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Li M, Li Y, Schindler SE, Yen D, Sutcliffe S, Babulal GM, Benzinger TL, Lenze EJ, Bateman RJ. Design and feasibility of an Alzheimer's disease blood test study in a diverse community-based population. Alzheimers Dement 2023; 19:5387-5398. [PMID: 37204806 PMCID: PMC10657331 DOI: 10.1002/alz.13125] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/06/2023] [Accepted: 04/07/2023] [Indexed: 05/20/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) blood tests are likely to become increasingly important in clinical practice, but they need to be evaluated in diverse groups before use in the general population. METHODS This study enrolled a community-based sample of older adults in the St. Louis, Missouri, USA area. Participants completed a blood draw, Eight-Item Informant Interview to Differentiate Aging and Dementia (AD8® ), Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), and Clinical Dementia Rating (CDR® ). RESULTS Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well accepted by the cohort, but it was perceived more positively by White and highly educated individuals. DISCUSSION Studying an AD blood test in a diverse population is feasible and may accelerate accurate diagnosis and implementation of effective treatments. HIGHLIGHTS A diverse group of older adults was recruited to evaluate a blood amyloid test. The enrollment rate was high and the blood test was well accepted by participants. Cognitive impairment screens have moderate performance in a diverse population. Alzheimer's disease blood tests are likely to be feasible for use in real-world settings.
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Affiliation(s)
- Melody Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Daniel Yen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Siobhan Sutcliffe
- Department of Surgery – Public Health Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Ganesh M. Babulal
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Eric J. Lenze
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- The Tracy Family Stable Isotope Labeling Quantitation Center for Neurodegenerative Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
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Dybing KM, Vetter CJ, Dempsey DA, Chaudhuri S, Saykin AJ, Risacher SL. Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET). MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.30.23298528. [PMID: 38077068 PMCID: PMC10705648 DOI: 10.1101/2023.11.30.23298528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.
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Affiliation(s)
- Kaitlyn M. Dybing
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Cecelia J. Vetter
- Ruth Lilly Medical Library, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Desarae A. Dempsey
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Soumilee Chaudhuri
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
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103
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Myburgh PJ, Moore MD, Pathirannahel BL, Grace LR, Solingapuram Sai KK. Fully automated production of [ 11C]PiB for clinical use on Trasis-AllinOne synthesizer module. Appl Radiat Isot 2023; 202:111040. [PMID: 37788544 PMCID: PMC10727203 DOI: 10.1016/j.apradiso.2023.111040] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 09/21/2023] [Accepted: 09/22/2023] [Indexed: 10/05/2023]
Abstract
Pittsburgh compound B ([11C]PiB) was the first broadly applied radiotracer with specificity for amyloid-β (Aβ) peptide aggregates in the brain and has since been established as the gold standard for positron emission tomography (PET) employed for clinical in vivo imaging of Aβ plaques, used for imaging applications of Alzheimer's disease (AD), related dementia, and other tauopathies. The use of [11C]PiB for routine PET studies is dependent on the production capabilities of each radiochemistry laboratory, subsequently a continuous effort is made to develop suitable and sustainable methods on a variety of auto synthesis platforms. Here we report a fully automated, multi-step radio synthesis, purification, and reformulation of [11C]PiB for PET imaging using the Trasis AllinOne synthesis unit, a commonly used commercial radiochemistry module. We performed three validation runs to evaluate the reproducibility and to verify that the acceptable criteria were met for the release of clinical-grade [11C]PiB using a Trasis AllinOne auto radiosynthesis unit. Solid phase supported radiolabeling was performed through the capture of precursor (6-OH-BTA-0) on a C18 solid phase extraction (SPE) cartridge and subsequent flushing of gaseous [11C]Methyl triflate(MeOTf) through the Sep-Pak for carbon-11 (11C) N-methylation. Starting with 92.5 GBq [11C]CO2, [11C]PiB synthesis was completed in approximately 25 min after cyclotron end of bombardment with an injectable dose >7.0 GBq at end of the synthesis. The radiopharmaceutical product met all quality control criteria and specifications for use in human studies.
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Affiliation(s)
- Paul Josef Myburgh
- Translational Imaging Program, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA
| | - Michael David Moore
- Translational Imaging Program, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA
| | | | - Laura Rose Grace
- Translational Imaging Program, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA
| | - Kiran Kumar Solingapuram Sai
- Translational Imaging Program, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA; Department of Radiology, Atrium Health Wake Forest Baptist Medical Center, Winston-Salem, NC, 27157, USA.
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Li C, Chen Z, He S, Chen Y, Liu J. Unveiling the influence of daily dietary patterns on brain cortical structure: insights from bidirectional Mendelian randomization. Food Funct 2023; 14:10418-10429. [PMID: 37960880 DOI: 10.1039/d3fo02879h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Cognitive impairment is a significant concern in aging populations. This study utilized Mendelian randomization analysis to explore the impact of dietary habits and macro-nutrients on cortical structure. A bidirectional Mendelian randomization approach was employed, incorporating large-scale genetic data on dietary habits and brain cortical structure. The results did not reveal significant causal relationships between dietary factors and overall cortical structure and thickness. However, specific dietary factors showed associations with cortical structure in certain regions. For instance, fat intake affected six cortical regions, while milk, protein, fruits, and water were associated with changes in specific regions. Reverse analysis suggested that cortical thickness influenced the consumption of alcohol, carbohydrates, coffee, and fish. These findings contribute to understanding the potential mechanisms underlying the role of dietary factors in cognitive function changes and provide evidence supporting the existence of the gut-brain axis.
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Affiliation(s)
- Cong Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
| | - Zhe Chen
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
| | - Shaqi He
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
| | - Yanjing Chen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
| | - Jun Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.
- Clinical Research Center for Medical Imaging in Hunan Province, Changsha, Hunan Province, 410011, People's Republic of China
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105
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Giannopoulou P, Vrahatis AG, Papalaskari MA, Vlamos P. The RODI mHealth app Insight: Machine-Learning-Driven Identification of Digital Indicators for Neurodegenerative Disorder Detection. Healthcare (Basel) 2023; 11:2985. [PMID: 37998477 PMCID: PMC10671821 DOI: 10.3390/healthcare11222985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 11/15/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023] Open
Abstract
Neurocognitive Disorders (NCDs) pose a significant global health concern, and early detection is crucial for optimizing therapeutic outcomes. In parallel, mobile health apps (mHealth apps) have emerged as a promising avenue for assisting individuals with cognitive deficits. Under this perspective, we pioneered the development of the RODI mHealth app, a unique method for detecting aligned with the criteria for NCDs using a series of brief tasks. Utilizing the RODI app, we conducted a study from July to October 2022 involving 182 individuals with NCDs and healthy participants. The study aimed to assess performance differences between healthy older adults and NCD patients, identify significant performance disparities during the initial administration of the RODI app, and determine critical features for outcome prediction. Subsequently, the results underwent machine learning processes to unveil underlying patterns associated with NCDs. We prioritize the tasks within RODI based on their alignment with the criteria for NCDs, thus acting as key digital indicators for the disorder. We achieve this by employing an ensemble strategy that leverages the feature importance mechanism from three contemporary classification algorithms. Our analysis revealed that tasks related to visual working memory were the most significant in distinguishing between healthy individuals and those with an NCD. On the other hand, processes involving mental calculations, executive working memory, and recall were less influential in the detection process. Our study serves as a blueprint for future mHealth apps, offering a guide for enhancing the detection of digital indicators for disorders and related conditions.
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Affiliation(s)
- Panagiota Giannopoulou
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
| | - Aristidis G. Vrahatis
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
| | | | - Panagiotis Vlamos
- Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, 49100 Corfu, Greece; (P.G.); (A.G.V.)
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Pittock RR, Aakre JA, Castillo AM, Ramanan VK, Kremers WK, Jack CR, Vemuri P, Lowe VJ, Knopman DS, Petersen RC, Graff-Radford J, Vassilaki M. Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging. Neurology 2023; 101:e1837-e1849. [PMID: 37586881 PMCID: PMC10663008 DOI: 10.1212/wnl.0000000000207770] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-β-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-β-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-β-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants. METHODS This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment. RESULTS Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings. DISCUSSION Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-β-amyloid mAbs.
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Affiliation(s)
- Rioghna R Pittock
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jeremiah A Aakre
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Anna M Castillo
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Vijay K Ramanan
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Walter K Kremers
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Maria Vassilaki
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN.
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Björk L, Shirani H, Todarwal Y, Linares M, Vidal R, Ghetti B, Norman P, Klingstedt T, Nilsson KPR. Distinct Heterocyclic Moieties Govern the Selectivity of Thiophene-Vinylene-Based Ligands Towards Aβ or Tau Pathology in Alzheime's Disease. European J Org Chem 2023; 26:e202300583. [PMID: 38585413 PMCID: PMC10997339 DOI: 10.1002/ejoc.202300583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Indexed: 04/09/2024]
Abstract
Distinct aggregated proteins are correlated with numerous neurodegenerative diseases and the development of ligands that selectively detect these pathological hallmarks is vital. Recently, the synthesis of thiophene-based optical ligands, denoted bi-thiophene-vinyl-benzothiazoles (bTVBTs), that could be utilized for selective assignment of tau pathology in brain tissue with Alzheime's disease (AD) pathology, was reported. Herein, we investigate the ability of these ligands to selectively distinguish tau deposits from aggregated amyloid-β (Aβ), the second AD associated pathological hallmark, when replacing the terminal thiophene moiety with other heterocyclic motifs. The selectivity for tau pathology was reduced when introducing specific heterocyclic motifs, verifying that specific molecular interactions between the ligands and the aggregates are necessary for selective detection of tau deposits. In addition, ligands having certain heterocyclic moieties attached to the central thiophene-vinylene building block displayed selectivity to aggregated Aβ pathology. Our findings provide chemical insights for the development of ligands that can distinguish between aggregated proteinaceous species consisting of different proteins and might also aid in creating novel agents for clinical imaging of tau pathology in AD.
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Affiliation(s)
- Linnea Björk
- Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden
| | - Hamid Shirani
- Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden
| | - Yogesh Todarwal
- Division of Theoretical Chemistry and Biology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, SE-106 91, Stockholm, Sweden
| | - Mathieu Linares
- Division of Theoretical Chemistry and Biology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, SE-106 91, Stockholm, Sweden
| | - Ruben Vidal
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, 46202 Indiana, USA
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, 46202 Indiana, USA
| | - Patrick Norman
- Division of Theoretical Chemistry and Biology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, SE-106 91, Stockholm, Sweden
| | - Therése Klingstedt
- Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden
| | - K Peter R Nilsson
- Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden
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108
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Oeckl P, Bluma M, Bucci M, Halbgebauer S, Chiotis K, Sandebring-Matton A, Ashton NJ, Molfetta GD, Grötschel L, Kivipelto M, Blennow K, Zetterberg H, Savitcheva I, Nordberg A, Otto M. Blood β-synuclein is related to amyloid PET positivity in memory clinic patients. Alzheimers Dement 2023; 19:4896-4907. [PMID: 37052206 DOI: 10.1002/alz.13046] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 04/14/2023]
Abstract
INTRODUCTION β-synuclein is an emerging blood biomarker to study synaptic degeneration in Alzheimer´s disease (AD), but its relation to amyloid-β (Αβ) pathology is unclear. METHODS We investigated the association of plasma β-synuclein levels with [18F] flutemetamol positron emission tomography (PET) in patients with AD dementia (n = 51), mild cognitive impairment (MCI-Aβ+ n = 18, MCI- Aβ- n = 30), non-AD dementias (n = 22), and non-demented controls (n = 5). RESULTS Plasma β-synuclein levels were higher in Aβ+ (AD dementia, MCI-Aβ+) than in Aβ- subjects (non-AD dementias, MCI-Aβ-) with good discrimination of Aβ+ from Aβ- subjects and prediction of Aβ status in MCI individuals. A positive correlation between plasma β-synuclein and Aβ PET was observed in multiple cortical regions across all lobes. DISCUSSION Plasma β-synuclein demonstrated discriminative properties for Aβ PET positive and negative subjects. Our data underline that β-synuclein is not a direct marker of Aβ pathology and suggest different longitudinal dynamics of synaptic degeneration versus amyloid deposition across the AD continuum. HIGHLIGHTS Blood and CSF β-synuclein levels are higher in Aβ+ than in Aβ- subjects. Blood β-synuclein level correlates with amyloid PET positivity in multiple regions. Blood β-synuclein predicts Aβ status in MCI individuals.
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Affiliation(s)
- Patrick Oeckl
- German Center for Neurodegenerative Diseases e.V. (DZNE), Ulm, Germany
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Steffen Halbgebauer
- German Center for Neurodegenerative Diseases e.V. (DZNE), Ulm, Germany
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Sandebring-Matton
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Lana Grötschel
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - 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
| | - 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, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, Stockholm, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Markus Otto
- Department of Neurology, Ulm University Hospital, Ulm, Germany
- University Clinic and Polyclinic for Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
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Eraslan Boz H, Koçoğlu K, Akkoyun M, Tüfekci IY, Ekin M, Akdal G. Eye movement patterns during viewing face images with neutral expressions in patients with early-stage Alzheimer's disease and amnestic mild cognitive impairment. Brain Behav 2023; 13:e3232. [PMID: 37605291 PMCID: PMC10636417 DOI: 10.1002/brb3.3232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) neuropathology affects the brain regions responsible for visuospatial skills. Accumulating evidence points to visual difficulties involving face processing in AD and amnestic mild cognitive impairment (aMCI). No study has so far examined eye movement patterns when viewing faces with neutral expressions in patients with AD. AIM The objective of this study aimed to examine the eye movements of patients with early-stage AD, aMCI, and healthy controls (HC) during viewing face images. MATERIALS&METHODS Thirty-one AD, 37 aMCI, and 33 HC were included in the study. Eye movements in facial stimuli were recorded with the EyeLink 1000 Plus eye-tracker. RESULTS Our findings showed that AD patients looked less at the eye area of interest than the nose and mouth areas of interest compared to aMCI and HC. Regardless of the group, all participants looked at the eye and nose areas of interest more and longer in the mouth area of interest. In addition, the first fixation duration to the eye area of interest of all participants was shorter than that of the nose and mouth. DISCUSSION Consistent with our study, studies in healthy adults revealed eye movement patterns that focused more on the eyes and nose. AD patients are unable to pay attention to the salient parts of faces, tending to focus instead on the non-informative parts. CONCLUSION Our study is the first to reveal eye movement differences in face processing in AD.
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Affiliation(s)
- Hatice Eraslan Boz
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
- Department of Neurology, Unit of NeuropsychologyDokuz Eylül UniversityIzmirTürkiye
| | - Koray Koçoğlu
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
| | - Müge Akkoyun
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
| | - Işıl Yağmur Tüfekci
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
| | - Merve Ekin
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
| | - Gülden Akdal
- Department of Neurosciences, Institute of Health SciencesDokuz Eylül UniversityIzmirTürkiye
- Department of NeurologyDokuz Eylül UniversityIzmirTürkiye
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110
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Smith MS, Knight IS, Kormos RC, Pepe JG, Kunach P, Diamond MI, Shahmoradian SH, Irwin JJ, DeGrado WF, Shoichet BK. Docking for molecules that bind in a symmetric stack with SymDOCK. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.27.564400. [PMID: 37961414 PMCID: PMC10634874 DOI: 10.1101/2023.10.27.564400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Discovering ligands for amyloid fibrils, such as those formed by the tau protein, is an area of much current interest. In recent structures, ligands bind in stacks in the tau fibrils to reflect the rotational and translational symmetry of the fibril itself; in these structures the ligands make few interactions with the protein but interact extensively with each other. To exploit this symmetry and stacking, we developed SymDOCK, a method to dock molecules that follow the protein's symmetry. For each prospective ligand pose, we apply the symmetry operation of the fibril to generate a self-interacting and fibril-interacting stack, checking that doing so will not cause a clash between the original molecule and its image. Absent a clash, we retain that pose and add the ligand-ligand van der Waals energy to the ligand's docking score (here using DOCK3.8). We can check these geometries and energies using an implementation of ANI, a neural network-based quantum-mechanical evaluation of the ligand stacking energies. In retrospective calculations, symmetry docking can reproduce the poses of three tau PET tracers whose structures have been determined. More convincingly, in a prospective study SymDOCK predicted the structure of the PET tracer MK-6240 bound in a symmetrical stack to AD PHF tau before that structure was determined; the docked pose was used to determine how MK-6240 fit the cryo-EM density. In proof-of-concept studies, SymDOCK enriched known ligands over property-matched decoys in retrospective screens without sacrificing docking speed, and can address large library screens that seek new symmetrical stackers. Future applications of this approach will be considered.
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Affiliation(s)
- Matthew S. Smith
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Ian S. Knight
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - Rian C. Kormos
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph G. Pepe
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Program in Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Peter Kunach
- McGill Research Centre for Studies in Aging, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marc I. Diamond
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sarah H. Shahmoradian
- Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - John J. Irwin
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
| | - William F. DeGrado
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA
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Tagmazian AA, Schwarz C, Lange C, Pitkänen E, Vuoksimaa E. ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid-beta from amyloid PET images. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.20.545686. [PMID: 37425778 PMCID: PMC10327176 DOI: 10.1101/2023.06.20.545686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Detection and measurement of amyloid-beta (Aβ) aggregation in the brain is a key factor for early identification and diagnosis of Alzheimer's disease (AD). We aimed to develop a deep learning model to predict Aβ cerebrospinal fluid (CSF) concentration directly from amyloid PET images, independent of tracers, brain reference regions or preselected regions of interest. We used 1870 Aβ PET images and CSF measurements to train and validate a convolutional neural network ("ArcheD"). We evaluated the ArcheD performance in relation to episodic memory and the standardized uptake value ratio (SUVR) of cortical Aβ. We also compared the brain region's relevance for the model's CSF prediction within clinical-based and biological-based classifications. ArcheD-predicted Aβ CSF values correlated strongly with measured Aβ CSF values ( r =0.81; p <0.001) and showed correlations with SUVR and episodic memory measures in all participants except in those with AD. For both clinical and biological classifications, cerebral white matter significantly contributed to CSF prediction ( q <0.01), specifically in non-symptomatic and early stages of AD. However, in late-stage disease, brain stem, subcortical areas, cortical lobes, limbic lobe, and basal forebrain made more significant contributions (q<0.01). Considering cortical gray matter separately, the parietal lobe was the strongest predictor of CSF amyloid levels in those with prodromal or early AD, while the temporal lobe played a more crucial role for those with AD. In summary, ArcheD reliably predicted Aβ CSF concentration from Aβ PET scans, offering potential clinical utility for Aβ level determination and early AD detection.
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Martínez-Dubarbie F, Guerra-Ruiz A, López-García S, Lage C, Fernández-Matarrubia M, Infante J, Pozueta-Cantudo A, García-Martínez M, Corrales-Pardo A, Bravo M, López-Hoyos M, Irure-Ventura J, Sánchez-Juan P, García-Unzueta MT, Rodríguez-Rodríguez E. Accuracy of plasma Aβ40, Aβ42, and p-tau181 to detect CSF Alzheimer's pathological changes in cognitively unimpaired subjects using the Lumipulse automated platform. Alzheimers Res Ther 2023; 15:163. [PMID: 37784138 PMCID: PMC10544460 DOI: 10.1186/s13195-023-01319-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 09/27/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND The arrival of new disease-modifying treatments for Alzheimer's disease (AD) requires the identification of subjects at risk in a simple, inexpensive, and non-invasive way. With tools allowing an adequate screening, it would be possible to optimize the use of these treatments. Plasma markers of AD are very promising, but it is necessary to prove that alterations in their levels are related to alterations in gold standard markers such as cerebrospinal fluid or PET imaging. With this research, we want to evaluate the performance of plasma Aβ40, Aβ42, and p-tau181 to detect the pathological changes in CSF using the automated Lumipulse platform. METHODS Both plasma and CSF Aβ40, Aβ42, and p-tau181 have been evaluated in a group of 208 cognitively unimpaired subjects with a 30.3% of ApoE4 carriers. We have correlated plasma and CSF values of each biomarker. Then, we have also assessed the differences in plasma marker values according to amyloid status (A - / +), AD status (considering AD + subjects to those A + plus Tau +), and ATN group defined by CSF. Finally, ROC curves have been performed, and the area under the curve has been measured using amyloid status and AD status as an outcome and different combinations of plasma markers as predictors. RESULTS Aβ42, amyloid ratio, p-tau181, and p-tau181/Aβ42 ratio correlated significantly between plasma and CSF. For these markers, the levels were significantly different in the A + / - , AD + / - , and ATN groups. Amyloid ratio predicts amyloid and AD pathology in CSF with an AUC of 0.89. CONCLUSIONS Plasma biomarkers of AD using the automated Lumipulse platform show good diagnostic performance in detecting Alzheimer's pathology in cognitively unimpaired subjects.
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Affiliation(s)
- Francisco Martínez-Dubarbie
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain.
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain.
| | - Armando Guerra-Ruiz
- Biochemistry and Clinical Analysis Department, Marqués de Valdecilla University Hospital, Santander, Cantabria, 39008, Spain
| | - Sara López-García
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
| | - Carmen Lage
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, University of California, San Francisco, San Francisco, USA
| | - Marta Fernández-Matarrubia
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
| | - Jon Infante
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28220, Spain
- Medicine and Psychiatry Department, University of Cantabria, Santander, Spain
| | - Ana Pozueta-Cantudo
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
| | - María García-Martínez
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
| | - Andrea Corrales-Pardo
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- Universidad Europea del Atlántico, Santander, Spain
| | - María Bravo
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
| | - Marcos López-Hoyos
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- Immunology Department, Marqués de Valdecilla University Hospital, Santander, Spain
- Molecular Biology Department, University of Cantabria, Santander, Spain
| | - Juan Irure-Ventura
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- Immunology Department, Marqués de Valdecilla University Hospital, Santander, Spain
| | - Pascual Sánchez-Juan
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28220, Spain
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, 28220, Spain
| | - María Teresa García-Unzueta
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- Biochemistry and Clinical Analysis Department, Marqués de Valdecilla University Hospital, Santander, Cantabria, 39008, Spain
| | - Eloy Rodríguez-Rodríguez
- Neurology Service, Marqués de Valdecilla University Hospital, Avda. de Valdecilla 25, Santander, Cantabria, 39008, Spain
- Institute for Research Marqués de Valdecilla (IDIVAL), Santander, Cantabria, 39011, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28220, Spain
- Medicine and Psychiatry Department, University of Cantabria, Santander, Spain
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Tao Y, Xia W, Zhao Q, Xiang H, Han C, Zhang S, Gu W, Tang W, Li Y, Tan L, Li D, Liu C. Structural mechanism for specific binding of chemical compounds to amyloid fibrils. Nat Chem Biol 2023; 19:1235-1245. [PMID: 37400537 DOI: 10.1038/s41589-023-01370-x] [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: 09/08/2022] [Accepted: 05/26/2023] [Indexed: 07/05/2023]
Abstract
Amyloid fibril is an important pharmaceutical target for diagnostic and therapeutic treatment of neurodegenerative diseases. However, rational design of chemical compounds that interact with amyloid fibrils is unachievable due to the lack of mechanistic understanding of the ligand-fibril interaction. Here we used cryoelectron microscopy to survey the amyloid fibril-binding mechanism of a series of compounds including classic dyes, (pre)clinical imaging tracers and newly identified binders from high-throughput screening. We obtained clear densities of several compounds in complex with an α-synuclein fibril. These structures unveil the basic mechanism of the ligand-fibril interaction, which exhibits remarkable difference from the canonical ligand-protein interaction. In addition, we discovered a druggable pocket that is also conserved in the ex vivo α-synuclein fibrils from multiple system atrophy. Collectively, these findings expand our knowledge of protein-ligand interaction in the amyloid fibril state, which will enable rational design of amyloid binders in a medicinally beneficial way.
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Affiliation(s)
- Youqi Tao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, China
| | - Wencheng Xia
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Qinyue Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, China
| | - Huaijiang Xiang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Chao Han
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Shenqing Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Gu
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Wenjun Tang
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
| | - Ying Li
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Li Tan
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Dan Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, China.
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
- University of the Chinese Academy of Sciences, Beijing, China.
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
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114
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Ferreira PCL, Zhang Y, Snitz B, Chang CCH, Bellaver B, Jacobsen E, Kamboh MI, Zetterberg H, Blennow K, Pascoal TA, Villemagne VL, Ganguli M, Karikari TK. Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort. Alzheimers Dement 2023; 19:4507-4519. [PMID: 36876954 PMCID: PMC10480336 DOI: 10.1002/alz.12986] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/12/2023] [Accepted: 01/15/2023] [Indexed: 03/07/2023]
Abstract
INTRODUCTION Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers. METHODS We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania. RESULTS K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group. DISCUSSION Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening. HIGHLIGHTS Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.
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Affiliation(s)
- Pamela C. L Ferreira
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Yingjin Zhang
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Beth Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Chung-Chou H. Chang
- Department of Biostatistics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Bruna Bellaver
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Erin Jacobsen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - M. Ilyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, HKG, China
- UW Department of Medicine, School of Medicine and Public Health, Madison, WI, 53726, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Tharick A. Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Victor L. Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Mary Ganguli
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Thomas K. Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, 431 41, Sweden
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Ferreira PCL, Therriault J, Tissot C, Ferrari-Souza JP, Benedet AL, Povala G, Bellaver B, Leffa DT, Brum WS, Lussier FZ, Bezgin G, Servaes S, Vermeiren M, Macedo AC, Cabrera A, Stevenson J, Triana-Baltzer G, Kolb H, Rahmouni N, Klunk WE, Lopez O, Villemagne VL, Cohen A, Tudorascu DL, Zimmer ER, Karikari TK, Ashton NJ, Zetterberg H, Blennow K, Gauthier S, Rosa-Neto P, Pascoal TA. Plasma p-tau231 and p-tau217 inform on tau tangles aggregation in cognitively impaired individuals. Alzheimers Dement 2023; 19:4463-4474. [PMID: 37534889 PMCID: PMC10592380 DOI: 10.1002/alz.13393] [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: 02/24/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 08/04/2023]
Abstract
INTRODUCTION Phosphorylated tau (p-tau) biomarkers have been recently proposed to represent brain amyloid-β (Aβ) pathology. Here, we evaluated the plasma biomarkers' contribution beyond the information provided by demographics (age and sex) to identify Aβ and tau pathologies in individuals segregated as cognitively unimpaired (CU) and impaired (CI). METHODS We assessed 138 CU and 87 CI with available plasma p-tau231, 217+ , and 181, Aβ42/40, GFAP and Aβ- and tau-PET. RESULTS In CU, only plasma p-tau231 and p-tau217+ significantly improved the performance of the demographics in detecting Aβ-PET positivity, while no plasma biomarker provided additional information to identify tau-PET positivity. In CI, p-tau217+ and GFAP significantly contributed to demographics to identify both Aβ-PET and tau-PET positivity, while p-tau231 only provided additional information to identify tau-PET positivity. DISCUSSION Our results support plasma p-tau231 and p-tau217+ as state markers of early Aβ deposition, but in later disease stages they inform on tau tangle accumulation. HIGHLIGHTS It is still unclear how much plasma biomarkers contribute to identification of AD pathology across the AD spectrum beyond the information already provided by demographics (age + sex). Plasma p-tau231 and p-tau217+ contribute to demographic information to identify brain Aβ pathology in preclinical AD. In CI individuals, plasma p-tau231 contributes to age and sex to inform on the accumulation of tau tangles, while p-tau217+ and GFAP inform on both Aβ deposition and tau pathology.
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Affiliation(s)
- Pamela C. L Ferreira
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Cécile Tissot
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - João Pedro Ferrari-Souza
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Andréa L. Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Guilherme Povala
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Bruna Bellaver
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Douglas T. Leffa
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Wagner S. Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Firoza Z. Lussier
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Marie Vermeiren
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arthur C. Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arlec Cabrera
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - William E. Klunk
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar Lopez
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Victor L. Villemagne
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Ann Cohen
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L. Tudorascu
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Eduardo R. Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Brain Insitute of Rio Grande do Sul, PUCRS, Porto Alegre, 90619-900, Brazil
| | - Thomas K. Karikari
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, 431 41, Sweden
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, HKG, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Serge Gauthier
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Tharick A. Pascoal
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
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Zhao Y, Guo Q, Zhang Y, Zheng J, Yang Y, Du X, Feng H, Zhang S. Application of Deep Learning for Prediction of Alzheimer's Disease in PET/MR Imaging. Bioengineering (Basel) 2023; 10:1120. [PMID: 37892850 PMCID: PMC10604050 DOI: 10.3390/bioengineering10101120] [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: 08/21/2023] [Revised: 09/19/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is a promising technique that combines the advantages of PET and MR to provide both functional and structural information of the brain. Deep learning (DL) is a subfield of machine learning (ML) and artificial intelligence (AI) that focuses on developing algorithms and models inspired by the structure and function of the human brain's neural networks. DL has been applied to various aspects of PET/MR imaging in AD, such as image segmentation, image reconstruction, diagnosis and prediction, and visualization of pathological features. In this review, we introduce the basic concepts and types of DL algorithms, such as feed forward neural networks, convolutional neural networks, recurrent neural networks, and autoencoders. We then summarize the current applications and challenges of DL in PET/MR imaging in AD, and discuss the future directions and opportunities for automated diagnosis, predictions of models, and personalized medicine. We conclude that DL has great potential to improve the quality and efficiency of PET/MR imaging in AD, and to provide new insights into the pathophysiology and treatment of this devastating disease.
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Affiliation(s)
- Yan Zhao
- Department of Information Center, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
| | - Qianrui Guo
- Department of Nuclear Medicine, Beijing Cancer Hospital, Beijing 100142, China;
| | - Yukun Zhang
- Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
| | - Jia Zheng
- Department of Nuclear Medicine, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing 100094, China
| | - Xuemei Du
- Department of Nuclear Medicine, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
| | - Hongbo Feng
- Department of Nuclear Medicine, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
| | - Shuo Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China
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Hampel H, Hu Y, Cummings J, Mattke S, Iwatsubo T, Nakamura A, Vellas B, O'Bryant S, Shaw LM, Cho M, Batrla R, Vergallo A, Blennow K, Dage J, Schindler SE. Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape. Neuron 2023; 111:2781-2799. [PMID: 37295421 PMCID: PMC10720399 DOI: 10.1016/j.neuron.2023.05.017] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 03/03/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.
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Affiliation(s)
- Harald Hampel
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Yan Hu
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Soeren Mattke
- Center for Improving Chronic Illness Care, University of Southern California, Los Angeles, CA, USA
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akinori Nakamura
- Department of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Japan; Department of Cognition and Behavior Science, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Bruno Vellas
- University Paul Sabatier, Gérontopôle, Toulouse University Hospital, UMR INSERM 1285, Toulouse, France
| | - Sid O'Bryant
- Institute for Translational Research, Texas College of Osteopathic Medicine, Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Leslie M Shaw
- Perelman School of Medicine, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Min Cho
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Richard Batrla
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Andrea Vergallo
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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Xie Y, Wang Y, Pei W, Chen Y. Theranostic in GLP-1R molecular imaging: challenges and emerging opportunities. Front Mol Biosci 2023; 10:1210347. [PMID: 37780209 PMCID: PMC10540701 DOI: 10.3389/fmolb.2023.1210347] [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: 04/22/2023] [Accepted: 09/06/2023] [Indexed: 10/03/2023] Open
Abstract
Theranostic in nuclear medicine combines diagnostic imaging and internal irradiation therapy using different therapeutic nuclear probes for visual diagnosis and precise treatment. GLP-1R is a popular receptor target in endocrine diseases, non-alcoholic steatohepatitis, tumors, and other areas. Likewise, it has also made breakthroughs in the development of molecular imaging. It was recognized that GLP-1R imaging originated from the study of insulinoma and afterwards was expanded in application including islet transplantation, pancreatic β-cell mass measurement, and ATP-dependent potassium channel-related endocrine diseases. Fortunately, GLP-1R molecular imaging has been involved in ischemic cardiomyocytes and neurodegenerative diseases. These signs illustrate the power of GLP-1R molecular imaging in the development of medicine. However, it is still limited to imaging diagnosis research in the current molecular imaging environment. The lack of molecular-targeted therapeutics related report hinders its radiology theranostic. In this article, the current research status, challenges, and emerging opportunities for GLP-1R molecular imaging are discussed in order to open a new path for theranostics and to promote the evolution of molecular medicine.
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Affiliation(s)
- Yang Xie
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, Sichuan, China
| | - Yudi Wang
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, Sichuan, China
| | - Wenjie Pei
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, Sichuan, China
| | - Yue Chen
- Department of Nuclear Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
- Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, Luzhou, Sichuan, China
- Academician (Expert) Workstation of Sichuan Province, Luzhou, Sichuan, China
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Kim HY, Chia WK, Hsieh CJ, Guarino DS, Graham TJA, Lengyel-Zhand Z, Schneider M, Tomita C, Lougee MG, Kim HJ, Pagar VV, Lee H, Hou C, Garcia BA, Petersson EJ, O’Shea J, Kotzbauer PT, Mathis CA, Lee VMY, Luk KC, Mach RH. A Novel Brain PET Radiotracer for Imaging Alpha Synuclein Fibrils in Multiple System Atrophy. J Med Chem 2023; 66:12185-12202. [PMID: 37651366 PMCID: PMC10617560 DOI: 10.1021/acs.jmedchem.3c00779] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
Abnormal α-synuclein (α-syn) aggregation characterizes α-synucleinopathies, including Parkinson's disease (PD) and multiple system atrophy (MSA). However, no suitable positron emission tomography (PET) radiotracer for imaging α-syn in PD and MSA exists currently. Our structure-activity relationship studies identified 4-methoxy-N-(4-(3-(pyridin-2-yl)-3,8-diazabicyclo[3.2.1]octan-8-yl)phenyl)benzamide (4i) as a PET radiotracer candidate for imaging α-syn. In vitro assays revealed high binding of 4i to recombinant α-syn fibrils (inhibition constant (Ki) = 6.1 nM) and low affinity for amyloid beta (Aβ) fibrils in Alzheimer's disease (AD) homogenates. However, [3H]4i also exhibited high specific binding to AD, progressive supranuclear palsy, and corticobasal degeneration tissues as well as PD and MSA tissues, suggesting notable affinity to tau. Nevertheless, the specific binding to pathologic α-syn aggregates in MSA post-mortem brain tissues was significantly higher than in PD tissues. This finding demonstrated the potential use of [11C]4i as a PET tracer for imaging α-syn in MSA patients. Nonhuman primate PET studies confirmed good brain uptake and rapid washout for [11C]4i.
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Affiliation(s)
- Ho Young Kim
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Wai Kit Chia
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Chia-Ju Hsieh
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Dinahlee Saturnino Guarino
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Thomas J. A. Graham
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Zsofia Lengyel-Zhand
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Mark Schneider
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Cosette Tomita
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Marshall G. Lougee
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104-6323, USA
| | - Hee Jong Kim
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6303, USA
| | - Vinayak V. Pagar
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104-6323, USA
| | - Hsiaoju Lee
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Catherine Hou
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
| | - Benjamin A. Garcia
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104-6303, USA
| | - E. James Petersson
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104-6323, USA
| | - Jennifer O’Shea
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110-1010, USA
| | - Paul T. Kotzbauer
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110-1010, USA
| | - Chester A. Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Virginia M.-Y. Lee
- Center for Neurodegenerative Disease Research, Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104-2676, USA
| | - Kelvin C. Luk
- Center for Neurodegenerative Disease Research, Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104-2676, USA
| | - Robert H. Mach
- Department of Radiology, University of Pennsylvania, Vagelos Laboratories, 1012, 231 S. 34th Street, Philadelphia, PA 19104-6323, USA
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Haratake Y, Sano K, Fujioka C, Oshima S, Munekane M, Yamasaki T, Mukai T. Chemical design of radioiodinated probes with a metabolizable linkage for target-selective imaging of systemic amyloidosis. Bioorg Med Chem 2023; 92:117426. [PMID: 37552917 DOI: 10.1016/j.bmc.2023.117426] [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: 07/20/2023] [Accepted: 07/26/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Systemic amyloidosis is a rare disease caused by the deposition of amyloid fibrils in various organs. Amyloid-targeted radiopharmaceuticals have been developed and applied to diagnose systemic amyloidosis peripherally; however, high-contrast imaging has not been achieved because of the high background signals in normal organs. To overcome this problem, we designed an amyloid-targeted radioiodinated probe 1 with a metabolizable linkage (ester bond) to release of radiolabeled metabolites (m-iodohippuric acid) in normal organs that could be rapidly excreted in the urine. METHODS Compound 1 was synthesized by conjugating 2-(4-(methylamino)phenyl)benzo[d]thiazol-6-ol, an amyloid-targeting compound, with m-iodohippuric acid. [125I]1 was synthesized via iododestannylation using a tributyltin precursor. Mouse models of amyloid A (AA) amyloidosis, a type of systemic amyloidosis, were prepared by administering amyloid-enhancing factor to mice and used for in vitro autoradiography using organ sections and in vivo evaluation. RESULTS [125I]1 was obtained with a radiochemical yield of 59% and radiochemical purity of over 95%. An in vitro autoradiographic study demonstrated that [125I]1 specifically binds to amyloid in the splenic tissue. Upon administration to normal mice, [125I]1 was distributed to organs throughout the body, followed by the rapid excretion of radioactivity in the urine as m-[125I]iodohippuric acid. Furthermore, ex vivo autoradiography showed that [125I]1 bound to the amyloid formed around the follicles in the spleens of AA amyloidosis model mice. CONCLUSION These results suggest that the interposition of a metabolizable linkage between an amyloid-targeting moiety and a radiolabeled hippuric acid would be useful in the design of radiopharmaceuticals for high-contrast imaging of systemic amyloidosis.
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Affiliation(s)
- Yoshie Haratake
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan
| | - Kohei Sano
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan
| | - Chika Fujioka
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan
| | - Satsuki Oshima
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan
| | - Masayuki Munekane
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan; Laboratory of Clinical Analytical Sciences, Graduate School of Medical Sciences, Kanazawa University, Japan
| | - Toshihide Yamasaki
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan
| | - Takahiro Mukai
- Laboratory of Biophysical Chemistry, Kobe Pharmaceutical University, Japan.
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Sauers SC, Toedebusch CD, Richardson R, Spira AP, Morris JC, Holtzman DM, Lucey BP. Chronotype is Associated with Sleep Quality in Older Adults. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.04.23294997. [PMID: 37732218 PMCID: PMC10508806 DOI: 10.1101/2023.09.04.23294997] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Introduction Disrupted sleep is common in individuals with Alzheimer's disease (AD) and may be a marker for AD risk. The timing of sleep or chronotype affects sleep-wake activity and is also associated with AD, but little is known about links between sleep and chronotype in older adults. In this study, we tested if different measures of sleep and chronotype are associated among older adults even after adjusting for multiple potentially confounding variables. Methods Participants (N=243) with a mean age of 74 underwent standardized cognitive assessments, measurement of CSF AD biomarkers, and sleep monitoring via single-channel EEG, actigraphy, and self-reported sleep logs. Chronotype was defined as the midpoint of sleep measured by actigraphy. Results Later mid-point of sleep (i.e., late chronotype) was associated with African American race and greater night-to-night variability in the sleep mid-point. After controlling for age, race, sex, cognitive status, AD biomarkers, and sleep disorders, a later mid-point of sleep was associated with longer rapid eye movement (REM) onset latency, decreased REM sleep time, lower sleep efficiency, increased sleep onset latency, and more awakenings at night. Late chronotype was also associated with increased <2 Hz non-REM slow-wave activity. Conclusions To identify individuals at risk for cognitive impairment before symptoms onset, non-invasive in vivo markers of brain function, such as sleep, are needed to track both future risk of cognitive impairment and response to interventions. Chronotype is a potential modifiable AD risk factor and should also be taken into account when using sleep as a marker for AD risk.
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Affiliation(s)
- Scott C. Sauers
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110
| | | | - Rachel Richardson
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110
| | - Adam P. Spira
- Department of Mental Health, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins School of Medicine, Baltimore, MD 21205
- The Johns Hopkins Center on Aging and Health, Baltimore, MD 21205
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110
| | - David M. Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110
- Center on Biological Rhythms and Sleep, Washington University School of Medicine, St Louis, MO 63110
| | - Brendan P. Lucey
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110
- Center on Biological Rhythms and Sleep, Washington University School of Medicine, St Louis, MO 63110
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110
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122
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Juganavar A, Joshi A, Shegekar T. Navigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations. Cureus 2023; 15:e44937. [PMID: 37818489 PMCID: PMC10561010 DOI: 10.7759/cureus.44937] [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: 08/09/2023] [Accepted: 09/09/2023] [Indexed: 10/12/2023] Open
Abstract
The hunt for early Alzheimer's disease detection has created cutting-edge diagnostic instruments with enormous promise. This article examines the many facets of these developments, focusing on how they have revolutionised diagnosis and patient outcomes. These tools make it possible to detect tiny brain changes even before they give birth to clinical symptoms by combining cutting-edge biomarkers, neuroimaging methods, and machine-learning algorithms. A significant opportunity for therapies that can slow the course of the disease exists during this early detection stage. Additionally, these cutting-edge techniques improve diagnostic precision, objectivity, and accessibility. Liquid biopsies and blood-based biomarkers provide non-invasive alternatives, filling accessibility gaps in diagnosis. While issues with standardisation, ethics, and data integration continue, collaboration within research, clinical practice, and policy realms fuels positive developments. As technology advances, the way towards better Alzheimer's diagnosis becomes more evident, giving patients and families dealing with this difficult illness fresh hope. The synergy between scientific advancement and compassionate treatment is crucial for improving Alzheimer's disease diagnosis, as this paper emphasises.
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Affiliation(s)
- Anup Juganavar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Abhishek Joshi
- Community Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Tejas Shegekar
- Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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123
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Keith CM, Haut MW, Wilhelmsen K, Mehta RI, Miller M, Navia RO, Ward M, Lindberg K, Coleman M, McCuddy WT, Deib G, Giolzetti A, D'Haese PF. Frontal and temporal lobe correlates of verbal learning and memory in aMCI and suspected Alzheimer's disease dementia. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:923-939. [PMID: 36367308 DOI: 10.1080/13825585.2022.2144618] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 11/01/2022] [Indexed: 11/13/2022]
Abstract
Alzheimer's disease is primarily known for deficits in learning and retaining new information. This has long been associated with pathological changes in the mesial temporal lobes. The role of the frontal lobes in memory in Alzheimer's disease is less well understood. In this study, we examined the role of the frontal lobes in learning, recognition, and retention of new verbal information, as well as the presence of specific errors (i.e., intrusions and false-positive errors). Participants included one hundred sixty-seven patients clinically diagnosed with amnestic mild cognitive impairment or suspected Alzheimer's disease dementia who were administered the California Verbal Learning Test and completed high-resolution MRI. We confirmed the role of the mesial temporal lobes in learning and retention, including the volumes of the hippocampus, entorhinal cortex, and parahippocampal gyrus. In addition, false-positive errors were associated with all volumes of the mesial temporal lobes and widespread areas within the frontal lobes. Errors of intrusion were related to the supplementary motor cortex and hippocampus. Most importantly, the mesial temporal lobes interacted with the frontal lobes for learning, recognition, and memory errors. Lower volumes in both regions explained more performance variance than any single structure. This study supports the interaction of the frontal lobes with the temporal lobes in many aspects of memory in Alzheimer's disease.
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Affiliation(s)
- Cierra M Keith
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, West Virginia, United States
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
| | - Marc W Haut
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, West Virginia, United States
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neurology, West Virginia University, Morgantown, West Virginia, United States
| | - Kirk Wilhelmsen
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neurology, West Virginia University, Morgantown, West Virginia, United States
| | - Rashi I Mehta
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neuroradiology, West Virginia University, Morgantown, West Virginia, United States
| | - Mark Miller
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, West Virginia, United States
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
| | - R Osvaldo Navia
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Medicine, West Virginia University, Morgantown, West Virginia, United States
| | - Melanie Ward
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neurology, West Virginia University, Morgantown, West Virginia, United States
| | - Katharine Lindberg
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, West Virginia, United States
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
| | - Michelle Coleman
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
| | - William T McCuddy
- Department of Neuropsychology, Barrow Neurological Institute, Phoenix, Arizona, United States
| | - Gerard Deib
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neuroradiology, West Virginia University, Morgantown, West Virginia, United States
| | - Angelo Giolzetti
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, West Virginia, United States
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
| | - Pierre-François D'Haese
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, United States
- Department of Neurology, West Virginia University, Morgantown, West Virginia, United States
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124
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Cools R, Kerkhofs K, Leitao RCF, Bormans G. Preclinical Evaluation of Novel PET Probes for Dementia. Semin Nucl Med 2023; 53:599-629. [PMID: 37149435 DOI: 10.1053/j.semnuclmed.2023.03.004] [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: 03/15/2023] [Accepted: 03/24/2023] [Indexed: 05/08/2023]
Abstract
The development of novel PET imaging agents that selectively bind specific dementia-related targets can contribute significantly to accurate, differential and early diagnosis of dementia causing diseases and support the development of therapeutic agents. Consequently, in recent years there has been a growing body of literature describing the development and evaluation of potential new promising PET tracers for dementia. This review article provides a comprehensive overview of novel dementia PET probes under development, classified by their target, and pinpoints their preclinical evaluation pathway, typically involving in silico, in vitro and ex/in vivo evaluation. Specific target-associated challenges and pitfalls, requiring extensive and well-designed preclinical experimental evaluation assays to enable successful clinical translation and avoid shortcomings observed for previously developed 'well-established' dementia PET tracers are highlighted in this review.
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Affiliation(s)
- Romy Cools
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Kobe Kerkhofs
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium; NURA, Belgian Nuclear Research Centre (SCK CEN), Mol, Belgium
| | - Renan C F Leitao
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Guy Bormans
- Laboratory for Radiopharmaceutical Research, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
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125
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Dadario NB, Sughrue ME. The functional role of the precuneus. Brain 2023; 146:3598-3607. [PMID: 37254740 DOI: 10.1093/brain/awad181] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 06/01/2023] Open
Abstract
Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 07102, USA
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126
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Scheres SHW, Ryskeldi-Falcon B, Goedert M. Molecular pathology of neurodegenerative diseases by cryo-EM of amyloids. Nature 2023; 621:701-710. [PMID: 37758888 DOI: 10.1038/s41586-023-06437-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 07/14/2023] [Indexed: 09/29/2023]
Abstract
Abnormal assembly of tau, α-synuclein, TDP-43 and amyloid-β proteins into amyloid filaments defines most human neurodegenerative diseases. Genetics provides a direct link between filament formation and the causes of disease. Developments in cryo-electron microscopy (cryo-EM) have made it possible to determine the atomic structures of amyloids from postmortem human brains. Here we review the structures of brain-derived amyloid filaments that have been determined so far and discuss their impact on research into neurodegeneration. Whereas a given protein can adopt many different filament structures, specific amyloid folds define distinct diseases. Amyloid structures thus provide a description of neuropathology at the atomic level and a basis for studying disease. Future research should focus on model systems that replicate the structures observed in disease to better understand the molecular mechanisms of disease and develop improved diagnostics and therapies.
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Affiliation(s)
- Sjors H W Scheres
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | | | - Michel Goedert
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
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127
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Kaštelan S, Braš M, Pjevač N, Bakija I, Tomić Z, Pjevač Keleminić N, Gverović Antunica A. Tear Biomarkers and Alzheimer's Disease. Int J Mol Sci 2023; 24:13429. [PMID: 37686235 PMCID: PMC10488148 DOI: 10.3390/ijms241713429] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/18/2023] [Accepted: 08/28/2023] [Indexed: 09/10/2023] Open
Abstract
Alzheimer's disease (AD) is an age-related progressive neurodegenerative brain disorder that represents the most common type of dementia. It poses a significant diagnostic challenge that requires timely recognition and treatment. Currently, there is no effective therapy for AD; however, certain medications may slow down its progression. The discovery of AD biomarkers, namely, magnetic resonance imaging, positron emission tomography and cerebrospinal fluid molecules (amyloid-β and tau) has advanced our understanding of this disease and has been crucial for identifying early neuropathologic changes prior to clinical changes and cognitive decline. The close interrelationship between the eye and the brain suggests that tears could be an interesting source of biomarkers for AD; however, studies in this area are limited. The identification of biomarkers in tears will enable the development of cost-effective, non-invasive methods of screening, diagnosis and disease monitoring. In order to use tears as a standard method for early and non-invasive diagnosis of AD, future studies need to be conducted on a larger scale.
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Affiliation(s)
- Snježana Kaštelan
- Department of Ophthalmology, Clinical Hospital Dubrava, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Marijana Braš
- Centre for Palliative Medicine, Medical Ethics and Communication Skills, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Neda Pjevač
- Department of Medical Statistics, Epidemiology and Medical Informatics, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Ivana Bakija
- Department of Integrative Psychiatry, Psychiatry Hospital “Sveti Ivan”, 10090 Zagreb, Croatia
| | - Zora Tomić
- Health Centre of the Croatian Department of Internal Affairs, 10000 Zagreb, Croatia
| | - Nada Pjevač Keleminić
- Department of Family Medicine, Health Centre Zagreb-Centar, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Antonela Gverović Antunica
- Department of Ophthalmology, General Hospital Dubrovnik, University of Dubrovnik, 20000 Dubrovnik, Croatia
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128
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Gu Y, Honig LS, Kang MS, Bahl A, Sanchez D, Reyes-Dumeyer D, Manly JJ, Lantigua RA, Dage JL, Brickman AM, Vardarajan BN, Mayeux R. Risk of Alzheimer's Disease is Associated with Longitudinal Changes in Plasma Biomarkers in the Multiethnic Washington Heights, Inwood Columbia Aging Project Cohort. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.11.23293967. [PMID: 37645764 PMCID: PMC10462222 DOI: 10.1101/2023.08.11.23293967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) biomarkers can help differentiate cognitively unimpaired (CU) individuals from mild cognitive impairment (MCI) and dementia. The role of AD biomarkers in predicting cognitive impairment and AD needs examination. METHODS In 628 CU individuals from a multi-ethnic cohort, Aβ42, Aβ40, phosphorylated tau-181 (P-tau181), glial fibrillary acid protein (GFAP), and neurofilament light chain (NfL) were measured in plasma. RESULTS Higher baseline levels of P-tau181/Aβ42 ratio were associated with increased risk of incident dementia. A biomarker pattern (with elevated Aβ42/Aβ40 but low P-tau181/Aβ42) was associated with decreased dementia risk. Compared to CU, participants who developed MCI or dementia had a rapid decrease in the biomarker pattern reflecting AD-specific pathological change. DISCUSSION Elevated levels of AD biomarker P-tau181/Aβ42, by itself or combined with a low Aβ42/Aβ40 level, predicts clinically diagnosed AD. Individuals with a rapid change in these biomarkers may need close monitoring for the potential downward trajectory of cognition.
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Affiliation(s)
- Yian Gu
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
- Department of Epidemiology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Lawrence S. Honig
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Min Suk Kang
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Aanya Bahl
- Department of Epidemiology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Danurys Sanchez
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Jennifer J. Manly
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Rafael A. Lantigua
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York,New York, USA
| | - Jeffrey L. Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Badri N Vardarajan
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New, York, New York, USA
- G.H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
- Department of Epidemiology, Vagelos College of Physicians and Surgeons, Columbia University, and the New York Presbyterian Hospital, New York, New York, USA
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129
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Tian M, Zuo C, Civelek AC, Carrio I, Watanabe Y, Kang KW, Murakami K, Garibotto V, Prior JO, Barthel H, Guan Y, Lu J, Zhou R, Jin C, Wu S, Zhang X, Zhong Y, Zhang H. International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:375-389. [PMID: 37589025 PMCID: PMC10425321 DOI: 10.1007/s43657-022-00068-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 08/18/2023]
Abstract
Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.
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Affiliation(s)
- Mei Tian
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Chuantao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- National Center for Neurological Disorders and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040 China
| | - Ali Cahid Civelek
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins Medicine, Baltimore, 21287 USA
| | - Ignasi Carrio
- Department of Nuclear Medicine, Hospital Sant Pau, Autonomous University of Barcelona, Barcelona, 08025 Spain
| | - Yasuyoshi Watanabe
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
| | - Keon Wook Kang
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080 Korea
| | - Koji Murakami
- Department of Radiology, Juntendo University Hospital, Tokyo, 113-8431 Japan
| | - Valentina Garibotto
- Diagnostic Department, University Hospitals of Geneva and NIMTlab, University of Geneva, Geneva, 1205 Switzerland
| | - John O. Prior
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, 1011 Switzerland
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University Medical Center, Leipzig, 04103 Germany
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
| | - Jiaying Lu
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Shuang Wu
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Yan Zhong
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 China
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310007 China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310007 China
| | - Molecular Imaging-Based Precision Medicine Task Group of A3 (China-Japan-Korea) Foresight Program
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200235 China
- Human Phenome Institute, Fudan University, Shanghai, 201203 China
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009 China
- National Center for Neurological Disorders and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040 China
- Department of Radiology and Radiological Science, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins Medicine, Baltimore, 21287 USA
- Department of Nuclear Medicine, Hospital Sant Pau, Autonomous University of Barcelona, Barcelona, 08025 Spain
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047 Japan
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080 Korea
- Department of Radiology, Juntendo University Hospital, Tokyo, 113-8431 Japan
- Diagnostic Department, University Hospitals of Geneva and NIMTlab, University of Geneva, Geneva, 1205 Switzerland
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Lausanne, 1011 Switzerland
- Department of Nuclear Medicine, Leipzig University Medical Center, Leipzig, 04103 Germany
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 China
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310007 China
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310007 China
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Gagliardi G, Rodriguez-Vieitez E, Montal V, Sepulcre J, Diez I, Lois C, Hanseeuw B, Schultz AP, Properzi MJ, Papp KV, Marshall GA, Fortea J, Johnson KA, Sperling RA, Vannini P. Cortical microstructural changes predict tau accumulation and episodic memory decline in older adults harboring amyloid. COMMUNICATIONS MEDICINE 2023; 3:106. [PMID: 37528163 PMCID: PMC10394044 DOI: 10.1038/s43856-023-00324-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/19/2023] [Indexed: 08/03/2023] Open
Abstract
INTRODUCTION Non-invasive diffusion-weighted imaging (DWI) to assess brain microstructural changes via cortical mean diffusivity (cMD) has been shown to be cross-sectionally associated with tau in cognitively normal older adults, suggesting that it might be an early marker of neuronal injury. Here, we investigated how regional cortical microstructural changes measured by cMD are related to the longitudinal accumulation of regional tau as well as to episodic memory decline in cognitively normal individuals harboring amyloid pathology. METHODS 122 cognitively normal participants from the Harvard Aging Brain Study underwent DWI, T1w-MRI, amyloid and tau PET imaging, and Logical Memory Delayed Recall (LMDR) assessments. We assessed whether the interaction of baseline amyloid status and cMD (in entorhinal and inferior-temporal cortices) was associated with longitudinal regional tau accumulation and with longitudinal LMDR using separate linear mixed-effects models. RESULTS We find a significant interaction effect of the amyloid status and baseline cMD in predicting longitudinal tau in the entorhinal cortex (p = 0.044) but not the inferior temporal lobe, such that greater baseline cMD values predicts the accumulation of entorhinal tau in amyloid-positive participants. Moreover, we find a significant interaction effect of the amyloid status and baseline cMD in the entorhinal cortex (but not inferior temporal cMD) in predicting longitudinal LMDR (p < 0.001), such that baseline entorhinal cMD predicts the episodic memory decline in amyloid-positive participants. CONCLUSIONS The combination of amyloidosis and elevated cMD in the entorhinal cortex may help identify individuals at short-term risk of tau accumulation and Alzheimer's Disease-related episodic memory decline, suggesting utility in clinical trials.
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Affiliation(s)
- Geoffroy Gagliardi
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Elena Rodriguez-Vieitez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Stockholm, 14152, Sweden
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, 08041, Spain
- Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, 28031, Spain
| | - Jorge Sepulcre
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Ibai Diez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Cristina Lois
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Bernard Hanseeuw
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
- Saint Luc University Hospital, Université Catholique de Louvain, Brussels, 1200, Belgium
| | - Aaron P Schultz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
| | - Michael J Properzi
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Kathryn V Papp
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Gad A Marshall
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, 08041, Spain
- Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, 28031, Spain
| | - Keith A Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Gordon Center for Medical Imaging, Boston, MA, 02114, USA
| | - Reisa A Sperling
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Patrizia Vannini
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA.
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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Zhao Q, Du X, Chen W, Zhang T, Xu Z. Advances in diagnosing mild cognitive impairment and Alzheimer's disease using 11C-PIB- PET/CT and common neuropsychological tests. Front Neurosci 2023; 17:1216215. [PMID: 37492405 PMCID: PMC10363609 DOI: 10.3389/fnins.2023.1216215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 06/15/2023] [Indexed: 07/27/2023] Open
Abstract
Alzheimer's disease (AD) is a critical health issue worldwide that has a negative impact on patients' quality of life, as well as on caregivers, society, and the environment. Positron emission tomography (PET)/computed tomography (CT) and neuropsychological scales can be used to identify AD and mild cognitive impairment (MCI) early, provide a differential diagnosis, and offer early therapies to impede the course of the illness. However, there are few reports of large-scale 11C-PIB-PET/CT investigations that focus on the pathology of AD and MCI. Therefore, further research is needed to determine how neuropsychological test scales and PET/CT measurements of disease progression interact.
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Affiliation(s)
- Qing Zhao
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Xinxin Du
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Wenhong Chen
- Department of Sleep Medicine, Guangxi Zhuang Autonomous Region People's Hospital, Nanning, Guangxi, China
| | - Ting Zhang
- Department of Rehabilitation, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
- Rehabilitation Therapeutics, School of Nursing of Jilin University, Changchun, Jilin, China
| | - Zhuo Xu
- Department of Rehabilitation, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
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Høilund-Carlsen PF, Revheim ME, Costa T, Kepp KP, Castellani RJ, Perry G, Alavi A, Barrio JR. FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls. Diagnostics (Basel) 2023; 13:2254. [PMID: 37443645 DOI: 10.3390/diagnostics13132254] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 06/29/2023] [Accepted: 06/30/2023] [Indexed: 07/15/2023] Open
Abstract
In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.
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Affiliation(s)
- Poul F Høilund-Carlsen
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark
- Research Unit of Clinical Physiology and Nuclear Medicine, Department of Clinical Research, University of Southern Denmark, 5230 Odense M, Denmark
| | - Mona-Elisabeth Revheim
- The Intervention Centre, Division of Technology and Innovation, Oslo University Hospital, 0372 Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, 0313 Oslo, Norway
| | - Tommaso Costa
- GDS, Department of Psychology, Koelliker Hospital, University of Turin, 10124 Turin, Italy
- FOCUS Lab, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Kasper P Kepp
- Section of Biophysical and Biomedicinal Chemistry, DTU Chemistry, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Rudolph J Castellani
- Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - George Perry
- Department of Neuroscience, Developmental and Regenerative Biology and Genetics of Neurodegeneration, Departments of Psychiatry and Neuroscience, University of Texas at San Antonio, San Antonio, TX 78249, USA
| | - Abass Alavi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jorge R Barrio
- Department of Molecular and Medical Pharmacology, David Geffen UCLA School of Medicine, Los Angeles, CA 90095, USA
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Xiong C, McCue LM, Buckles V, Grant E, Agboola F, Coble D, Bateman RJ, Fagan AM, Benzinger TL, Hassenstab J, Schindler SE, McDade E, Moulder K, Gordon BA, Cruchaga C, Day GS, Ikeuchi T, Suzuki K, Allegri RF, Vöglein J, Levin J, Morris JC. Cross-sectional and longitudinal comparisons of biomarkers and cognition among asymptomatic middle-aged individuals with a parental history of either autosomal dominant or late-onset Alzheimer's disease. Alzheimers Dement 2023; 19:2923-2932. [PMID: 36640138 PMCID: PMC10345163 DOI: 10.1002/alz.12912] [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: 05/05/2022] [Revised: 11/21/2022] [Accepted: 11/23/2022] [Indexed: 01/15/2023]
Abstract
BACKGROUND Comparisons of late-onset Alzheimer's disease (LOAD) and autosomal dominant AD (ADAD) are confounded by age. METHODS We compared biomarkers from cerebrospinal fluid (CSF), magnetic resonance imaging, and amyloid imaging with Pittsburgh Compound-B (PiB) across four groups of 387 cognitively normal participants, 42 to 65 years of age, in the Dominantly Inherited Alzheimer Network (DIAN) and the Adult Children Study (ACS) of LOAD: DIAN mutation carriers (MCs) and non-carriers (NON-MCs), and ACS participants with a positive (FH+) and negative (FH-) family history of LOAD. RESULTS At baseline, MCs had the lowest age-adjusted level of CSF Aβ42 and the highest levels of total and phosphorylated tau-181, and PiB uptake. Longitudinally, MC had similar increase in PiB uptake to FH+, but drastically faster decline in hippocampal volume than others, and was the only group showing cognitive decline. DISCUSSION Preclinical ADAD and LOAD share many biomarker signatures, but cross-sectional and longitudinal differences may exist.
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Affiliation(s)
- Chengjie Xiong
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Lena M. McCue
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Virginia Buckles
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Elizabeth Grant
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Folasade Agboola
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Dean Coble
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Randall J. Bateman
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Anne M Fagan
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Tammie L.S. Benzinger
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Radiology, Washington University, St. Louis, Missouri, USA
- Department of Neurological Surgery, Washington University, St. Louis, Missouri, USA
| | - Jason Hassenstab
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
- Department of Psychology, Washington University, St. Louis, Missouri, USA
| | - Suzanne E. Schindler
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Eric McDade
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Krista Moulder
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Brian A. Gordon
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Psychology, Washington University, St. Louis, Missouri, USA
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Carlos Cruchaga
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University, St. Louis, Missouri, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, FL, USA
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, JAPAN
| | | | | | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University, St. Louis, Missouri, USA
- The Dominantly Inherited Alzheimer Network, Washington University, St. Louis, Missouri, USA
- Department of Neurology, Washington University, St. Louis, Missouri, USA
- Department of Pathology and Immunology, Washington University, St. Louis, Missouri, USA
- Department of Physical Therapy, Washington University, St. Louis, Missouri, USA
- Department of Occupational Therapy, Washington University, St. Louis, Missouri, USA
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Yadollahikhales G, Rojas JC. Anti-Amyloid Immunotherapies for Alzheimer's Disease: A 2023 Clinical Update. Neurotherapeutics 2023; 20:914-931. [PMID: 37490245 PMCID: PMC10457266 DOI: 10.1007/s13311-023-01405-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/22/2023] [Indexed: 07/26/2023] Open
Abstract
The amyloid cascade hypothesis is a useful framework for therapeutic development in Alzheimer's disease (AD). Amyloid b1-42 (Aβ) has been the main target of experimental therapies, based on evidence of the neurotoxic effects of Aβ, and of the potential adverse effects of brain Aβ burden detected in humans in vivo by positron emission tomography (PET). Progress on passive anti-amyloid immunotherapy research includes identification of antibodies that facilitate microglial activation, catalytical disaggregation, and increased flow of Aβ from cerebrospinal fluid (CSF) to plasma, thus decreasing the neurotoxic effects of Aβ. Recently completed phase 2 and 3 trials of 3rd generation anti-amyloid immunotherapies are supportive of their clinical efficacy in reducing brain Aβ burden and preventing cognitive decline. Data from recent trials implicate these agents as the first effective disease-modifying therapies against AD and has led to the US Food and Drug Administration (FDA) recent approval of aducanumab and lecanemab, under an accelerated approval pathway. The clinical effects of these agents are modest, however, and associated with amyloid-related imaging abnormalities (ARIA). Testing the effects of anti-Aβ immunotherapies in pre-symptomatic populations and identification of more potent and safer agents is the scope of ongoing and future research. Innovations in clinical trial design will be the key for the efficient and equitable development of novel anti-Aβ immunotherapies. The progress in the field of AD therapeutics will bring new clinical, logistical, and ethical challenges, which pose to revolutionize the practice of neurology, dementia care, and preventive cognitive healthcare.
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Affiliation(s)
- Golnaz Yadollahikhales
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, 1551 4th Street, 411G, San Francisco, CA, 94158, USA
| | - Julio C Rojas
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, 1551 4th Street, 411G, San Francisco, CA, 94158, USA.
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Liu H, Barthélemy NR, Ovod V, Bollinger JG, He Y, Chahin SL, Androff B, Bateman RJ, Lucey BP. Acute sleep loss decreases CSF-to-blood clearance of Alzheimer's disease biomarkers. Alzheimers Dement 2023; 19:3055-3064. [PMID: 36695437 PMCID: PMC10366339 DOI: 10.1002/alz.12930] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 11/22/2022] [Accepted: 12/20/2022] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Sleep deprivation increases cerebrospinal fluid (CSF) amyloid beta (Aβ) and tau levels; however, sleep's effect on Aβ and tau in plasma is unknown. METHODS In a cross-over design, CSF Aβ and tau concentrations were measured in five cognitively normal individuals who had blood and CSF collected every 2 hours for 36 hours during sleep-deprived and normal sleep control conditions. RESULTS Aβ40, Aβ42, unphosphorylated tau threonine181 (T181), unphosphorylated tau threonine-217 (T217), and phosphorylated T181 (pT181) concentrations increased ∼35% to 55% in CSF and decreased ∼5% to 15% in plasma during sleep deprivation. CSF/plasma ratios of all Alzheimer's disease (AD) biomarkers increased during sleep deprivation while the CSF/plasma albumin ratio, a measure of blood-CSF barrier permeability, decreased. CSF and plasma Aβ42/40, pT181/T181, and pT181/Aβ42 ratios were stable longitudinally in both groups. DISCUSSION These findings show that sleep loss alters some plasma AD biomarkers by lowering brain clearance mechanisms and needs to be taken into account when interpreting individual plasma AD biomarkers but not ratios.
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Affiliation(s)
- Haiyan Liu
- Department of Neurology, Washington University School of Medicine, St Louis, MO
| | - Nicolas R. Barthélemy
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Vitaliy Ovod
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - James G. Bollinger
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Yingxin He
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Samir L. Chahin
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Brendan Androff
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
| | - Brendan P. Lucey
- Department of Neurology, Washington University School of Medicine, St Louis, MO
- Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO
- Center On Biological Rhythms and Sleep, Washington University School of Medicine, St Louis, MO
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Pakula RJ, Scott PJH. Applications of radiolabeled antibodies in neuroscience and neuro-oncology. J Labelled Comp Radiopharm 2023; 66:269-285. [PMID: 37322805 DOI: 10.1002/jlcr.4049] [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: 03/04/2023] [Revised: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/17/2023]
Abstract
Positron emission tomography (PET) is a powerful tool in medicine and drug development, allowing for non-invasive imaging and quantitation of biological processes in live organisms. Targets are often probed with small molecules, but antibody-based PET is expanding because of many benefits, including ease of design of new antibodies toward targets, as well as the very strong affinities that can be expected. Application of antibodies to PET imaging of targets in the central nervous system (CNS) is a particularly nascent field, but one with tremendous potential. In this review, we discuss the growth of PET in imaging of CNS targets, present the promises and progress in antibody-based CNS PET, explore challenges faced by the field, and discuss questions that this promising approach will need to answer moving forward for imaging and perhaps even radiotherapy.
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Affiliation(s)
- Ryan J Pakula
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter J H Scott
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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137
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Zhang Y, Chen H, Li R, Sterling K, Song W. Amyloid β-based therapy for Alzheimer's disease: challenges, successes and future. Signal Transduct Target Ther 2023; 8:248. [PMID: 37386015 PMCID: PMC10310781 DOI: 10.1038/s41392-023-01484-7] [Citation(s) in RCA: 128] [Impact Index Per Article: 128.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 05/05/2023] [Accepted: 05/09/2023] [Indexed: 07/01/2023] Open
Abstract
Amyloid β protein (Aβ) is the main component of neuritic plaques in Alzheimer's disease (AD), and its accumulation has been considered as the molecular driver of Alzheimer's pathogenesis and progression. Aβ has been the prime target for the development of AD therapy. However, the repeated failures of Aβ-targeted clinical trials have cast considerable doubt on the amyloid cascade hypothesis and whether the development of Alzheimer's drug has followed the correct course. However, the recent successes of Aβ targeted trials have assuaged those doubts. In this review, we discussed the evolution of the amyloid cascade hypothesis over the last 30 years and summarized its application in Alzheimer's diagnosis and modification. In particular, we extensively discussed the pitfalls, promises and important unanswered questions regarding the current anti-Aβ therapy, as well as strategies for further study and development of more feasible Aβ-targeted approaches in the optimization of AD prevention and treatment.
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Affiliation(s)
- Yun Zhang
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China.
| | - Huaqiu Chen
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Ran Li
- The Second Affiliated Hospital and Yuying Children's Hospital, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Keenan Sterling
- Townsend Family Laboratories, Department of Psychiatry, The University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
| | - Weihong Song
- National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China.
- The Second Affiliated Hospital and Yuying Children's Hospital, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China.
- Townsend Family Laboratories, Department of Psychiatry, The University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, China.
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Zhao J, Jiang L, Matlock A, Xu Y, Zhu J, Zhu H, Tian L, Wolozin B, Cheng JX. Mid-infrared chemical imaging of intracellular tau fibrils using fluorescence-guided computational photothermal microscopy. LIGHT, SCIENCE & APPLICATIONS 2023; 12:147. [PMID: 37322011 PMCID: PMC10272128 DOI: 10.1038/s41377-023-01191-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/18/2023] [Accepted: 05/21/2023] [Indexed: 06/17/2023]
Abstract
Amyloid proteins are associated with a broad spectrum of neurodegenerative diseases. However, it remains a grand challenge to extract molecular structure information from intracellular amyloid proteins in their native cellular environment. To address this challenge, we developed a computational chemical microscope integrating 3D mid-infrared photothermal imaging with fluorescence imaging, termed Fluorescence-guided Bond-Selective Intensity Diffraction Tomography (FBS-IDT). Based on a low-cost and simple optical design, FBS-IDT enables chemical-specific volumetric imaging and 3D site-specific mid-IR fingerprint spectroscopic analysis of tau fibrils, an important type of amyloid protein aggregates, in their intracellular environment. Label-free volumetric chemical imaging of human cells with/without seeded tau fibrils is demonstrated to show the potential correlation between lipid accumulation and tau aggregate formation. Depth-resolved mid-infrared fingerprint spectroscopy is performed to reveal the protein secondary structure of the intracellular tau fibrils. 3D visualization of the β-sheet for tau fibril structure is achieved.
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Affiliation(s)
- Jian Zhao
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA.
| | - Lulu Jiang
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Alex Matlock
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA
| | - Yihong Xu
- Department of Physics, Boston University, Boston, MA, 02215, USA
| | - Jiabei Zhu
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
| | - Hongbo Zhu
- State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 130033, Changchun, China
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Benjamin Wolozin
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Ji-Xin Cheng
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
- Department of Physics, Boston University, Boston, MA, 02215, USA.
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Photonics Center, Boston University, Boston, MA, 02215, USA.
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139
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Ferreiro AL, Choi J, Ryou J, Newcomer EP, Thompson R, Bollinger RM, Hall-Moore C, Ndao IM, Sax L, Benzinger TLS, Stark SL, Holtzman DM, Fagan AM, Schindler SE, Cruchaga C, Butt OH, Morris JC, Tarr PI, Ances BM, Dantas G. Gut microbiome composition may be an indicator of preclinical Alzheimer's disease. Sci Transl Med 2023; 15:eabo2984. [PMID: 37315112 PMCID: PMC10680783 DOI: 10.1126/scitranslmed.abo2984] [Citation(s) in RCA: 84] [Impact Index Per Article: 84.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/26/2023] [Indexed: 06/16/2023]
Abstract
Alzheimer's disease (AD) pathology is thought to progress from normal cognition through preclinical disease and ultimately to symptomatic AD with cognitive impairment. Recent work suggests that the gut microbiome of symptomatic patients with AD has an altered taxonomic composition compared with that of healthy, cognitively normal control individuals. However, knowledge about changes in the gut microbiome before the onset of symptomatic AD is limited. In this cross-sectional study that accounted for clinical covariates and dietary intake, we compared the taxonomic composition and gut microbial function in a cohort of 164 cognitively normal individuals, 49 of whom showed biomarker evidence of early preclinical AD. Gut microbial taxonomic profiles of individuals with preclinical AD were distinct from those of individuals without evidence of preclinical AD. The change in gut microbiome composition correlated with β-amyloid (Aβ) and tau pathological biomarkers but not with biomarkers of neurodegeneration, suggesting that the gut microbiome may change early in the disease process. We identified specific gut bacterial taxa associated with preclinical AD. Inclusion of these microbiome features improved the accuracy, sensitivity, and specificity of machine learning classifiers for predicting preclinical AD status when tested on a subset of the cohort (65 of the 164 participants). Gut microbiome correlates of preclinical AD neuropathology may improve our understanding of AD etiology and may help to identify gut-derived markers of AD risk.
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Affiliation(s)
- Aura L. Ferreiro
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Pathology and Immunology, Division of Laboratory and Genomic Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - JooHee Choi
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jian Ryou
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Erin P. Newcomer
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Regina Thompson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Rebecca M. Bollinger
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carla Hall-Moore
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - I. Malick Ndao
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Laurie Sax
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tammie L. S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Susan L. Stark
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David M. Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anne M. Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Phillip I. Tarr
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Beau M. Ances
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Gautam Dantas
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Pathology and Immunology, Division of Laboratory and Genomic Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
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140
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Cogswell PM, Fan AP. Multimodal comparisons of QSM and PET in neurodegeneration and aging. Neuroimage 2023; 273:120068. [PMID: 37003447 PMCID: PMC10947478 DOI: 10.1016/j.neuroimage.2023.120068] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/17/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Audrey P Fan
- Department of Biomedical Engineering and Department of Neurology, University of California, Davis, 1590 Drew Avenue, Davis, CA 95618, USA
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141
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Björk L, Klingstedt T, Nilsson KPR. Thiophene-Based Ligands: Design, Synthesis and Their Utilization for Optical Assignment of Polymorphic-Disease-Associated Protein Aggregates. Chembiochem 2023; 24:e202300044. [PMID: 36891883 PMCID: PMC10404026 DOI: 10.1002/cbic.202300044] [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: 01/20/2023] [Revised: 03/03/2023] [Accepted: 03/08/2023] [Indexed: 03/10/2023]
Abstract
The development of ligands for detecting protein aggregates is of great interest, as these aggregated proteinaceous species are the pathological hallmarks of several devastating diseases, including Alzheimer's disease. In this regard, thiophene-based ligands have emerged as powerful tools for fluorescent assessment of these pathological entities. The intrinsic conformationally sensitive photophysical properties of poly- and oligothiophenes have allowed optical assignment of disease-associated protein aggregates in tissue sections, as well as real-time in vivo imaging of protein deposits. Herein, we recount the chemical evolution of different generations of thiophene-based ligands, and exemplify their use for the optical distinction of polymorphic protein aggregates. Furthermore, the chemical determinants for achieving a superior fluorescent thiophene-based ligand, as well as the next generation of thiophene-based ligands targeting distinct aggregated species are described. Finally, the directions for future research into the chemical design of thiophene-based ligands that can aid in resolving the scientific challenges around protein aggregation diseases are discussed.
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Affiliation(s)
- Linnea Björk
- Department of Physics, Chemistry and Biology, Linköping University, 581 83, Linköping, Sweden
| | - Therése Klingstedt
- Department of Physics, Chemistry and Biology, Linköping University, 581 83, Linköping, Sweden
| | - K Peter R Nilsson
- Department of Physics, Chemistry and Biology, Linköping University, 581 83, Linköping, Sweden
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142
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Smith R, Cullen NC, Binette AP, Leuzy A, Blennow K, Zetterberg H, Klein G, Borroni E, Ossenkoppele R, Janelidze S, Palmqvist S, Mattsson-Carlgren N, Stomrud E, Hansson O. Tau-PET is superior to phospho-tau when predicting cognitive decline in symptomatic AD patients. Alzheimers Dement 2023; 19:2497-2507. [PMID: 36516028 PMCID: PMC10264552 DOI: 10.1002/alz.12875] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/15/2022] [Accepted: 10/21/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Biomarkers for the prediction of cognitive decline in patients with amnestic mild cognitive impairment (MCI) and amnestic mild dementia are needed for both clinical practice and clinical trials. METHODS We evaluated the ability of tau-PET (positron emission tomography), cortical atrophy on magnetic resonance imaging (MRI), baseline cognition, apolipoprotein E gene (APOE) status, plasma and cerebrospinal fluid (CSF) levels of phosphorylated tau-217, neurofilament light (NfL), and amyloid beta (Aβ)42/40 ratio (individually and in combination) to predict cognitive decline over 2 years in BioFINDER-2 and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS Baseline tau-PET and a composite baseline cognitive score were the strongest independent predictors of cognitive decline. Cortical thickness and NfL provided some additional information. Using a predictive algorithm to enrich patient selection in a theoretical clinical trial led to a significantly lower required sample size. DISCUSSION Models including baseline tau-PET and cognition consistently provided the best prediction of change in cognitive function over 2 years in patients with amnestic MCI or mild dementia.
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Affiliation(s)
- Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Nicholas C. Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | | | | | | | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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143
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Cogswell PM, Lundt ES, Therneau TM, Mester CT, Wiste HJ, Graff-Radford J, Schwarz CG, Senjem ML, Gunter JL, Reid RI, Przybelski SA, Knopman DS, Vemuri P, Petersen RC, Jack CR. Evidence against a temporal association between cerebrovascular disease and Alzheimer's disease imaging biomarkers. Nat Commun 2023; 14:3097. [PMID: 37248223 PMCID: PMC10226977 DOI: 10.1038/s41467-023-38878-8] [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: 08/30/2022] [Accepted: 05/15/2023] [Indexed: 05/31/2023] Open
Abstract
Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
| | - Emily S Lundt
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Carly T Mester
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | | | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
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Timsina J, Ali M, Do A, Wang L, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542118. [PMID: 37292823 PMCID: PMC10245826 DOI: 10.1101/2023.05.24.542118] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. METHODS We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity. RESULTS Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously. DISCUSSION This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
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145
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Pemberton HG, Buckley C, Battle M, Bollack A, Patel V, Tomova P, Cooke D, Balhorn W, Hegedorn K, Lilja J, Brand C, Farrar G. Software compatibility analysis for quantitative measures of [ 18F]flutemetamol amyloid PET burden in mild cognitive impairment. EJNMMI Res 2023; 13:48. [PMID: 37225974 DOI: 10.1186/s13550-023-00994-3] [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: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
RATIONALE Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. METHODS Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. RESULTS Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98). CONCLUSION Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | | | - Mark Battle
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Vrajesh Patel
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Petya Tomova
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | | | | | | | | | - Christine Brand
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Gill Farrar
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
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146
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Fontana IC, Scarpa M, Malarte ML, Rocha FM, Ausellé-Bosch S, Bluma M, Bucci M, Chiotis K, Kumar A, Nordberg A. Astrocyte Signature in Alzheimer's Disease Continuum through a Multi-PET Tracer Imaging Perspective. Cells 2023; 12:1469. [PMID: 37296589 PMCID: PMC10253101 DOI: 10.3390/cells12111469] [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: 02/01/2023] [Revised: 05/02/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023] Open
Abstract
Reactive astrogliosis is an early event in the continuum of Alzheimer's disease (AD). Current advances in positron emission tomography (PET) imaging provide ways of assessing reactive astrogliosis in the living brain. In this review, we revisit clinical PET imaging and in vitro findings using the multi-tracer approach, and point out that reactive astrogliosis precedes the deposition of Aβ plaques, tau pathology, and neurodegeneration in AD. Furthermore, considering the current view of reactive astrogliosis heterogeneity-more than one subtype of astrocyte involved-in AD, we discuss how astrocytic body fluid biomarkers might fit into trajectories different from that of astrocytic PET imaging. Future research focusing on the development of innovative astrocytic PET radiotracers and fluid biomarkers may provide further insights into the heterogeneity of reactive astrogliosis and improve the detection of AD in its early stages.
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Affiliation(s)
- Igor C. Fontana
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Miriam Scarpa
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Mona-Lisa Malarte
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Filipa M. Rocha
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Instituto de Ciência Biomédicas Abel Salazar da Universidade do Porto, 4050-313 Porto, Portugal
- Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal
| | - Sira Ausellé-Bosch
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Faculty of Health and Life Sciences, Pompeu Fabra University, 08003 Barcelona, Spain
| | - Marina Bluma
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Marco Bucci
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Amit Kumar
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 52 Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 57 Stockholm, Sweden
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147
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Bray NW, Pieruccini-Faria F, Witt ST, Bartha R, Doherty TJ, Nagamatsu LS, Almeida QJ, Liu-Ambrose T, Middleton LE, Bherer L, Montero-Odasso M. Combining exercise with cognitive training and vitamin D 3 to improve functional brain connectivity (FBC) in older adults with mild cognitive impairment (MCI). Results from the SYNERGIC trial. GeroScience 2023:10.1007/s11357-023-00805-6. [PMID: 37162700 PMCID: PMC10170058 DOI: 10.1007/s11357-023-00805-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
Changes in functional brain connectivity (FBC) may indicate how lifestyle modifications can prevent the progression to dementia; FBC identifies areas that are spatially separate but temporally synchronized in their activation and is altered in those with mild cognitive impairment (MCI), a prodromal state between healthy cognitive aging and dementia. Participants with MCI were randomly assigned to one of five study arms. Three times per week for 20-weeks, participants performed 30-min of (control) cognitive training, followed by 60-min of (control) physical exercise. Additionally, a vitamin D3 (10,000 IU/pill) or a placebo capsule was ingested three times per week for 20-weeks. Using the CONN toolbox, we measured FBC change (Post-Pre) across four statistical models that collapsed for and/or included some or all study arms. We conducted Pearson correlations between FBC change and changes in physical and cognitive functioning. Our sample included 120 participants (mean age: 73.89 ± 6.50). Compared to the pure control, physical exercise (model one; p-False Discovery Rate (FDR) < 0.01 & < 0.05) with cognitive training (model two; p-FDR = < 0.001), and all three interventions combined (model four; p-FDR = < 0.01) demonstrated an increase in FBC between regions of the Default-Mode Network (i.e., hippocampus and angular gyrus). After controlling for false discovery rate, there were no significant correlations between change in connectivity and change in cognitive or physical function. Physical exercise alone appears to be as efficacious as combined interventional strategies in altering FBC, but implications for behavioral outcomes remain unclear.
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Affiliation(s)
- Nick W Bray
- Cumming School of Medicine, Department of Physiology & Pharmacology, University of Calgary, Calgary, AB, T2N 1N4, Canada.
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, T2N 1N4, Canada.
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, 550 Wellington Road, Room A3-116, London, ON, N6C-0A7, Canada.
| | - Frederico Pieruccini-Faria
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, 550 Wellington Road, Room A3-116, London, ON, N6C-0A7, Canada
- Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine & Dentistry, Western University, London, ON, N6A-5C1, Canada
| | - Suzanne T Witt
- BrainsCAN, Western University, London, ON, N6A-3K7, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A-5C1, Canada
- Robarts Research Institute, Western University, London, ON, N6A-5B7, Canada
| | - Timothy J Doherty
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A-5C1, Canada
- Department of Physical Medicine and Rehabilitation, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A-5C1, Canada
| | - Lindsay S Nagamatsu
- Faculty of Health Sciences, School of Kinesiology, Western University, London, ON, N6G-2V4, Canada
| | - Quincy J Almeida
- Faculty of Science, Department of Kinesiology and Physical Education, Wilfrid Laurier University, Waterloo, ON, N2L-3C5, Canada
| | - Teresa Liu-Ambrose
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, V6T-1Z3, Canada
- Centre for Aging SMART at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada
| | - Laura E Middleton
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, N2L-3G1, Canada
| | - Louis Bherer
- Department of Medicine, University of Montréal, Montréal, QC, H3T-1J4, Canada
- Research Centre, Montreal Heart Institute, Montréal, QC, H1T-1C8, Canada
| | - Manuel Montero-Odasso
- Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, 550 Wellington Road, Room A3-116, London, ON, N6C-0A7, Canada.
- Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine & Dentistry, Western University, London, ON, N6A-5C1, Canada.
- Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, ON, N6A-5C1, Canada.
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148
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Wu CY, Ho CY, Yang YH. Developing Biomarkers for the Skin: Biomarkers for the Diagnosis and Prediction of Treatment Outcomes of Alzheimer's Disease. Int J Mol Sci 2023; 24:ijms24108478. [PMID: 37239825 DOI: 10.3390/ijms24108478] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 05/02/2023] [Accepted: 05/06/2023] [Indexed: 05/28/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by memory decline and cognitive impairment. Research on biomarkers can aid in early diagnosis, monitoring disease progression, evaluating treatment efficacy, and advancing fundamental research. We conducted a cross-sectional longitudinal study to see if there is an association between AD patients and age-matched healthy controls for their physiologic skin characteristics, such as pH, hydration, transepidermal water loss (TEWL), elasticity, microcirculation, and ApoE genotyping. The study used the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating-Sum of the Boxes (CDR-SB) scales as references to quantify the presence of disease, if any. Our findings demonstrate that AD patients have a dominantly neutral pH, greater skin hydration, and less elasticity compared to the control subjects. At baseline, the tortuous capillary percentage negatively correlated with MMSE scores in AD patients. However, AD patients who carry the ApoE E4 allele and exhibit a high percentage of tortuous capillaries and capillary tortuous numbers have shown better treatment outcomes at six months. Therefore, we believe that physiologic skin testing is a rapid and effective way to screen, monitor progression, and ultimately guide the most appropriate treatment for AD patients.
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Affiliation(s)
- Ching-Ying Wu
- Department of Dermatology, College of Medicine and Post Baccalaureat Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
- Department of Cosmetic Science, Chang Gung University of Science and Technology, Taoyuan 333, Taiwan
| | - Chih-Yi Ho
- Department of Dermatology, College of Medicine and Post Baccalaureat Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Yuan-Han Yang
- Department of Neurology, College of Post Baccalaureat Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
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149
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Altomare D, Barkhof F, Caprioglio C, Collij LE, Scheltens P, Lopes Alves I, Bouwman F, Berkhof J, van Maurik IS, Garibotto V, Moro C, Delrieu J, Payoux P, Saint-Aubert L, Hitzel A, Molinuevo JL, Grau-Rivera O, Gispert JD, Drzezga A, Jessen F, Zeyen P, Nordberg A, Savitcheva I, Jelic V, Walker Z, Edison P, Demonet JF, Gismondi R, Farrar G, Stephens AW, Frisoni GB. Clinical Effect of Early vs Late Amyloid Positron Emission Tomography in Memory Clinic Patients: The AMYPAD-DPMS Randomized Clinical Trial. JAMA Neurol 2023:2804755. [PMID: 37155177 PMCID: PMC10167601 DOI: 10.1001/jamaneurol.2023.0997] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Importance Amyloid positron emission tomography (PET) allows the direct assessment of amyloid deposition, one of the main hallmarks of Alzheimer disease. However, this technique is currently not widely reimbursed because of the lack of appropriately designed studies demonstrating its clinical effect. Objective To assess the clinical effect of amyloid PET in memory clinic patients. Design, Setting, and Participants The AMYPAD-DPMS is a prospective randomized clinical trial in 8 European memory clinics. Participants were allocated (using a minimization method) to 3 study groups based on the performance of amyloid PET: arm 1, early in the diagnostic workup (within 1 month); arm 2, late in the diagnostic workup (after a mean [SD] 8 [2] months); or arm 3, if and when the managing physician chose. Participants were patients with subjective cognitive decline plus (SCD+; SCD plus clinical features increasing the likelihood of preclinical Alzheimer disease), mild cognitive impairment (MCI), or dementia; they were assessed at baseline and after 3 months. Recruitment took place between April 16, 2018, and October 30, 2020. Data analysis was performed from July 2022 to January 2023. Intervention Amyloid PET. Main Outcome and Measure The main outcome was the difference between arm 1 and arm 2 in the proportion of participants receiving an etiological diagnosis with a very high confidence (ie, ≥90% on a 50%-100% visual numeric scale) after 3 months. Results A total of 844 participants were screened, and 840 were enrolled (291 in arm 1, 271 in arm 2, 278 in arm 3). Baseline and 3-month visit data were available for 272 participants in arm 1 and 260 in arm 2 (median [IQR] age: 71 [65-77] and 71 [65-77] years; 150/272 male [55%] and 135/260 male [52%]; 122/272 female [45%] and 125/260 female [48%]; median [IQR] education: 12 [10-15] and 13 [10-16] years, respectively). After 3 months, 109 of 272 participants (40%) in arm 1 had a diagnosis with very high confidence vs 30 of 260 (11%) in arm 2 (P < .001). This was consistent across cognitive stages (SCD+: 25/84 [30%] vs 5/78 [6%]; P < .001; MCI: 45/108 [42%] vs 9/102 [9%]; P < .001; dementia: 39/80 [49%] vs 16/80 [20%]; P < .001). Conclusion and Relevance In this study, early amyloid PET allowed memory clinic patients to receive an etiological diagnosis with very high confidence after only 3 months compared with patients who had not undergone amyloid PET. These findings support the implementation of amyloid PET early in the diagnostic workup of memory clinic patients. Trial Registration EudraCT Number: 2017-002527-21.
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Affiliation(s)
- Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
- Institute of Neurology, Institute of Healthcare Engineering, University College London, London, United Kingdom
| | - Camilla Caprioglio
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
| | - Femke Bouwman
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Johannes Berkhof
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Ingrid S van Maurik
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Christian Moro
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Julien Delrieu
- Gérontopôle, Department of Geriatrics, Toulouse University Hospital, Toulouse, France
- Maintain Aging Research Team, CERPOP, Inserm, Université Paul Sabatier, Toulouse, France
| | - Pierre Payoux
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), UMR1214 Inserm, Université de Toulouse III, Toulouse, France
| | - Laure Saint-Aubert
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), UMR1214 Inserm, Université de Toulouse III, Toulouse, France
| | - Anne Hitzel
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck, Copenhagen, Denmark
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Excellence Cluster Cellular Stress Responses in Aging-Related Diseases (CECAD), Medical Faculty, University of Cologne, Cologne, Germany
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center of Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Vesna Jelic
- Cognitive Disorders Clinic, Theme Inflammation and Aging, Karolinska University Hospital-Huddinge, Stockholm, Sweden
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, United Kingdom
- St Margaret's Hospital, Essex Partnership University NHS Foundation Trust, Essex, United Kingdom
| | - Paul Edison
- Division of Neurology, Department of Brain Sciences, Imperial College London, London, United Kingdom
| | | | | | | | | | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
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150
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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