616 DOI: 10.1001/jamaneurol.2022.0676] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease. Objective To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+). Design, Setting, and Participants This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022. Main Outcomes and Measures Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical+) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined. Results The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL+). Individuals in the A+T cortical+ group were younger than those in the A+T MTL+ group (t61.867 = -2.597; P = .03). Across the A+T cortical+ and A+T MTL+ groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical+ and A+T MTL+ groups, whereas executive functioning scores were lower for the A+T cortical+ group than for the A+T MTL+ group. The prevalence of the A+T cortical+ group and tau patterns within the A+T cortical+ group were consistent in ADNI, HABS, and Wisconsin. Conclusions and Relevance This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.
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Affiliation(s)
- Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Joseph R Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Kyan Younes
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Karly A Cody
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison
| | - Aaron Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Inma Cobos
- Department of Pathology, Stanford University School of Medicine, Stanford, California
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
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22
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Zhang Y, Wu KM, Yang L, Dong Q, Yu JT. Tauopathies: new perspectives and challenges. Mol Neurodegener 2022; 17:28. [PMID: 35392986 PMCID: PMC8991707 DOI: 10.1186/s13024-022-00533-z] [Citation(s) in RCA: 99] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/23/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Tauopathies are a class of neurodegenerative disorders characterized by neuronal and/or glial tau-positive inclusions. MAIN BODY Clinically, tauopathies can present with a range of phenotypes that include cognitive/behavioral-disorders, movement disorders, language disorders and non-specific amnestic symptoms in advanced age. Pathologically, tauopathies can be classified based on the predominant tau isoforms that are present in the inclusion bodies (i.e., 3R, 4R or equal 3R:4R ratio). Imaging, cerebrospinal fluid (CSF) and blood-based tau biomarkers have the potential to be used as a routine diagnostic strategy and in the evaluation of patients with tauopathies. As tauopathies are strongly linked neuropathologically and genetically to tau protein abnormalities, there is a growing interest in pursuing of tau-directed therapeutics for the disorders. Here we synthesize emerging lessons on tauopathies from clinical, pathological, genetic, and experimental studies toward a unified concept of these disorders that may accelerate the therapeutics. CONCLUSIONS Since tauopathies are still untreatable diseases, efforts have been made to depict clinical and pathological characteristics, identify biomarkers, elucidate underlying pathogenesis to achieve early diagnosis and develop disease-modifying therapies.
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Affiliation(s)
- Yi Zhang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai, 200040 China
| | - Kai-Min Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai, 200040 China
| | - Liu Yang
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai, 200040 China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai, 200040 China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, 12th Wulumuqi Zhong Road, Shanghai, 200040 China
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23
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Chun MY, Lee J, Jeong JH, Roh JH, Oh SJ, Oh M, Oh JS, Kim JS, Moon SH, Woo SY, Kim YJ, Choe YS, Kim HJ, Na DL, Jang H, Seo SW. 18F-THK5351 PET Positivity and Longitudinal Changes in Cognitive Function in β-Amyloid-Negative Amnestic Mild Cognitive Impairment. Yonsei Med J 2022; 63:259-264. [PMID: 35184428 PMCID: PMC8860937 DOI: 10.3349/ymj.2022.63.3.259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/05/2021] [Accepted: 12/07/2021] [Indexed: 11/27/2022] Open
Abstract
PURPOSE Neuroinflammation is considered an important pathway associated with several diseases that result in cognitive decline. 18F-THK5351 positron emission tomography (PET) signals might indicate the presence of neuroinflammation, as well as Alzheimer's disease-type tau aggregates. β-amyloid (Aβ)-negative (Aβ-) amnestic mild cognitive impairment (aMCI) may be associated with non-Alzheimer's disease pathophysiology. Accordingly, we investigated associations between 18F-THK5351 PET positivity and cognitive decline among Aβ- aMCI patients. MATERIALS AND METHODS The present study included 25 amyloid PET negative aMCI patients who underwent a minimum of two follow-up neuropsychological evaluations, including clinical dementia rating-sum of boxes (CDR-SOB). The patients were classified into two groups: 18F-THK5351-positive and -negative groups. The present study used a linear mixed effects model to estimate the effects of 18F-THK5351 PET positivity on cognitive prognosis among Aβ- aMCI patients. RESULTS Among the 25 Aβ- aMCI patients, 10 (40.0%) were 18F-THK5351 positive. The patients in the 18F-THK5351-positive group were older than those in the 18F-THK5351-negative group (77.4±2.2 years vs. 70.0±5.5 years; p<0.001). There was no difference between the two groups with regard to the proportion of apolipoprotein E ε4 carriers. Interestingly, however, the CDR-SOB scores of the 18F-THK5351-positive group deteriorated at a faster rate than those of the 18F-THK5351-negative group (B=0.003, p=0.033). CONCLUSION The results of the present study suggest that increased 18F-THK5351 uptake might be a useful predictor of poor prognosis among Aβ- aMCI patients, which might be associated with increased neuroinflammation (ClinicalTrials.gov NCT02656498).
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Affiliation(s)
- Min Young Chun
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jongmin Lee
- Department of Neurology, Myongji St. Mary's Hospital, Seoul, Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Seoul Hospital, Ewha Womans University College of Medicine, Seoul, Korea
| | - Jee Hoon Roh
- Department of Physiology, Korea University College of Medicine, Seoul, Korea
- Neuroscience Research Institute, Korea University College of Medicine, Seoul, Korea
| | - Seung Jun Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Minyoung Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jungsu S Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae Seung Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Seung Hwan Moon
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sook-Young Woo
- Biostatistics Team, Samsung Biomedical Research Institute, Seoul, Korea
| | - Young Ju Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University School of Medicine, Suwon, Korea.
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24
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Xu X, Ruan W, Liu F, Gai Y, Liu Q, Su Y, Liang Z, Sun X, Lan X. 18F-APN-1607 Tau Positron Emission Tomography Imaging for Evaluating Disease Progression in Alzheimer’s Disease. Front Aging Neurosci 2022; 13:789054. [PMID: 35221982 PMCID: PMC8868571 DOI: 10.3389/fnagi.2021.789054] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 12/20/2021] [Indexed: 12/31/2022] Open
Abstract
Purpose 18F-APN-1607 is a novel tau positron emission tomography (PET) tracer characterized with high binding affinity for 3− and 4-repeat tau deposits. The aim was to analyze the spatial distribution of 18F-APN-1607 PET imaging in Alzheimer’s disease (AD) subjects with different stages and to investigate the relationship between the change of tau deposition and overall disease progression. Methods We retrospectively analyzed the 18F-APN-1607 PET imaging of 31 subjects with clinically and imaging defined as AD. According to the Mini-Mental State Examination (MMSE) score, patients were divided into three groups, namely, mild (≥21, n = 7), moderate (10–20, n = 16), and severe (≤9, n = 8). PET imaging was segmented to 70 regions of interest (ROIs) and extracted the standard uptake value (SUV) of each ROI. SUV ratio (SUVR) was calculated from the ratio of SUV in different brain regions to the cerebellar cortex. The regions were defined as positive and negative with unsupervised cluster analysis according to SUVR. The SUVRs of each region were compared among groups with the one-way ANOVA or Kruskal–Wallis H test. Furthermore, the correlations between MMSE score and regional SUVR were calculated with Pearson or Spearman correlation analysis. Results There were no significant differences among groups in gender (χ2 = 3.814, P = 0.161), age of onset (P = 0.170), age (P = 0.109), and education level (P = 0.065). With the disease progression, the 18F-APN-1607 PET imaging showed the spread of tau deposition from the hippocampus, posterior cingulate gyrus (PCG), and lateral temporal cortex (LTC) to the parietal and occipital lobes, and finally to the frontal lobe. Between the mild and moderate groups, the main brain areas with significant differences in 18F-APN-1607 uptake were supplementary motor area (SMA), cuneus, precuneus, occipital lobule, paracentral lobule, right angular gyrus, and parietal, which could be used for early disease progression assessment (P < 0.05). There were significant differences in the frontal lobe, right temporal lobe, and fusiform gyrus between the moderate and severe groups, which might be suitable for the late-stage disease progression assessment (P < 0.05). Conclusion 18F-APN-1607 PET may serve as an effective imaging marker for visualizing the change pattern of tau protein deposition in AD patients, and its uptake level in certain brain regions is closely related to the severity of cognitive impairment. These indicate the potential of 18F-APN-1607 PET for the in vivo evaluation of the progression of AD.
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Affiliation(s)
- Xiaojun Xu
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Weiwei Ruan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Fang Liu
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Yongkang Gai
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Qingyao Liu
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
| | - Ying Su
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhihou Liang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xun Sun
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- *Correspondence: Xun Sun,
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
- Xiaoli Lan,
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25
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Dartora CM, Borelli WV, Koole M, Marques da Silva AM. Cognitive Decline Assessment: A Review From Medical Imaging Perspective. Front Aging Neurosci 2021; 13:704661. [PMID: 34489675 PMCID: PMC8416532 DOI: 10.3389/fnagi.2021.704661] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
Aging is a complex process that involves changes at both molecular and morphological levels. However, our understanding of how aging affects brain anatomy and function is still poor. In addition, numerous biomarkers and imaging markers, usually associated with neurodegenerative diseases such as Alzheimer's disease (AD), have been clinically used to study cognitive decline. However, the path of cognitive decline from healthy aging to a mild cognitive impairment (MCI) stage has been studied only marginally. This review presents aspects of cognitive decline assessment based on the imaging differences between individuals cognitively unimpaired and in the decline spectrum. Furthermore, we discuss the relationship between imaging markers and the change in their patterns with aging by using neuropsychological tests. Our goal is to delineate how aging has been studied by using medical imaging tools and further explore the aging brain and cognitive decline. We find no consensus among the biomarkers to assess the cognitive decline and its relationship with the cognitive decline trajectory. Brain glucose hypometabolism was found to be directly related to aging and indirectly to cognitive decline. We still need to understand how to quantify an expected hypometabolism during cognitive decline during aging. The Aβ burden should be longitudinally studied to achieve a better consensus on its association with changes in the brain and cognition decline with aging. There exists a lack of standardization of imaging markers that highlight the need for their further improvement. In conclusion, we argue that there is a lot to investigate and understand cognitive decline better and seek a window for a suitable and effective treatment strategy.
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Affiliation(s)
- Caroline Machado Dartora
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
| | - Wyllians Vendramini Borelli
- Neurology Department, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Ana Maria Marques da Silva
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil.,Medical Image Computing Laboratory, School of Technology, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
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26
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Ossenkoppele R, Reimand J, Smith R, Leuzy A, Strandberg O, Palmqvist S, Stomrud E, Zetterberg H, Scheltens P, Dage JL, Bouwman F, Blennow K, Mattsson-Carlgren N, Janelidze S, Hansson O. Tau PET correlates with different Alzheimer's disease-related features compared to CSF and plasma p-tau biomarkers. EMBO Mol Med 2021; 13:e14398. [PMID: 34254442 PMCID: PMC8350902 DOI: 10.15252/emmm.202114398] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 12/13/2022] Open
Abstract
PET, CSF and plasma biomarkers of tau pathology may be differentially associated with Alzheimer's disease (AD)‐related demographic, cognitive, genetic and neuroimaging markers. We examined 771 participants with normal cognition, mild cognitive impairment or dementia from BioFINDER‐2 (n = 400) and ADNI (n = 371). All had tau‐PET ([18F]RO948 in BioFINDER‐2, [18F]flortaucipir in ADNI) and CSF p‐tau181 biomarkers available. Plasma p‐tau181 and plasma/CSF p‐tau217 were available in BioFINDER‐2 only. Concordance between PET, CSF and plasma tau biomarkers ranged between 66 and 95%. Across the whole group, ridge regression models showed that increased CSF and plasma p‐tau181 and p‐tau217 levels were independently of tau PET associated with higher age, and APOEɛ4‐carriership and Aβ‐positivity, while increased tau‐PET signal in the temporal cortex was associated with worse cognitive performance and reduced cortical thickness. We conclude that biofluid and neuroimaging markers of tau pathology convey partly independent information, with CSF and plasma p‐tau181 and p‐tau217 levels being more tightly linked with early markers of AD (especially Aβ‐pathology), while tau‐PET shows the strongest associations with cognitive and neurodegenerative markers of disease progression.
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Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Juhan Reimand
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Health Technologies, Tallinn University of Technology, Tallinn, Estonia.,Radiology Centre, North Estonia Medical Centre, Tallinn, Estonia
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - 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, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | | - Femke Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - 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, 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
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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27
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Raber J, Perez R, Torres ERS, Krenik D, Boutros S, Patel E, Chlebowski AC, Torres ER, Perveen Z, Penn A, Paulsen DB, Bartlett MG, Jia E, Holden S, Hall R, Morré J, Wong C, Ho E, Choi J, Stevens JF, Noël A, Bobe G, Kisby G. Effects of Chronic Secondhand Smoke (SHS) Exposure on Cognitive Performance and Metabolic Pathways in the Hippocampus of Wild-Type and Human Tau Mice. ENVIRONMENTAL HEALTH PERSPECTIVES 2021; 129:57009. [PMID: 34009016 PMCID: PMC8132614 DOI: 10.1289/ehp8428] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
BACKGROUND Exposure to secondhand smoke (SHS) is a risk factor for developing sporadic forms of sporadic dementia. A human tau (htau) mouse model is available that exhibits age-dependent tau dysregulation, neurofibrillary tangles, neuronal loss, neuroinflammation, and oxidative stress starting at an early age (3-4 months) and in which tau dysregulation and neuronal loss correlate with synaptic dysfunction and cognitive decline. OBJECTIVE The goal of this study was to assess the effects of chronic SHS exposure (10 months' exposure to ∼30 mg/m3) on behavioral and cognitive function, metabolism, and neuropathology in mice. METHODS Wild-type (WT) and htau female and male mice were exposed to SHS (90% side stream, 10% main stream) using the SCIREQ® inExpose™ system or air control for 168 min per day, for 312 d, 7 d per week. The exposures continued during the days of behavioral and cognitive testing. In addition to behavioral and cognitive performance and neuropathology, the lungs of mice were examined for pathology and alterations in gene expression. RESULTS Mice exposed to chronic SHS exposure showed the following genotype-dependent responses: a) lower body weights in WT, but not htau, mice; b) less spontaneous alternation in WT, but not htau, mice in the Y maze; c) faster swim speeds of WT, but not htau, mice in the water maze; d) lower activity levels of WT and htau mice in the open field; e) lower expression of brain PHF1, TTCM1, IGF1β, and HSP90 protein levels in WT male, but not female, mice; and f) more profound effects on hippocampal metabolic pathways in WT male than female mice and more profound effects in WT than htau mice. DISCUSSION The brain of WT mice, in particular WT male mice, might be especially susceptible to the effects of chronic SHS exposure. In WT males, independent pathways involving ascorbate, flavin adenine dinucleotide, or palmitoleic acid might contribute to the hippocampal injury following chronic SHS exposure. https://doi.org/10.1289/EHP8428.
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Affiliation(s)
- Jacob Raber
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
- Departments of Neurology, Psychiatry, and Radiation Medicine, Division of Neuroscience ONPRC, Oregon Health & Science University, Portland, Oregon, USA
- College of Pharmacy, Oregon State University, Corvallis, Oregon, USA
| | - Ruby Perez
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Eileen Ruth S. Torres
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Destine Krenik
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Sydney Boutros
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Esha Patel
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Anna C. Chlebowski
- Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA
| | - Estefania Ramos Torres
- Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA
| | - Zakia Perveen
- Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA
| | - Arthur Penn
- Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA
| | - Daniel B. Paulsen
- Department of Pathobiological Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA
| | | | - Enze Jia
- University of Georgia, College of Pharmacy, Athens, Georgia, USA
| | - Sarah Holden
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Reed Hall
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Jeffrey Morré
- Mass Spectrometry Core, Oregon State University, Corvallis, Oregon, USA
| | - Carmen Wong
- Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA
- Department of Animal Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Emily Ho
- Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon, USA
| | - Jaewoo Choi
- Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA
| | - Jan Frederik Stevens
- College of Pharmacy, Oregon State University, Corvallis, Oregon, USA
- Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA
| | - Alexandra Noël
- Department of Comparative Biomedical Sciences, Louisiana State University School of Veterinary Medicine, Baton Rouge, Louisiana, USA
| | - Gerd Bobe
- Mass Spectrometry Core, Oregon State University, Corvallis, Oregon, USA
- Linus Pauling Institute, Oregon State University, Corvallis, Oregon, USA
| | - Glen Kisby
- Department of Basic Medical Sciences, Western University of Health Sciences, College of Osteopathic Medicine of the Pacific Northwest, Lebanon, Oregon, USA
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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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