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Oveisgharan S, Yu L, de Paiva Lopes K, Petyuk VA, Tasaki S, Vialle R, Menon V, Wang Y, De Jager PL, Schneider JA, Bennett DA. G-protein coupled estrogen receptor 1, amyloid-β, and tau tangles in older adults. Commun Biol 2024; 7:569. [PMID: 38750228 PMCID: PMC11096330 DOI: 10.1038/s42003-024-06272-9] [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: 09/22/2023] [Accepted: 04/30/2024] [Indexed: 05/18/2024] Open
Abstract
Accumulation of amyloid-β (Aβ) and tau tangles are hallmarks of Alzheimer's disease. Aβ is extracellular while tau tangles are typically intracellular, and it is unknown how these two proteinopathies are connected. Here, we use data of 1206 elders and test that RNA expression levels of GPER1, a transmembrane protein, modify the association of Aβ with tau tangles. GPER1 RNA expression is related to more tau tangles (p = 0.001). Moreover, GPER1 expression modifies the association of immunohistochemistry-derived Aβ load with tau tangles (p = 0.044). Similarly, GPER1 expression modifies the association between Aβ proteoforms and tau tangles: total Aβ protein (p = 0.030) and Aβ38 peptide (p = 0.002). Using single nuclei RNA-seq indicates that GPER1 RNA expression in astrocytes modifies the relation of Aβ load with tau tangles (p = 0.002), but not GPER1 in excitatory neurons or endothelial cells. We conclude that GPER1 may be a link between Aβ and tau tangles driven mainly by astrocytic GPER1 expression.
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Affiliation(s)
- Shahram Oveisgharan
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Katia de Paiva Lopes
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Ricardo Vialle
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Vilas Menon
- Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Center for Translational and Computational Neuroimmunology, Columbia University Irving Medical Center, New York, NY, USA
| | - Yanling Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
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Jonaitis EM, Hermann BP, Mueller KD, Clark LR, Du L, Betthauser TJ, Cody K, Gleason CE, Christian BT, Asthana S, Chappell RJ, Chin NA, Johnson SC, Langhough RE. Longitudinal normative standards for cognitive tests and composites using harmonized data from two Wisconsin AD-risk-enriched cohorts. Alzheimers Dement 2024; 20:3305-3321. [PMID: 38539269 PMCID: PMC11095443 DOI: 10.1002/alz.13774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 04/06/2024]
Abstract
INTRODUCTION Published norms are typically cross-sectional and often are not sensitive to preclinical cognitive changes due to dementia. We developed and validated demographically adjusted cross-sectional and longitudinal normative standards using harmonized outcomes from two Alzheimer's disease (AD) risk-enriched cohorts. METHODS Data from the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center were combined. Quantile regression was used to develop unconditional (cross-sectional) and conditional (longitudinal) normative standards for 18 outcomes using data from cognitively unimpaired participants (N = 1390; mean follow-up = 9.25 years). Validity analyses (N = 2456) examined relationships between percentile scores (centiles), consensus-based cognitive statuses, and AD biomarker levels. RESULTS Unconditional and conditional centiles were lower in those with consensus-based impairment or biomarker positivity. Similarly, quantitative biomarker levels were higher in those whose centiles suggested decline. DISCUSSION This study presents normative standards for cognitive measures sensitive to pre-clinical changes. Future directions will investigate potential clinical applications of longitudinal normative standards. HIGHLIGHTS Quantile regression was used to construct longitudinal norms for cognitive tests. Poorer percentile scores were related to concurrent diagnosis and Alzheimer's disease biomarkers. A ShinyApp was built to display test scores and norms and flag low performance.
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Affiliation(s)
- Erin M. Jonaitis
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Bruce P. Hermann
- Department of NeurologySchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Kimberly D. Mueller
- Department of Communication Sciences and DisordersUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Lindsay R. Clark
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
| | - Lianlian Du
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Tobey J. Betthauser
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Karly Cody
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Carey E. Gleason
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Bradley T. Christian
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Waisman CenterUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of Medical PhysicsSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Richard J. Chappell
- Department of StatisticsSchool of ComputerData and Information SciencesUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of Biostatistics and Medical InformaticsSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Division of GeriatricsUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans Hospital, MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Rebecca E. Langhough
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of MedicineSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
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Lee S, Byun MS, Yi D, Ahn H, Jung G, Jung JH, Chang YY, Kim K, Choi H, Choi J, Lee JY, Kang KM, Sohn CH, Lee YS, Kim YK, Lee DY. Plasma Leptin and Alzheimer Protein Pathologies Among Older Adults. JAMA Netw Open 2024; 7:e249539. [PMID: 38700863 PMCID: PMC11069086 DOI: 10.1001/jamanetworkopen.2024.9539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 03/01/2024] [Indexed: 05/06/2024] Open
Abstract
Importance Many epidemiologic studies have suggested that low levels of plasma leptin, a major adipokine, are associated with increased risk of Alzheimer disease (AD) dementia and cognitive decline. Nevertheless, the mechanistic pathway linking plasma leptin and AD-related cognitive decline is not yet fully understood. Objective To examine the association of plasma leptin levels with in vivo AD pathologies, including amyloid-beta (Aβ) and tau deposition, through both cross-sectional and longitudinal approaches among cognitively unimpaired older adults. Design, Setting, and Participants This was a longitudinal cohort study from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer Disease. Data were collected from January 1, 2014, to December 31, 2020, and data were analyzed from July 11 to September 6, 2022. The study included a total of 208 cognitively unimpaired participants who underwent baseline positron emission tomography (PET) scans for brain Aβ deposition. For longitudinal analyses, 192 participants who completed both baseline and 2-year follow-up PET scans for brain Aβ deposition were included. Exposure Plasma leptin levels as assessed by enzyme-linked immunosorbent assay. Main Outcomes and Measures Baseline levels and longitudinal changes of global Aβ and AD-signature region tau deposition measured by PET scans. Results Among the 208 participants, the mean (SD) age was 66.0 (11.3) years, 114 were women (54.8%), and 37 were apolipoprotein E ε4 carriers (17.8%). Lower plasma leptin levels had a significant cross-sectional association with greater brain Aβ deposition (β = -0.04; 95% CI, -0.09 to 0.00; P = .046), while there was no significant association between plasma leptin levels and tau deposition (β = -0.02; 95% CI, -0.05 to 0.02; P = .41). In contrast, longitudinal analyses revealed that there was a significant association between lower baseline leptin levels and greater increase of tau deposition over 2 years (β = -0.06; 95% CI, -0.11 to -0.01; P = .03), whereas plasma leptin levels did not have a significant association with longitudinal change of Aβ deposition (β = 0.006; 95% CI, 0.00-0.02; P = .27). Conclusions and Relevance The present findings suggest that plasma leptin may be protective for the development or progression of AD pathology, including both Aβ and tau deposition.
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Affiliation(s)
- Seunghoon Lee
- Department of Psychiatry, Myongji Hospital, Hanyang University College of Medicine, Goyang, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Hyejin Ahn
- Interdisciplinary Program of Cognitive Science, Seoul National University College of Humanities, Seoul, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Joon Hyung Jung
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Republic of Korea
| | - Yoon Young Chang
- Department of Psychiatry, Inje University, Sanggye Paik Hospital, Seoul, Republic of Korea
| | - Kyungtae Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeji Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jeongmin Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun-Young Lee
- Department of Neuropsychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Interdisciplinary Program of Cognitive Science, Seoul National University College of Humanities, Seoul, Republic of Korea
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Young CB, Smith V, Karjadi C, Grogan S, Ang TFA, Insel PS, Henderson VW, Sumner M, Poston KL, Au R, Mormino EC. Speech patterns during memory recall relates to early tau burden across adulthood. Alzheimers Dement 2024; 20:2552-2563. [PMID: 38348772 PMCID: PMC11032578 DOI: 10.1002/alz.13731] [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: 10/24/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 04/22/2024]
Abstract
INTRODUCTION Early cognitive decline may manifest in subtle differences in speech. METHODS We examined 238 cognitively unimpaired adults from the Framingham Heart Study (32-75 years) who completed amyloid and tau PET imaging. Speech patterns during delayed recall of a story memory task were quantified via five speech markers, and their associations with global amyloid status and regional tau signal were examined. RESULTS Total utterance time, number of between-utterance pauses, speech rate, and percentage of unique words significantly correlated with delayed recall score although the shared variance was low (2%-15%). Delayed recall score was not significantly different between β-amyoid-positive (Aβ+) and -negative (Aβ-) groups and was not associated with regional tau signal. However, longer and more between-utterance pauses, and slower speech rate were associated with increased tau signal across medial temporal and early neocortical regions. DISCUSSION Subtle speech changes during memory recall may reflect cognitive impairment associated with early Alzheimer's disease pathology. HIGHLIGHTS Speech during delayed memory recall relates to tau PET signal across adulthood. Delayed memory recall score was not associated with tau PET signal. Speech shows greater sensitivity to detecting subtle cognitive changes associated with early tau accumulation. Our cohort spans adulthood, while most PET imaging studies focus on older adults.
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Affiliation(s)
- Christina B. Young
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Viktorija Smith
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Cody Karjadi
- Department of Anatomy & Neurobiology and Framingham Heart StudyBoston University Chobanian and Avedisian School of MedicineBostonMassachusettsUSA
| | - Selah‐Marie Grogan
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
| | - Ting Fang Alvin Ang
- Department of Anatomy & Neurobiology and Framingham Heart StudyBoston University Chobanian and Avedisian School of MedicineBostonMassachusettsUSA
| | - Philip S. Insel
- Department of PsychiatryUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Victor W. Henderson
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Department of Epidemiology and Population HealthStanford UniversityStanfordCaliforniaUSA
| | - Meghan Sumner
- Department of LinguisticsStanford UniversityStanfordCaliforniaUSA
| | - Kathleen L. Poston
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Wu Tsai Neuroscience InstituteStanford UniversityStanfordCaliforniaUSA
| | - Rhoda Au
- Department of Anatomy & Neurobiology and Framingham Heart StudyBoston University Chobanian and Avedisian School of MedicineBostonMassachusettsUSA
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological SciencesStanford University School of MedicineStanfordCaliforniaUSA
- Wu Tsai Neuroscience InstituteStanford UniversityStanfordCaliforniaUSA
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Sanabria Bohórquez SM, Baker S, Manser PT, Tonietto M, Galli C, Wildsmith KR, Zou Y, Kerchner GA, Weimer R, Teng E. Evaluation of partial volume correction and analysis of longitudinal [ 18F]GTP1 tau PET imaging in Alzheimer's disease using linear mixed-effects models. FRONTIERS IN NEUROIMAGING 2024; 3:1355402. [PMID: 38606196 PMCID: PMC11008283 DOI: 10.3389/fnimg.2024.1355402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/29/2024] [Indexed: 04/13/2024]
Abstract
Purpose We evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM). Methods We applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden-level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates. Results The VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability. Conclusion The results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test-retest variability. Clinical trial registration NCT02640092 and NCT03289143.
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Affiliation(s)
| | - Suzanne Baker
- Clinical Imaging Group, Genentech, Inc., South San Francisco, CA, United States
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Paul T. Manser
- Biostatistics, Genentech, Inc., South San Francisco, CA, United States
| | - Matteo Tonietto
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Christopher Galli
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | | | - Yixuan Zou
- Data and Statistical Science, Product Development, Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Geoffrey A. Kerchner
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Robby Weimer
- Translational Imaging, Genentech, Inc., South San Francisco, CA, United States
| | - Edmond Teng
- Early Clinical Development, Genentech, Inc., South San Francisco, CA, United States
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Wang X, Bakulski KM, Karvonen‐Gutierrez CA, Park SK, Morgan D, Albin RL, Paulson HL. Blood-based biomarkers for Alzheimer's disease and cognitive function from mid- to late life. Alzheimers Dement 2024; 20:1807-1814. [PMID: 38126555 PMCID: PMC10984504 DOI: 10.1002/alz.13583] [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: 08/30/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023]
Abstract
INTRODUCTION We investigated associations of Alzheimer's disease (AD) serum biomarkers with longitudinal changes in cognitive function from mid- to late life among women. METHODS The study population included 192 women with the median age of 53.3 years at baseline, from the Study of Women's Health Across the Nation Michigan Cohort, followed up over 14 years. Associations between baseline serum amyloid β (Aβ)42, the Aβ42/40 ratio, phosphorylated tau181 (p-tau181), and total tau with longitudinal changes in cognition were evaluated using linear mixed effects models. RESULTS After adjusting for confounders, lower Aβ42/40 ratios were associated with faster declines in the Digit Span Backward Test. Higher p-tau181 also showed a borderline statistically significant association with more rapid decline in the Symbol Digit Modalities Test. DISCUSSION Our findings suggest that mid-life serum AD biomarkers could be associated with accelerated cognitive decline from mid- to late life in women. Future studies with larger samples are needed to validate and extend our findings. HIGHLIGHTS This study investigates midlife serum AD biomarkers on longitudinal cognitive function changes in women. Mid-life serum AD biomarkers are associated with accelerated cognitive decline. A decrease in the Aβ42/40 ratio was associated with a faster decline in the DSB score. A higher p-tau181 concentration was associated with a faster decline in the SDMT score.
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Affiliation(s)
- Xin Wang
- Department of EpidemiologySchool of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Kelly M. Bakulski
- Department of EpidemiologySchool of Public HealthUniversity of MichiganAnn ArborMichiganUSA
- Michigan Alzheimer's Disease CenterUniversity of MichiganAnn ArborMichiganUSA
| | | | - Sung Kyun Park
- Department of EpidemiologySchool of Public HealthUniversity of MichiganAnn ArborMichiganUSA
- Department of Environmental Health SciencesSchool of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - David Morgan
- Department of Translational NeuroscienceCollege of Human MedicineGrand Rapids Research CenterMichigan State UniversityGrand RapidsMichiganUSA
| | - Roger L. Albin
- Michigan Alzheimer's Disease CenterUniversity of MichiganAnn ArborMichiganUSA
- Department of NeurologyUniversity of MichiganAnn ArborMichiganUSA
- Neurology Service & GRECCVAAAHSAnn ArborMichiganUSA
| | - Henry L. Paulson
- Michigan Alzheimer's Disease CenterUniversity of MichiganAnn ArborMichiganUSA
- Department of NeurologyUniversity of MichiganAnn ArborMichiganUSA
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Kjeldsen PL, Damholdt MF, Madsen LS, Nissen PH, Aanerud JFA, Parbo P, Ismail R, Kaasing M, Eskildsen SF, Østergaard L, Brooks DJ. Performance on complex memory tests is associated with β-amyloid in individuals at risk of developing Alzheimer's disease. J Neuropsychol 2024; 18:120-135. [PMID: 37382036 DOI: 10.1111/jnp.12332] [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: 10/04/2022] [Revised: 06/01/2023] [Accepted: 06/13/2023] [Indexed: 06/30/2023]
Abstract
The pathophysiological development of Alzheimer's disease (AD) begins in the brain years before the onset of clinical symptoms. The accumulation of beta-amyloid (Aβ) is thought to be the first cortical pathology to occur. Carrying one apolipoprotein E (APOE) ε4 allele increases the risk of developing AD at least 2-3 times and is associated with earlier Aβ accumulation. Although it is difficult to identify Aβ-related cognitive impairment in early AD with standard cognitive tests, more sensitive memory tests may be able to do this. We sought to examine associations between Aβ and performance on three tests within three subdomains of memory, verbal, visual, and associative memory, to elucidate which of these tests were sensitive to Aβ-related cognitive impairment in at-risk subjects. 55 APOE ε4 carriers underwent MRI, 11 C-Pittsburgh Compound B (PiB) PET, and cognitive testing. A composite cortical PiB SUVR cut-off score of 1.5 was used to categorise subjects as either APOE ε4 Aβ+ or APOE ε4 Aβ-. Correlations were carried out using cortical surface analysis. In the whole APOE ε4 group, we found significant correlations between Aβ load and performance on verbal, visual, and associative memory tests in widespread cortical areas, the strongest association being with performance on associative memory tests. In the APOE ε4 Aβ+ group, we found significant correlations between Aβ load and performance of verbal and associative, but not visual, memory in localised cortical areas. Performance on verbal and associative memory tests provides sensitive markers of early Aβ-related cognitive impairment in at-risk subjects.
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Affiliation(s)
- Pernille Louise Kjeldsen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
- Department of Neurology, Aalborg University Hospital, Aalborg, Denmark
| | - Malene Flensborg Damholdt
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Psychology, Aarhus University, Aarhus, Denmark
| | - Lasse Stensvig Madsen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centre of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Peter Henrik Nissen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark
| | | | - Peter Parbo
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark
| | - Rola Ismail
- Department of Nuclear Medicine, Sygehus Lillebaelt, Vejle, Denmark
| | - Malene Kaasing
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centre of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Simon Fristed Eskildsen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centre of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Leif Østergaard
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Centre of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - David James Brooks
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus, Denmark
- Translational and Clinical Research Institute, University of Newcastle upon Tyne, Newcastle upon Tyne, UK
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Ashton NJ, Brum WS, Di Molfetta G, Benedet AL, Arslan B, Jonaitis E, Langhough RE, Cody K, Wilson R, Carlsson CM, Vanmechelen E, Montoliu-Gaya L, Lantero-Rodriguez J, Rahmouni N, Tissot C, Stevenson J, Servaes S, Therriault J, Pascoal T, Lleó A, Alcolea D, Fortea J, Rosa-Neto P, Johnson S, Jeromin A, Blennow K, Zetterberg H. Diagnostic Accuracy of a Plasma Phosphorylated Tau 217 Immunoassay for Alzheimer Disease Pathology. JAMA Neurol 2024; 81:255-263. [PMID: 38252443 PMCID: PMC10804282 DOI: 10.1001/jamaneurol.2023.5319] [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: 07/10/2023] [Accepted: 11/10/2023] [Indexed: 01/23/2024]
Abstract
Importance Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer disease (AD) pathology, with p-tau217 considered to have the most utility. However, availability of p-tau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective To determine the utility of a novel and commercially available immunoassay for plasma p-tau217 to detect AD pathology and evaluate reference ranges for abnormal amyloid β (Aβ) and longitudinal change across 3 selected cohorts. Design, Setting, and Participants This cohort study examined data from 3 single-center observational cohorts: cross-sectional and longitudinal data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort (visits October 2017-August 2021) and Wisconsin Registry for Alzheimer's Prevention (WRAP) cohort (visits February 2007-November 2020) and cross-sectional data from the Sant Pau Initiative on Neurodegeneration (SPIN) cohort (baseline visits March 2009-November 2021). Participants included individuals with and without cognitive impairment grouped by amyloid and tau (AT) status using PET or CSF biomarkers. Data were analyzed from February to June 2023. Exposures Magnetic resonance imaging, Aβ positron emission tomography (PET), tau PET, cerebrospinal fluid (CSF) biomarkers (Aβ42/40 and p-tau immunoassays), and plasma p-tau217 (ALZpath pTau217 assay). Main Outcomes and Measures Accuracy of plasma p-tau217 in detecting abnormal amyloid and tau pathology, longitudinal p-tau217 change according to baseline pathology status. Results The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%] and 282 males [35.9%]). High accuracy was observed in identifying elevated Aβ (area under the curve [AUC], 0.92-0.96; 95% CI, 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95% CI, 0.84-0.99) across all cohorts. These accuracies were comparable with CSF biomarkers in determining abnormal PET signal. The detection of abnormal Aβ pathology using a 3-range reference yielded reproducible results and reduced confirmatory testing by approximately 80%. Longitudinally, plasma p-tau217 values showed an annual increase only in Aβ-positive individuals, with the highest increase observed in those with tau positivity. Conclusions and Relevance This study found that a commercially available plasma p-tau217 immunoassay accurately identified biological AD, comparable with results using CSF biomarkers, with reproducible cut-offs across cohorts. It detected longitudinal changes, including at the preclinical stage.
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Affiliation(s)
- Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rebecca E. Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Karly Cody
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rachael Wilson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | | | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cecile Tissot
- 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Pedro Rosa-Neto
- 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Sterling Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, 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 & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
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9
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Lopez OL, Villemagne VL, Chang YF, Cohen AD, Klunk WE, Mathis CA, Pascoal T, Ikonomovic MD, Rowe C, Dore V, Snitz BE, Lopresti BJ, Kamboh MI, Aizenstein HJ, Kuller LH. Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia. Neurology 2024; 102:e207920. [PMID: 38165336 PMCID: PMC10870745 DOI: 10.1212/wnl.0000000000207920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/03/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES While the highest prevalence of dementia occurs in individuals older than 80 years, most imaging studies focused on younger populations. The rates of β-amyloid (Aβ) accumulation and the effect of Alzheimer disease (AD) pathology on progression to dementia in this age group remain unexplored. In this study, we examined the relationship between changes in Aβ deposition over time and incident dementia in nondemented individuals followed during a period of 11 years. METHODS We examined 94 participants (age 85.9 + 2.8 years) who had up to 5 measurements of Pittsburgh compound-B (PiB)-PET and clinical evaluations from 2009 to 2020. All 94 participants had 2 PiB-PET scans, 76 participants had 3 PiB-PET scans, 18 participants had 4 PiB-PET scans, and 10 participants had 5 PiB-PET scans. The rates of Aβ deposition were compared with 120 nondemented individuals younger than 80 years (69.3 ± 5.4 years) from the Australian Imaging, Biomarker, and Lifestyle (AIBL) study who had 3 or more annual PiB-PET assessments. RESULTS By 2020, 49% of the participants developed dementia and 63% were deceased. There was a gradual increase in Aβ deposition in all participants whether they were considered Aβ positive or negative at baseline. In a Cox model controlled for age, sex, education level, APOE-4 allele, baseline Mini-Mental State Examination, and mortality, short-term change in Aβ deposition was not significantly associated with incident dementia (HR 2.19 (0.41-11.73). However, baseline Aβ burden, cortical thickness, and white matter lesions volume were the predictors of incident dementia. Aβ accumulation was faster (p = 0.01) in the older cohort (5.6%/year) when compared with AIBL (4.1%/year). In addition, baseline Aβ deposition was a predictor of short-term change (mean time 1.88 years). DISCUSSION There was an accelerated Aβ accumulation in cognitively normal individuals older than 80 years. Baseline Aβ deposition was a determinant of incident dementia and short-term change in Aβ deposition suggesting that an active Aβ pathologic process was present when these participants were cognitively normal. Consequently, age may not be a limiting factor for the use of the emergent anti-Aβ therapies.
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Affiliation(s)
- Oscar L Lopez
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Yue-Fang Chang
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Ann D Cohen
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - William E Klunk
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Chester A Mathis
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Tharick Pascoal
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Milos D Ikonomovic
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Christopher Rowe
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Vincent Dore
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Beth E Snitz
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Brian J Lopresti
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - M Ilyas Kamboh
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Howard J Aizenstein
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Lewis H Kuller
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
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10
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Simon SS, Varangis E, Lee S, Gu Y, Gazes Y, Razlighi QR, Habeck C, Stern Y. In vivo tau is associated with change in memory and processing speed, but not reasoning, in cognitively unimpaired older adults. Neurobiol Aging 2024; 133:28-38. [PMID: 38376885 PMCID: PMC10879688 DOI: 10.1016/j.neurobiolaging.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 08/30/2023] [Accepted: 10/01/2023] [Indexed: 02/21/2024]
Abstract
The relationship between tau deposition and cognitive decline in cognitively healthy older adults is still unclear. The tau PET tracer 18F-MK-6240 has shown favorable imaging characteristics to identify early tau deposition in aging. We evaluated the relationship between in vivo tau levels (18F-MK-6240) and retrospective cognitive change over 5 years in episodic memory, processing speed, and reasoning. For tau quantification, a set of regions of interest (ROIs) was selected a priori based on previous literature: (1) total-ROI comprising selected areas, (2) medial temporal lobe-ROI, and (3) lateral temporal lobe-ROI and cingulate/parietal lobe-ROI. Higher tau burden in most ROIs was associated with a steeper decline in memory and speed. There were no associations between tau and reasoning change. The novelty of this finding is that tau burden may affect not only episodic memory, a well-established finding but also processing speed. Our finding reinforces the notion that early tau deposition in areas related to Alzheimer's disease is associated with cognitive decline in cognitively unimpaired individuals, even in a sample with low amyloid-β pathology.
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Affiliation(s)
- Sharon Sanz Simon
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Eleanna Varangis
- School of Kinesiology, University of Michigan, Ann Arbor, MI, USA; Concussion Center, University of Michigan, Ann Arbor, MI, USA
| | - Seonjoo Lee
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Yian Gu
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Yunglin Gazes
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | | | - Christian Habeck
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology, Columbia University, Vagelos College of Physicians and Surgeons, New York, NY, USA.
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11
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Hale MR, Langhough R, Du L, Hermann BP, Van Hulle CA, Carboni M, Kollmorgen G, Basche KE, Bruno D, Sanson-Miles L, Jonaitis EM, Chin NA, Okonkwo OC, Bendlin BB, Carlsson CM, Zetterberg H, Blennow K, Betthauser TJ, Johnson SC, Mueller KD. Associations between recall of proper names in story recall and CSF amyloid and tau in adults without cognitive impairment. Neurobiol Aging 2024; 133:87-98. [PMID: 37925995 PMCID: PMC10842469 DOI: 10.1016/j.neurobiolaging.2023.09.018] [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: 01/18/2023] [Revised: 09/26/2023] [Accepted: 09/28/2023] [Indexed: 11/07/2023]
Abstract
Neuropsychological measures sensitive to decline in the preclinical phase of Alzheimer's disease are needed. We previously demonstrated that higher amyloid-beta (Aβ) assessed by positron emission tomography in adults without cognitive impairment was associated with recall of fewer proper names in Logical Memory story recall. The current study investigated the association between proper names and cerebrospinal fluid biomarkers (Aβ42/40, phosphorylated tau181 [pTau181], neurofilament light) in 223 participants from the Wisconsin Registry for Alzheimer's Prevention. We assessed associations between biomarkers and delayed Logical Memory total score and proper names using binary logistic regressions. Sensitivity analyses used multinomial logistic regression and stratified biomarker groups. Lower Logical Memory total score and proper names scores from the most recent visit were associated with biomarker positivity. Relatedly, there was a 27% decreased risk of being classified Aβ42/40+/pTau181+ for each additional proper name recalled. A linear mixed effects model found that longitudinal change in proper names recall was predicted by biomarker status. These results demonstrate a novel relationship between proper names and Alzheimer's disease-cerebrospinal fluid pathology.
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Affiliation(s)
- Madeline R Hale
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca Langhough
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Lianlian Du
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Bruce P Hermann
- Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Carol A Van Hulle
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | | | | | - Kristin E Basche
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Davide Bruno
- School of Psychology, Liverpool John Moores University, Liverpool, UK
| | - Leah Sanson-Miles
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA
| | - Erin M Jonaitis
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Nathaniel A Chin
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Ozioma C Okonkwo
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Barbara B Bendlin
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Cynthia M Carlsson
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - Henrik Zetterberg
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; 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, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - 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
| | - Tobey J Betthauser
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine & Public Health, Madison, WI, USA; VA Geriatric Research, Education and Clinical Center (GRECC), William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Kimberly D Mueller
- Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA; Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA; School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
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12
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Rani N, Alm KH, Corona-Long CA, Speck CL, Soldan A, Pettigrew C, Zhu Y, Albert M, Bakker A. Tau PET burden in Brodmann areas 35 and 36 is associated with individual differences in cognition in non-demented older adults. Front Aging Neurosci 2023; 15:1272946. [PMID: 38161595 PMCID: PMC10757623 DOI: 10.3389/fnagi.2023.1272946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/23/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction The accumulation of neurofibrillary tau tangles, a neuropathological hallmark of Alzheimer's disease (AD), occurs in medial temporal lobe (MTL) regions early in the disease process, with some of the earliest deposits localized to subregions of the entorhinal cortex. Although functional specialization of entorhinal cortex subregions has been reported, few studies have considered functional associations with localized tau accumulation. Methods In this study, stepwise linear regressions were used to examine the contributions of regional tau burden in specific MTL subregions, as measured by 18F-MK6240 PET, to individual variability in cognition. Dependent measures of interest included the Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini Mental State Examination (MMSE), and composite scores of delayed episodic memory and language. Other model variables included age, sex, education, APOE4 status, and global amyloid burden, indexed by 11C-PiB. Results Tau burden in right Brodmann area 35 (BA35), left and right Brodmann area 36 (BA36), and age each uniquely contributed to the proportion of explained variance in CDR-SB scores, while right BA36 and age were also significant predictors of MMSE scores, and right BA36 was significantly associated with delayed episodic memory performance. Tau burden in both left and right BA36, along with education, uniquely contributed to the proportion of explained variance in language composite scores. Importantly, the addition of more inclusive ROIs, encompassing less granular segmentation of the entorhinal cortex, did not significantly contribute to explained variance in cognition across any of the models. Discussion These findings suggest that the ability to quantify tau burden in more refined MTL subregions may better account for individual differences in cognition, which may improve the identification of non-demented older adults who are on a trajectory of decline due to AD.
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Affiliation(s)
- Nisha Rani
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Kylie H. Alm
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Caitlin A. Corona-Long
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Caroline L. Speck
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Yuxin Zhu
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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13
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Du L, Hermann BP, Jonaitis EM, Cody KA, Rivera-Rivera L, Rowley H, Field A, Eisenmenger L, Christian BT, Betthauser TJ, Larget B, Chappell R, Janelidze S, Hansson O, Johnson SC, Langhough R. Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors. Brain Commun 2023; 5:fcad333. [PMID: 38107504 PMCID: PMC10724051 DOI: 10.1093/braincomms/fcad333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023] Open
Abstract
Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo Rivera-Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Howard Rowley
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bret Larget
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Rick Chappell
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund 205 02, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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Pratt MR, Vocadlo DJ. Understanding and exploiting the roles of O-GlcNAc in neurodegenerative diseases. J Biol Chem 2023; 299:105411. [PMID: 37918804 PMCID: PMC10687168 DOI: 10.1016/j.jbc.2023.105411] [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: 08/16/2023] [Revised: 10/18/2023] [Accepted: 10/23/2023] [Indexed: 11/04/2023] Open
Abstract
O-GlcNAc is a common modification found on nuclear and cytoplasmic proteins. Determining the catalytic mechanism of the enzyme O-GlcNAcase (OGA), which removes O-GlcNAc from proteins, enabled the creation of potent and selective inhibitors of this regulatory enzyme. Such inhibitors have served as important tools in helping to uncover the cellular and organismal physiological roles of this modification. In addition, OGA inhibitors have been important for defining the augmentation of O-GlcNAc as a promising disease-modifying approach to combat several neurodegenerative diseases including both Alzheimer's disease and Parkinson's disease. These studies have led to development and optimization of OGA inhibitors for clinical application. These compounds have been shown to be well tolerated in early clinical studies and are steadily advancing into the clinic. Despite these advances, the mechanisms by which O-GlcNAc protects against these various types of neurodegeneration are a topic of continuing interest since improved insight may enable the creation of more targeted strategies to modulate O-GlcNAc for therapeutic benefit. Relevant pathways on which O-GlcNAc has been found to exert beneficial effects include autophagy, necroptosis, and processing of the amyloid precursor protein. More recently, the development and application of chemical methods enabling the synthesis of homogenous proteins have clarified the biochemical effects of O-GlcNAc on protein aggregation and uncovered new roles for O-GlcNAc in heat shock response. Here, we discuss the features of O-GlcNAc in neurodegenerative diseases, the application of inhibitors to identify the roles of this modification, and the biochemical effects of O-GlcNAc on proteins and pathways associated with neurodegeneration.
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Affiliation(s)
- Matthew R Pratt
- Department of Chemistry and Department of Biological Sciences, University of Southern California, Los Angeles, California, USA.
| | - David J Vocadlo
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia, Canada; Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada.
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15
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Hari E, Kurt E, Ulasoglu-Yildiz C, Bayram A, Bilgic B, Demiralp T, Gurvit H. Morphometric analysis of medial temporal lobe subregions in Alzheimer's disease using high-resolution MRI. Brain Struct Funct 2023; 228:1885-1899. [PMID: 37486408 DOI: 10.1007/s00429-023-02683-2] [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: 01/16/2023] [Accepted: 07/07/2023] [Indexed: 07/25/2023]
Abstract
The spread pattern of progressive degeneration seen in Alzheimer's disease (AD) to small-scale medial temporal lobe subregions is critical for early diagnosis. In this context, it was aimed to examine the morphometric changes of the hippocampal subfields, amygdala nuclei, entorhinal cortex (ERC), and parahippocampal cortex (PHC) using MRI. MRI data of patients diagnosed with 20 Alzheimer's disease dementia (ADD), 30 amnestic mild cognitive impairment (aMCI), and 30 subjective cognitive impairment (SCI) without demographic differences were used. Segmentation and parcellation were performed using FreeSurfer. The segmentation process obtained volume values of 12 hippocampal subfields and 9 amygdala nuclei. Thickness values of ERC and PHC were calculated with the parcellation process. ANCOVA was performed using age, education and gender as covariates to evaluate the intergroup differences. Linear discriminant analysis was used to investigate whether atrophy predicted groups at an early stage. ERC and PHC thickness decreased significantly throughout the disease continuum, while only ERC was affected in the early stage. When the hippocampal and amygdala subfields were compared volumetrically, significant differences were found in the amygdala between the SCI and aMCI groups. In the early period, only volume reduction in the anterior amygdaloid area of the amygdala nuclei exceeded the significance threshold. Research on AD primarily focuses on original hippocampocentric structures and their main function which is episodic memory. Our results emphasized the significance of so far relatively neglected olfactocentric structures and their functions, such as smell and social cognition in the pre-dementia stages of the AD process.
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Affiliation(s)
- Emre Hari
- Graduate School of Health Sciences, Istanbul University, Bozdogan Kemeri Caddesi No:8 Vezneciler Hamami Sokagi, Vezneciler, 34216, Fatih, Istanbul, Turkey.
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey.
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey.
| | - Elif Kurt
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Ali Bayram
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Başar Bilgic
- Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Hakan Gurvit
- Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
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16
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Gallagher RL, Koscik RL, Moody JF, Vogt NM, Adluru N, Kecskemeti SR, Van Hulle CA, Chin NA, Asthana S, Kollmorgen G, Suridjan I, Carlsson CM, Johnson SC, Dean DC, Zetterberg H, Blennow K, Alexander AL, Bendlin BB. Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status. Alzheimers Res Ther 2023; 15:180. [PMID: 37848950 PMCID: PMC10583332 DOI: 10.1186/s13195-023-01281-y] [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: 12/03/2021] [Accepted: 07/27/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. METHODS Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). RESULTS Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. CONCLUSION Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.
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Affiliation(s)
- Rigina L Gallagher
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Rebecca Langhough Koscik
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Jason F Moody
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Nicholas M Vogt
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nagesh Adluru
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | | | - Carol A Van Hulle
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nathaniel A Chin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | | | | | - Cynthia M Carlsson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Sterling C Johnson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Douglas C Dean
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Henrik Zetterberg
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrew L Alexander
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Barbara B Bendlin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA.
- Wisconsin Alzheimer's Institute, Madison, WI, USA.
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Jagust WJ, Teunissen CE, DeCarli C. The complex pathway between amyloid β and cognition: implications for therapy. Lancet Neurol 2023; 22:847-857. [PMID: 37454670 DOI: 10.1016/s1474-4422(23)00128-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 03/11/2023] [Accepted: 03/27/2023] [Indexed: 07/18/2023]
Abstract
For decades, the hypothesis that brain deposition of the amyloid β protein initiates Alzheimer's disease has dominated research and clinical trials. Targeting amyloid β is starting to produce therapeutic benefit, although whether amyloid-lowering drugs will be widely and meaningfully effective is still unclear. Despite extensive in-vivo biomarker evidence in humans showing the importance of an amyloid cascade that drives cognitive decline, the amyloid hypothesis does not fully account for the complexity of late-life cognitive impairment. Multiple brain pathological changes, inflammation, and host factors of resilience might also be involved in contributing to the development of dementia. This variability suggests that the benefits of lowering amyloid β might depend on how strongly an amyloid pathway is manifest in an individual in relation to other coexisting pathophysiological processes. A new approach to research and treatment, which fully considers the multiple factors that drive cognitive decline, is necessary.
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Affiliation(s)
- William J Jagust
- School of Public Health, and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Program Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
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18
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Ashton NJ, Brum WS, Di Molfetta G, Benedet AL, Arslan B, Jonatis E, Langhough RE, Cody K, Wilson R, Carlsson CM, Vanmechelen E, Montoliu-Gaya L, Lantero-Rodriguez J, Rahmouni N, Tissot C, Stevenson J, Servaes S, Therriault J, Pascoal T, Lleó A, Alcolea D, Fortea J, Rosa-Neto P, Johnson S, Jeromin A, Blennow K, Zetterberg H. Diagnostic accuracy of the plasma ALZpath pTau217 immunoassay to identify Alzheimer's disease pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.11.23292493. [PMID: 37502842 PMCID: PMC10370224 DOI: 10.1101/2023.07.11.23292493] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Importance Phosphorylated tau (pTau) is a specific blood biomarker for Alzheimer's disease (AD) pathology, with pTau217 considered to have the most utility. However, availability of pTau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective To determine the utility of a novel and commercially available Single molecule array (Simoa) for plasma pTau217 (ALZpath) to detect AD pathology. To evaluate references ranges for abnormal Aβ across three selected cohorts. Design Setting Participants Three single-centre observational cohorts were involved in the study: Translational Biomarkers in Aging and Dementia (TRIAD), Wisconsin Registry for Alzheimer's Prevention (WRAP), and Sant Pau Initiative on Neurodegeneration (SPIN). MRI, Aβ-PET, and tau-PET data were available for TRIAD and WRAP, while CSF biomarkers were additionally measured in a subset of TRIAD and SPIN. Plasma measurements of pTau181, pTau217 (ALZpath), pTau231, Aβ42/40, GFAP, and NfL, were available for all cohorts. Longitudinal blood biomarker data spanning 3 years for TRIAD and 8 years for WRAP were included. Exposures MRI, Aβ-PET, tau-PET, CSF biomarkers (Aβ42/40 and pTau immunoassays) and plasma pTau217 (ALZpath Simoa). Main Outcomes and Measures The accuracy of plasma pTau217 for detecting abnormal amyloid and tau pathology. Longitudinal pTau217 change according to baseline pathology status. Results The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%]) were included in the study. High accuracy was observed in identifying elevated Aβ (AUC, 0.92-0.96; 95%CI 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95%CI 0.84-0.99) across all cohorts. These accuracies were significantly higher than other plasma biomarker combinations and comparable to CSF biomarkers. The detection of abnormal Aβ pathology using binary or three-range references yielded reproducible results. Longitudinally, plasma pTau217 showed an annual increase only in Aβ-positive individuals, with the highest increase observed in those with tau-positivity. Conclusions and Relevance The ALZpath plasma pTau217 Simoa assay accurately identifies biological AD, comparable to CSF biomarkers, with reproducible cut-offs across cohorts. It detects longitudinal changes, including at the preclinical stage, and is the first widely available, accessible, and scalable blood test for pTau217 detection.
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Affiliation(s)
- Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute London UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation London UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin Jonatis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Rebecca E. Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Karly Cody
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Rachael Wilson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA
| | | | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cecile Tissot
- 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Pedro Rosa-Neto
- 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
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Sterling Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & 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 & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- 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, Clear Water Bay, Hong Kong, China
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19
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Lamontagne-Kam D, Ulfat AK, Hervé V, Vu TM, Brouillette J. Implication of tau propagation on neurodegeneration in Alzheimer's disease. Front Neurosci 2023; 17:1219299. [PMID: 37483337 PMCID: PMC10360202 DOI: 10.3389/fnins.2023.1219299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 06/07/2023] [Indexed: 07/25/2023] Open
Abstract
Propagation of tau fibrils correlate closely with neurodegeneration and memory deficits seen during the progression of Alzheimer's disease (AD). Although it is not well-established what drives or attenuates tau spreading, new studies on human brain using positron emission tomography (PET) have shed light on how tau phosphorylation, genetic factors, and the initial epicenter of tau accumulation influence tau accumulation and propagation throughout the brain. Here, we review the latest PET studies performed across the entire AD continuum looking at the impact of amyloid load on tau pathology. We also explore the effects of structural, functional, and proximity connectivity on tau spreading in a stereotypical manner in the brain of AD patients. Since tau propagation can be quite heterogenous between individuals, we then consider how the speed and pattern of propagation are influenced by the starting localization of tau accumulation in connected brain regions. We provide an overview of some genetic variants that were shown to accelerate or slow down tau spreading. Finally, we discuss how phosphorylation of certain tau epitopes affect the spreading of tau fibrils. Since tau pathology is an early event in AD pathogenesis and is one of the best predictors of neurodegeneration and memory impairments, understanding the process by which tau spread from one brain region to another could pave the way to novel therapeutic avenues that are efficient during the early stages of the disease, before neurodegeneration induces permanent brain damage and severe memory loss.
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20
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Fischer B, Van Hulle CA, Langhough R, Norton D, Zuelsdorff M, Gooding DC, Wyman MF, Johnson A, Lambrou N, James T, Bouges S, Carter FP, Salazar H, Kirmess K, Holubasch M, Meyer M, Venkatesh V, West T, Verghese P, Yarasheski K, Carlsson CM, Johnson SC, Asthana S, Gleason CE. Plasma Aβ42/40 and cognitive variability are associated with cognitive function in Black Americans: Findings from the AA-FAIM cohort. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2023; 9:e12414. [PMID: 37752907 PMCID: PMC10519622 DOI: 10.1002/trc2.12414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 06/25/2023] [Indexed: 09/28/2023]
Abstract
Introduction It is critical to develop more inclusive Alzheimer's disease (AD) research protocols to ensure that historically excluded groups are included in preclinical research and have access to timely diagnosis and treatment. If validated in racialized groups, plasma AD biomarkers and measures of subtle cognitive dysfunction could provide avenues to expand diversity in preclinical AD research. We sought to evaluate the utility of two easily obtained, low-burden disease markers, plasma amyloid beta (Aβ)42/40, and intra-individual cognitive variability (IICV), to predict concurrent and longitudinal cognitive performance in a sample of Black adults. Methods Two hundred fifty-seven Black participants enrolled in the African Americans Fighting Alzheimer's in Midlife (AA-FAIM) study underwent at least one cognitive assessment visit; a subset of n = 235 had plasma samples. Baseline IICV was calculated as the standard deviation across participants' z scores on five cognitive measures: Rey Auditory Verbal Learning Test Delayed Recall, Trail Making Test Parts A and B (Trails A and B), and Boston Naming Test. Using mixed effects regression models, we compared concurrent and longitudinal models to baseline plasma Aβ42/40 or IICV by age interactions. PrecivityAD assays quantified baseline plasma Aβ42/40. Results IICV was associated with concurrent/baseline performance on several outcomes but did not modify associations between age and cognitive decline. In contrast, plasma Aβ42/40 was unrelated to baseline cognitive performance, but a pattern emerged in interactions with age in longitudinal models of Trails A and B and Rey Auditory Verbal Learning Test total learning trials. Although not significant after correcting for multiple comparisons, low Aβ42/40 was associated with faster cognitive declines over time. Discussion Our results are promising as they extend existing findings to an Black American sample using low-cost, low-burden methods that can be implemented outside of a research center, thus supporting efforts for inclusive AD biomarker research.
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Affiliation(s)
- Barbara Fischer
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Department of NeurologyUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Carol Ann Van Hulle
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Rebecca Langhough
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of WisconsinMadisonWisconsinUSA
| | - Derek Norton
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Department of Biostatistics and Medical InformaticsUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Megan Zuelsdorff
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- School of NursingUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Diane Carol Gooding
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Department of PsychologyUniversity of Wisconsin–MadisonMadison, WisconsinUSA
- Department of PsychiatryUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Mary F. Wyman
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Adrienne Johnson
- Center for Tobacco Research and InterventionSchool of Medicine and Public HealthUniversity of Wisconsin–MadisonMadisonWisconsinUSA
| | - Nickolas Lambrou
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Taryn James
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Shenikqua Bouges
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Fabu Phillis Carter
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | - Hector Salazar
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
| | | | | | | | | | - Tim West
- C2N DiagnosticsSt. LouisMissouriUSA
| | | | | | - Cynthia M. Carlsson
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of WisconsinMadisonWisconsinUSA
| | - Sterling C. Johnson
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of WisconsinMadisonWisconsinUSA
| | - Sanjay Asthana
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's InstituteUniversity of WisconsinMadisonWisconsinUSA
| | - Carey E. Gleason
- Madison VA GRECCWilliam S. Middleton Memorial HospitalMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin–Madison School of Medicine and Public HealthMadisonWisconsinUSA
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21
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Macedo AC, Tissot C, Therriault J, Servaes S, Wang YT, Fernandez-Arias J, Rahmouni N, Lussier FZ, Vermeiren M, Bezgin G, Vitali P, Ng KP, Zimmer ER, Guiot MC, Pascoal TA, Gauthier S, Rosa-Neto P. The Use of Tau PET to Stage Alzheimer Disease According to the Braak Staging Framework. J Nucl Med 2023:jnumed.122.265200. [PMID: 37321820 PMCID: PMC10394315 DOI: 10.2967/jnumed.122.265200] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 04/25/2023] [Indexed: 06/17/2023] Open
Abstract
Amyloid-β plaques and neurofibrillary tangles (NFTs) are the 2 histopathologic hallmarks of Alzheimer disease (AD). On the basis of the pattern of NFT distribution in the brain, Braak and Braak proposed a histopathologic staging system for AD. Braak staging provides a compelling framework for staging and monitoring of NFT progression in vivo using PET imaging. Because AD staging remains based on clinical features, there is an unmet need to translate neuropathologic staging to a biologic clinical staging system. Such a biomarker staging system might play a role in staging preclinical AD or in improving recruitment strategies for clinical trials. Here, we review the literature regarding AD staging with the Braak framework using tau PET imaging, here called PET-based Braak staging. Our aim is to summarize the efforts of implementing Braak staging using PET and assess correspondence with the Braak histopathologic descriptions and with AD biomarkers. Methods: We conducted a systematic literature search in May 2022 on PubMed and Scopus combining the terms "Alzheimer" AND "Braak" AND ("positron emission tomography" OR "PET"). Results: The database search returned 262 results, and after assessment for eligibility, 21 studies were selected. Overall, most studies indicate that PET-based Braak staging may be an efficient method to stage AD since it presents an adequate ability to discriminate between phases of the AD continuum and correlates with clinical, fluid, and imaging biomarkers of AD. However, the translation of the original Braak descriptions to tau PET was done taking into account the limitations of this imaging technique. This led to important interstudy variability in the anatomic definitions of Braak stage regions of interest. Conclusion: Refinements in this staging system are necessary to incorporate atypical variants and Braak-nonconformant cases. Further studies are needed to understand the possible applications of PET-based Braak staging to clinical practice and research. Furthermore, there is a need for standardization in the topographic definitions of Braak stage regions of interest to guarantee reproducibility and methodologic homogeneity across studies.
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Affiliation(s)
- Arthur C Macedo
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Cécile Tissot
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Joseph Therriault
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Stijn Servaes
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Yi-Ting Wang
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Jaime Fernandez-Arias
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Nesrine Rahmouni
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Firoza Z Lussier
- Department of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Marie Vermeiren
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Gleb Bezgin
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Eduardo R Zimmer
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; and
| | | | - Tharick A Pascoal
- Department of Psychiatry and Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Serge Gauthier
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada;
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22
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Xiang C, Ai W, Zhang Y. Language dysfunction correlates with cognitive impairments in older adults without dementia mediated by amyloid pathology. Front Neurol 2023; 14:1051382. [PMID: 37265466 PMCID: PMC10230042 DOI: 10.3389/fneur.2023.1051382] [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: 09/22/2022] [Accepted: 04/05/2023] [Indexed: 06/03/2023] Open
Abstract
Background Previous studies have explored the application of non-invasive biomarkers of language dysfunction for the early detection of Alzheimer's disease (AD). However, language dysfunction over time may be quite heterogeneous within different diagnostic groups. Method Patient demographics and clinical data were retrieved from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database for the participants without dementia who had measures of cerebrospinal fluid (CSF) biomarkers and language dysfunction. We analyzed the effect of longitudinal neuropathological and clinical correlates in the pathological process of semantic fluency and confrontation naming. The mediation effects of AD biomarkers were also explored by the mediation analysis. Result There were 272 subjects without dementia included in this analysis. Higher rates of decline in semantic fluency and confrontation naming were associated with a higher risk of progression to MCI or AD, and a greater decline in cognitive abilities. Moreover, the rate of change in semantic fluency was significantly associated with Aβ deposition, while confrontation naming was significantly associated with both amyloidosis and tau burden. Mediation analyses revealed that both confrontation naming and semantic fluency were partially mediated by the Aβ aggregation. Conclusion In conclusion, the changes in language dysfunction may partly stem from the Aβ deposition, while confrontation naming can also partly originate from the increase in tau burden. Therefore, this study sheds light on how language dysfunction is partly constitutive of mild cognitive impairment and dementia and therefore is an important clinical predictor.
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Affiliation(s)
- Chunchen Xiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Weiping Ai
- Department of Neurology, Zhangjiakou First Hospital, Zhangjiakou, China
| | - Yumei Zhang
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Stroke, Beijing Institute for Brain Disorders, Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
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23
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Zavecz Z, Shah VD, Murillo OG, Vallat R, Mander BA, Winer JR, Jagust WJ, Walker MP. NREM sleep as a novel protective cognitive reserve factor in the face of Alzheimer's disease pathology. BMC Med 2023; 21:156. [PMID: 37138290 PMCID: PMC10155344 DOI: 10.1186/s12916-023-02811-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/28/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) pathology impairs cognitive function. Yet some individuals with high amounts of AD pathology suffer marked memory impairment, while others with the same degree of pathology burden show little impairment. Why is this? One proposed explanation is cognitive reserve i.e., factors that confer resilience against, or compensation for the effects of AD pathology. Deep NREM slow wave sleep (SWS) is recognized to enhance functions of learning and memory in healthy older adults. However, that the quality of NREM SWS (NREM slow wave activity, SWA) represents a novel cognitive reserve factor in older adults with AD pathology, thereby providing compensation against memory dysfunction otherwise caused by high AD pathology burden, remains unknown. METHODS Here, we tested this hypothesis in cognitively normal older adults (N = 62) by combining 11C-PiB (Pittsburgh compound B) positron emission tomography (PET) scanning for the quantification of β-amyloid (Aβ) with sleep electroencephalography (EEG) recordings to quantify NREM SWA and a hippocampal-dependent face-name learning task. RESULTS We demonstrated that NREM SWA significantly moderates the effect of Aβ status on memory function. Specifically, NREM SWA selectively supported superior memory function in individuals suffering high Aβ burden, i.e., those most in need of cognitive reserve (B = 2.694, p = 0.019). In contrast, those without significant Aβ pathological burden, and thus without the same need for cognitive reserve, did not similarly benefit from the presence of NREM SWA (B = -0.115, p = 0.876). This interaction between NREM SWA and Aβ status predicting memory function was significant after correcting for age, sex, Body Mass Index, gray matter atrophy, and previously identified cognitive reserve factors, such as education and physical activity (p = 0.042). CONCLUSIONS These findings indicate that NREM SWA is a novel cognitive reserve factor providing resilience against the memory impairment otherwise caused by high AD pathology burden. Furthermore, this cognitive reserve function of NREM SWA remained significant when accounting both for covariates, and factors previously linked to resilience, suggesting that sleep might be an independent cognitive reserve resource. Beyond such mechanistic insights are potential therapeutic implications. Unlike many other cognitive reserve factors (e.g., years of education, prior job complexity), sleep is a modifiable factor. As such, it represents an intervention possibility that may aid the preservation of cognitive function in the face of AD pathology, both present moment and longitudinally.
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Affiliation(s)
- Zsófia Zavecz
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA.
| | - Vyoma D Shah
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Olivia G Murillo
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Raphael Vallat
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, 92617, USA
| | - Joseph R Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Matthew P Walker
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA.
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA.
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24
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Hampton OL, Mukherjee S, Properzi MJ, Schultz AP, Crane PK, Gibbons LE, Hohman TJ, Maruff P, Lim YY, Amariglio RE, Papp KV, Johnson KA, Rentz DM, Sperling RA, Buckley RF. Harmonizing the preclinical Alzheimer cognitive composite for multicohort studies. Neuropsychology 2023; 37:436-449. [PMID: 35862098 PMCID: PMC9859944 DOI: 10.1037/neu0000833] [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] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVES Studies are increasingly examining research questions across multiple cohorts using data from the preclinical Alzheimer cognitive composite (PACC). Our objective was to use modern psychometric approaches to develop a harmonized PACC. METHOD We used longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Harvard Aging Brain Study (HABS), and Australian Imaging, Biomarker and Lifestyle Study of Ageing (AIBL) cohorts (n = 2,712). We further demonstrated our method with the Anti-Amyloid Treatment of Asymptomatic Alzheimer's Disease (A4) Study prerandomized data (n = 4,492). For the harmonization method, we used confirmatory factor analysis (CFA) on the final visit of the longitudinal cohorts to determine parameters to generate latent PACC (lPACC) scores. Overlapping tests across studies were set as "anchors" that tied cohorts together, while parameters from unique tests were freely estimated. We performed validation analyses to assess the performance of lPACC versus the common standardized PACC (zPACC). RESULTS Baseline (BL) scores for the zPACC were centered on zero, by definition. The harmonized lPACC did not define a common mean of zero and demonstrated differences in baseline ability levels across the cohorts. Baseline lPACC slightly outperformed zPACC in the prediction of progression to dementia. Longitudinal change in the lPACC was more constrained and less variable relative to the zPACC. In combined-cohort analyses, longitudinal lPACC slightly outperformed longitudinal zPACC in its association with baseline β-amyloid status. CONCLUSIONS This study proposes procedures for harmonizing the PACC that make fewer strong assumptions than the zPACC, facilitating robust multicohort analyses. This implementation of item response theory lends itself to adapting across future cohorts with similar composites. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Olivia L. Hampton
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Shubhabrata Mukherjee
- Department of Medicine, Division of General Internal Medicine, University of Washington
| | - Michael J. Properzi
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Aaron P. Schultz
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Paul K. Crane
- Department of Medicine, Division of General Internal Medicine, University of Washington
| | - Laura E. Gibbons
- Department of Medicine, Division of General Internal Medicine, University of Washington
| | - Timothy J. Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Paul Maruff
- Cogstate Ltd., Melbourne, Victoria, Australia
| | - Yen Ying Lim
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Rebecca E. Amariglio
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
| | - Kathryn V. Papp
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
| | - Keith A. Johnson
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Dorene M. Rentz
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
| | - Reisa A. Sperling
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
| | - Rachel F. Buckley
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts, United States
- Department of Neurology, Brigham and Women’s Hospital, Center for Alzheimer Research and Treatment, Boston, Massachusetts, United States
- Melbourne School of Psychological Science, University of Melbourne
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25
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Fu JF, Lois C, Sanchez J, Becker JA, Rubinstein ZB, Thibault E, Salvatore AN, Sari H, Farrell ME, Guehl NJ, Normandin MD, Fakhri GE, Johnson KA, Price JC. Kinetic evaluation and assessment of longitudinal changes in reference region and extracerebral [ 18F]MK-6240 PET uptake. J Cereb Blood Flow Metab 2023; 43:581-594. [PMID: 36420769 PMCID: PMC10063833 DOI: 10.1177/0271678x221142139] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 10/17/2022] [Accepted: 11/06/2022] [Indexed: 11/25/2022]
Abstract
[18F]MK-6240 meningeal/extracerebral off-target binding may impact tau quantification. We examined the kinetics and longitudinal changes of extracerebral and reference regions. [18F]MK-6240 PET was performed in 24 cognitively-normal and eight cognitively-impaired subjects, with arterial samples in 13 subjects. Follow-up scans at 6.1 ± 0.5 (n = 25) and 13.3 ± 0.9 (n = 16) months were acquired. Extracerebral and reference region (cerebellar gray matter (CerGM)-based, cerebral white matter (WM), pons) uptake were evaluated using standardized uptake values (SUV90-110), spectral analysis, and distribution volume. Longitudinal changes in SUV90-110 were examined. The impact of reference region on target region outcomes, partial volume correction (PVC) and regional erosion were evaluated. Eroded WM and pons showed lower variability, lower extracerebral contamination, and lower longitudinal changes than CerGM-based regions. CerGM-based regions resulted larger cross-sectional effect sizes for group differentiation. Extracerebral signal was high in 50% of subjects and exhibited irreversible kinetics and nonsignificant longitudinal changes over one-year but was highly variable at subject-level. PVC resulted in higher variability in reference region uptake and longitudinal changes. Our results suggest that eroded CerGM may be preferred for cross-sectional, whilst eroded WM or pons may be preferred for longitudinal [18F]MK-6240 studies. For CerGM, erosion was necessary (preferred over PVC) to address the heterogenous nature of extracerebral signal.
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Affiliation(s)
- Jessie Fanglu Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Cristina Lois
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Justin Sanchez
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - J Alex Becker
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Zoe B Rubinstein
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Emma Thibault
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Andrew N Salvatore
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Hasan Sari
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | | | - Nicolas J Guehl
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Marc D Normandin
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Georges El Fakhri
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Keith A Johnson
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
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26
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Ennis GE, Betthauser TJ, Koscik RL, Chin NA, Christian BT, Asthana S, Johnson SC, Bendlin BB. The relationship of insulin resistance and diabetes to tau PET SUVR in middle-aged to older adults. Alzheimers Res Ther 2023; 15:55. [PMID: 36932429 PMCID: PMC10022314 DOI: 10.1186/s13195-023-01180-2] [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: 12/14/2022] [Accepted: 01/31/2023] [Indexed: 03/19/2023]
Abstract
BACKGROUND Insulin resistance (IR) and type 2 diabetes have been found to increase the risk for Alzheimer's clinical syndrome in epidemiologic studies but have not been associated with tau tangles in neuropathological research and have been inconsistently associated with cerebrospinal fluid P-tau181. IR and type 2 diabetes are well-recognized vascular risk factors. Some studies suggest that cardiovascular risk may act synergistically with cortical amyloid to increase tau measured using tau PET. Utilizing data from largely nondemented middle-aged and older adult cohorts enriched for AD risk, we investigated the association of IR and diabetes to tau PET and whether amyloid moderated those relationships. METHODS Participants were enrolled in either the Wisconsin Registry for Alzheimer's Prevention (WRAP) or Wisconsin Alzheimer's Disease Research Center (WI-ADRC) Clinical Core. Two partially overlapping samples were studied: a sample characterized using HOMA-IR (n=280 WRAP participants) and a sample characterized on diabetic status (n=285 WRAP and n=109 WI-ADRC). IR was measured using the homeostasis model assessment of insulin resistance (HOMA-IR). Tau PET employing the radioligand 18F-MK-6240 was used to detect AD-specific aggregated tau. Linear regression tested the relationship of IR and diabetic status to tau PET standardized uptake value ratio (SUVR) within the entorhinal cortex and whether relationships were moderated by amyloid assessed by amyloid PET distribution volume ratio (DVR) and amyloid PET positivity status. RESULTS Neither HOMA-IR nor diabetic status was significantly associated with tau PET SUVR. The relationship between IR and tau PET SUVR was not moderated by amyloid PET DVR or positivity status. The association between diabetic status and tau PET SUVR was not significantly moderated by amyloid PET DVR but was significantly moderated by amyloid PET positivity status. Among the amyloid PET-positive participants, the estimated marginal tau PET SUVR mean was higher in the diabetic (n=6) relative to the nondiabetic group (n=88). CONCLUSION Findings indicate that IR may not be related to tau in generally healthy middle-aged and older adults who are in the early stages of the AD clinicopathologic continuum but suggest the need for additional research to investigate whether a synergistic relationship between type 2 diabetes and amyloid is associated with increased tau levels.
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Affiliation(s)
- Gilda E Ennis
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Nathaniel A Chin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Bradley T Christian
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, WI, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Wisconsin Alzheimer's Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Hospital Department of Veterans Affairs, Madison, WI, USA
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27
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Du L, Langhough R, Hermann BP, Jonaitis E, Betthauser TJ, Cody KA, Mueller K, Zuelsdorff M, Chin N, Ennis GE, Bendlin BB, Gleason CE, Christian BT, Plante DT, Chappell R, Johnson SC. Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention. Brain Commun 2023; 5:fcad039. [PMID: 36910417 PMCID: PMC9999364 DOI: 10.1093/braincomms/fcad039] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 12/09/2022] [Accepted: 02/22/2023] [Indexed: 02/25/2023] Open
Abstract
Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Kimberly Mueller
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Megan Zuelsdorff
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- University of Wisconsin-Madison School of Nursing, Madison, WI 53705, USA
| | - Nathaniel Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Gilda E Ennis
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Madison VA GRECC, William S. Middleton Memorial Hospital, Madison, WI 53705, USA
| | - Carey E Gleason
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Madison VA GRECC, William S. Middleton Memorial Hospital, Madison, WI 53705, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - David T Plante
- Department of Psychiatry, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53719, USA
| | - Rick Chappell
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
- Madison VA GRECC, William S. Middleton Memorial Hospital, Madison, WI 53705, USA
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28
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Based on Tau PET Radiomics Analysis for the Classification of Alzheimer's Disease and Mild Cognitive Impairment. Brain Sci 2023; 13:brainsci13020367. [PMID: 36831910 PMCID: PMC9953966 DOI: 10.3390/brainsci13020367] [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: 12/28/2022] [Revised: 02/06/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients.
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29
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Insel PS, Young CB, Aisen PS, Johnson KA, Sperling RA, Mormino EC, Donohue MC. Tau positron emission tomography in preclinical Alzheimer's disease. Brain 2023; 146:700-711. [PMID: 35962782 PMCID: PMC10169284 DOI: 10.1093/brain/awac299] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/01/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Rates of tau accumulation in cognitively unimpaired older adults are subtle, with magnitude and spatial patterns varying in recent reports. Regional accumulation also likely varies in the degree to which accumulation is amyloid-β-dependent. Thus, there is a need to evaluate the pattern and consistency of tau accumulation across multiple cognitively unimpaired cohorts and how these patterns relate to amyloid burden, in order to design optimal tau end points for clinical trials. Using three large cohorts of cognitively unimpaired older adults, the Anti-Amyloid Treatment in Asymptomatic Alzheimer's and companion study, Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (n = 447), the Alzheimer's Disease Neuroimaging Initiative (n = 420) and the Harvard Aging Brain Study (n = 190), we attempted to identify regions with high rates of tau accumulation and estimate how these rates evolve over a continuous spectrum of baseline amyloid deposition. Optimal combinations of regions, tailored to multiple ranges of baseline amyloid burden as hypothetical clinical trial inclusion criteria, were tested and validated. The inferior temporal cortex, fusiform gyrus and middle temporal cortex had the largest effect sizes of accumulation in both longitudinal cohorts when considered individually. When tau regions of interest were combined to find composite weights to maximize the effect size of tau change over time, both longitudinal studies exhibited a similar pattern-inferior temporal cortex, almost exclusively, was optimal for participants with mildly elevated amyloid β levels. For participants with highly elevated baseline amyloid β levels, combined optimal composite weights were 53% inferior temporal cortex, 31% amygdala and 16% fusiform. At mildly elevated levels of baseline amyloid β, a sample size of 200/group required a treatment effect of 0.40-0.45 (40-45% slowing of tau accumulation) to power an 18-month trial using the optimized composite. Neither a temporal lobe composite nor a global composite reached 80% power with 200/group with an effect size under 0.5. The focus of early tau accumulation on the medial temporal lobe has resulted from the observation that the entorhinal cortex is the initial site to show abnormal levels of tau with age. However, these abnormal levels do not appear to be the result of a high rate of accumulation in the short term, but possibly a more moderate rate occurring early with respect to age. While the entorhinal cortex plays a central role in the early appearance of tau, it may be the inferior temporal cortex that is the critical region for rapid tau accumulation in preclinical Alzheimer's disease.
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Affiliation(s)
- Philip S Insel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Paul S Aisen
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | - Keith A Johnson
- Department of Neurology, Harvard Aging Brain Study, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Harvard Aging Brain Study, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Michael C Donohue
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
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Gellersen HM, Trelle AN, Farrar BG, Coughlan G, Korkki SM, Henson RN, Simons JS. Medial temporal lobe structure, mnemonic and perceptual discrimination in healthy older adults and those at risk for mild cognitive impairment. Neurobiol Aging 2023; 122:88-106. [PMID: 36516558 DOI: 10.1016/j.neurobiolaging.2022.11.004] [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: 05/13/2022] [Revised: 11/02/2022] [Accepted: 11/03/2022] [Indexed: 11/10/2022]
Abstract
Cognitive tests sensitive to the integrity of the medial temporal lobe (MTL), such as mnemonic discrimination of perceptually similar stimuli, may be useful early markers of risk for cognitive decline in older populations. Perceptual discrimination of stimuli with overlapping features also relies on MTL but remains relatively unexplored in this context. We assessed mnemonic discrimination in two test formats (Forced Choice, Yes/No) and perceptual discrimination of objects and scenes in 111 community-dwelling older adults at different risk status for cognitive impairment based on neuropsychological screening. We also investigated associations between performance and MTL sub-region volume and thickness. The at-risk group exhibited reduced entorhinal thickness and impaired perceptual and mnemonic discrimination. Perceptual discrimination impairment partially explained group differences in mnemonic discrimination and correlated with entorhinal thickness. Executive dysfunction accounted for Yes/No deficits in at-risk adults, demonstrating the importance of test format for the interpretation of memory decline. These results suggest that perceptual discrimination tasks may be useful tools for detecting incipient cognitive impairment related to reduced MTL integrity in nonclinical populations.
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Affiliation(s)
- Helena M Gellersen
- Department of Psychology, University of Cambridge, Cambridge, UK; German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | | | | | - Gillian Coughlan
- Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Saana M Korkki
- Aging Research Center, Karolinska Institute and Stockholm University, Stockholm, Sweden
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit and Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jon S Simons
- Department of Psychology, University of Cambridge, Cambridge, UK.
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31
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Young CB, Johns E, Kennedy G, Belloy ME, Insel PS, Greicius MD, Sperling RA, Johnson KA, Poston KL, Mormino EC. APOE effects on regional tau in preclinical Alzheimer's disease. Mol Neurodegener 2023; 18:1. [PMID: 36597122 PMCID: PMC9811772 DOI: 10.1186/s13024-022-00590-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 12/14/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND APOE variants are strongly associated with abnormal amyloid aggregation and additional direct effects of APOE on tau aggregation are reported in animal and human cell models. The degree to which these effects are present in humans when individuals are clinically unimpaired (CU) but have abnormal amyloid (Aβ+) remains unclear. METHODS We analyzed data from CU individuals in the Anti-Amyloid Treatment in Asymptomatic AD (A4) and Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) studies. Amyloid PET data were available for 4486 participants (3163 Aβ-, 1323 Aβ+) and tau PET data were available for a subset of 447 participants (55 Aβ-, 392 Aβ+). Linear models examined APOE (number of e2 and e4 alleles) associations with global amyloid and regional tau burden in medial temporal lobe (entorhinal, amygdala) and early neocortical regions (inferior temporal, inferior parietal, precuneus). Consistency of APOE4 effects on regional tau were examined in 220 Aβ + CU and mild cognitive impairment (MCI) participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS APOE2 and APOE4 were associated with lower and higher amyloid positivity rates, respectively. Among Aβ+ CU, e2 and e4 were associated with reduced (-12 centiloids per allele) and greater (+15 centiloids per allele) continuous amyloid burden, respectively. APOE2 was associated with reduced regional tau in all regions (-0.05 to -0.09 SUVR per allele), whereas APOE4 was associated with greater regional tau (+0.02 to +0.07 SUVR per allele). APOE differences were confirmed by contrasting e3/e3 with e2/e3 and e3/e4. Mediation analyses among Aβ+ s showed that direct effects of e2 on regional tau were present in medial temporal lobe and early neocortical regions, beyond an indirect pathway mediated by continuous amyloid burden. For e4, direct effects on regional tau were only significant in medial temporal lobe. The magnitude of protective e2 effects on regional tau was consistent across brain regions, whereas detrimental e4 effects were greatest in medial temporal lobe. APOE4 patterns were confirmed in Aβ+ ADNI participants. CONCLUSIONS APOE influences early regional tau PET burden, above and beyond effects related to cross-sectional amyloid PET burden. Therapeutic strategies targeting underlying mechanisms related to APOE may modify tau accumulation among Aβ+ individuals.
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Affiliation(s)
- Christina B Young
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA.
| | - Emily Johns
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Gabriel Kennedy
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Michael E Belloy
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Philip S Insel
- University of California San Francisco, San Francisco, CA, USA
| | - Michael D Greicius
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Reisa A Sperling
- Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Keith A Johnson
- Brigham and Women's Hospital, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Kathleen L Poston
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
| | - Elizabeth C Mormino
- Stanford University School of Medicine, 453 Quarry Rd., Palo Alto, Stanford, CA, 94304, USA
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Walsh T, Duff L, Riviere ME, Tariot PN, Doak K, Smith M, Borowsky B, Lopez Lopez C, Arratia PC, Liu F, Scholten I, Gordon D, Arbuckle J, Graf A, Quinn M, Ricart J, Langbaum JB. Outreach, Screening, and Randomization of APOE ε4 Carriers into an Alzheimer's Prevention Trial: A global Perspective from the API Generation Program. J Prev Alzheimers Dis 2023; 10:453-463. [PMID: 37357285 PMCID: PMC10426731 DOI: 10.14283/jpad.2023.27] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) prevention trials require a large outreach and screening funnel to identify cognitively unimpaired adults who meet the study's inclusion criteria, such as certain clinical or demographic criteria, genetic risk factors, and/or biomarker evidence of the disease. OBJECTIVES Describe tactics and strategies to identify and enroll cognitively unimpaired adults with one (heterozygotes [HT]) or two (homozygotes [HM]) copies of the APOE ε4 allele, a genetic risk factor for dementia due to AD, into the Alzheimer's Prevention Initiative (API) Generation Program, the largest and only prevention trials for late onset AD using this enrichment technique. DESIGN AND SETTING The Generation Program was comprised of two global, randomized, double-blind, placebo-controlled, parallel group adaptive design with variable treatment duration clinical trials. Generation Study 1 randomized participants into one of two cohorts: Cohort 1 which evaluated CAD106 vs. placebo or Cohort 2 which evaluated umibecestat vs placebo. Generation Study 2 randomized participants into two doses of umibecestat vs. placebo. The Generation Program was terminated early in 2019, while enrollment was still occurring. PARTICIPANTS Both Generation Study 1 and Generation Study 2 enrolled cognitively unimpaired APOE ε4 HMs aged 60-75; Generation Study 2 also enrolled APOE ε4 HTs ages 60-75 with elevated brain amyloid. METHODS AND MEASUREMENTS Describe results of the centralized and localized outreach, recruitment, screening strategies and tactics as well as characteristics of sites successful at enrolling genetically eligible participants, with a particular focus on APOE ε4 HMs given the 2-3% prevalence of this genotype. RESULTS At the time the trial program was terminated, 35,333 individuals had consented to the optional prescreening ICF1a/ICFA and provided a sample of DNA for APOE genotyping, 1,138 APOE ε4 HMs consented to screening for Generation Study 1 (ICF1b), and 1,626 APOE ε4 carriers were randomized into either Generation Study 1 or Generation Study 2. Genetic testing registries, partnerships with genetic testing/counseling companies, and the optional prescreening ICF1a/ICFA were the most successful strategies for identifying genetically eligible participants for screening. CONCLUSIONS It is feasible to recruit, screen and randomize cognitively unimpaired APOE ε4 carriers, particularly APOE ε4 HMs for a global AD prevention trial. The Generation Program was on track to complete enrollment by end of 2019. Factors that were key to this success included: working with sites to develop customizable outreach, recruitment, and screening programs specific to their site needs, providing forums for sites to exchange best practices, and developing partnerships between the sponsor team and trial sites.
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Affiliation(s)
- T Walsh
- Jessica Langbaum, PhD, Banner Alzheimer's Institute, 901 E. Willetta Street, Phoenix, AZ 85006, USA,
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Kwan ATH, Arfaie S, Therriault J, Azizi Z, Lussier FZ, Tissot C, Chamoun M, Bezgin G, Servaes S, Stevenon J, Rahmouni N, Pallen V, Gauthier S, Rosa-Neto P. Medial temporal tau predicts memory decline in cognitively unimpaired elderly. Brain Commun 2022; 5:fcac325. [PMID: 36627889 PMCID: PMC9814120 DOI: 10.1093/braincomms/fcac325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 10/05/2022] [Accepted: 12/07/2022] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease can be detected in living people using in vivo biomarkers of amyloid-β and tau, even in the absence of cognitive impairment during the preclinical phase. [18F]-MK-6420 is a high-affinity PET tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early Alzheimer's disease symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau-PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the translational biomarkers in ageing and dementia study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau-PET with [18F]-MK-6420 and amyloid-β PET with [18F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke or other neurological disorders. There were 111 eligible participants selected based on the availability of amyloid-β PET, tau-PET, MRI and APOEɛ4 genotyping. Among these participants, the mean standard deviation age was 70.1 (8.6) years; 20 (18%) were tau-PET-positive and 71 of 111 (63.9%) were women. A significant association between the baseline Braak Stages I-II [18F]-MK-6240 standardized uptake value ratio positivity and change in composite memory score were observed at the 12-month follow-up, after correcting for age, sex and years of education [logical memory and Rey Auditory Verbal Learning Test, standardized beta = -0.52 (-0.82-0.21), P < 0.001, for dichotomized tau-PET and -1.22 (-1.84-(-0.61)], P < 0.0001, for continuous tau-PET]. Moderate cognitive decline was observed for A + T + over the follow-up period, whereas no significant change was observed for A-T+, A + T- and A-T-, although it should be noted that the A-T + group was small. Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [18F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [18F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of Alzheimer's disease defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [18F]-MK-6420 PET provides us with hope that living patients with Alzheimer's disease may be diagnosed during the preclinical phase before it is too late.
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Affiliation(s)
| | | | - Joseph Therriault
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Zahra Azizi
- Department of Medicine, McGill University Health Centre, Montreal, QC H3G 2M1, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Cecile Tissot
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Jenna Stevenon
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Vanessa Pallen
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Mental Health University Institute, Le Centre Intégré Universitaire de Santé et de Services Sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Montreal, QC H4H 1R3, Canada,Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 1A1, Canada
| | - Pedro Rosa-Neto
- Correspondence to: Pedro Rosa-Neto, MD, PhD Translational Neuroimaging Laboratory The McGill University Research Centre for Studies in Aging Douglas Hospital, McGill University 6875 LaSalle Blvd— - FBC Room 3149 Montréal, Québec H4H 1R3, Canada E-mail:
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Ashton NJ, Janelidze S, Mattsson-Carlgren N, Binette AP, Strandberg O, Brum WS, Karikari TK, González-Ortiz F, Di Molfetta G, Meda FJ, Jonaitis EM, Koscik RL, Cody K, Betthauser TJ, Li Y, Vanmechelen E, Palmqvist S, Stomrud E, Bateman RJ, Zetterberg H, Johnson SC, Blennow K, Hansson O. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer's trial selection and disease monitoring. Nat Med 2022; 28:2555-2562. [PMID: 36456833 PMCID: PMC9800279 DOI: 10.1038/s41591-022-02074-w] [Citation(s) in RCA: 100] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 10/03/2022] [Indexed: 12/03/2022]
Abstract
Blood biomarkers indicative of Alzheimer's disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4-6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer's Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fernándo González-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Francisco J Meda
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Karly Cody
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - 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
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- ADx NeuroSciences, Technologiepark 94, Ghent, Belgium.
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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Microbiota-derived metabolite Indoles induced aryl hydrocarbon receptor activation and inhibited neuroinflammation in APP/PS1 mice. Brain Behav Immun 2022; 106:76-88. [PMID: 35961580 DOI: 10.1016/j.bbi.2022.08.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/23/2022] [Accepted: 08/05/2022] [Indexed: 01/12/2023] Open
Abstract
Gut microbiota alterations might affect the development of Alzheimer's disease (AD) through microbiota-derived metabolites. For example, microbiota-derived Indoles via tryptophan metabolism prevented Aβ accumulation and Tau hyperphosphorylation, restored synaptic plasticity, and then promoted the cognitive and behavioral ability of APP/PS1 mice. The imbalanced compositions of Indoles-producing bacteria with tryptophan deficiency were found in male APP/PS1 mice, but the molecular mechanisms remained unclear. Our current study revealed that Indoles (including indole, indole-3-acetic acid and indole-3-propionic acid) upregulated the production of aryl hydrocarbon receptor (AhR), inhibited the activation of the NF-κB signal pathway as well as the formation of the NLRP3 inflammasome, reduced the release of inflammatory cytokines, including TNF-α, IL-6, IL-1β and IL-18, alleviating the inflammatory response of APP/PS1 mice. These findings demonstrated the roles of Indoles-producing bacteria in activating the AhR pathway to regulate neuroinflammation of AD through gut microbiota-derived Indoles, which implied a novel way for AD treatment.
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Xu Y, Xiong H, Zhang B, Lee I, Xie J, Li M, Zhang H, Seung Kim J. Photodynamic Alzheimer’s disease therapy: From molecular catalysis to photo-nanomedicine. Coord Chem Rev 2022. [DOI: 10.1016/j.ccr.2022.214726] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Strikwerda-Brown C, Hobbs DA, Gonneaud J, St-Onge F, Binette AP, Ozlen H, Provost K, Soucy JP, Buckley RF, Benzinger TLS, Morris JC, Villemagne VL, Doré V, Sperling RA, Johnson KA, Rowe CC, Gordon BA, Poirier J, Breitner JCS, Villeneuve S. Association of Elevated Amyloid and Tau Positron Emission Tomography Signal With Near-Term Development of Alzheimer Disease Symptoms in Older Adults Without Cognitive Impairment. JAMA Neurol 2022; 79:975-985. [PMID: 35907254 PMCID: PMC9339146 DOI: 10.1001/jamaneurol.2022.2379] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 06/24/2022] [Indexed: 12/12/2022]
Abstract
Importance National Institute on Aging-Alzheimer's Association (NIA-AA) workgroups have proposed biological research criteria intended to identify individuals with preclinical Alzheimer disease (AD). Objective To assess the clinical value of these biological criteria to identify older individuals without cognitive impairment who are at near-term risk of developing symptomatic AD. Design, Setting, and Participants This longitudinal cohort study used data from 4 independent population-based cohorts (PREVENT-AD, HABS, AIBL, and Knight ADRC) collected between 2003 and 2021. Participants were older adults without cognitive impairment with 1 year or more of clinical observation after amyloid β and tau positron emission tomography (PET). Median clinical follow-up after PET ranged from 1.94 to 3.66 years. Exposures Based on binary assessment of global amyloid burden (A) and a composite temporal region of tau PET uptake (T), participants were stratified into 4 groups (A+T+, A+T-, A-T+, A-T-). Presence (+) or absence (-) of neurodegeneration (N) was assessed using temporal cortical thickness. Main Outcomes and Measures Each cohort was analyzed separately. Primary outcome was clinical progression to mild cognitive impairment (MCI), identified by a Clinical Dementia Rating score of 0.5 or greater in Knight ADRC and by consensus committee review in the other cohorts. Clinical raters were blind to imaging, genetic, and fluid biomarker data. A secondary outcome was cognitive decline, based on a slope greater than 1.5 SD below the mean of an independent subsample of individuals without cognitive impairment. Outcomes were compared across the biomarker groups. Results Among 580 participants (PREVENT-AD, 128; HABS, 153; AIBL, 48; Knight ADRC, 251), mean (SD) age ranged from 67 (5) to 76 (6) years across cohorts, with between 55% (137/251) and 74% (95/128) female participants. Across cohorts, 33% to 83% of A+T+ participants progressed to MCI during follow-up (mean progression time, 2-2.72 years), compared with less than 20% of participants in other biomarker groups. Progression further increased to 43% to 100% when restricted to A+T+(N+) individuals. Cox proportional hazard ratios for progression to MCI in the A+T+ group vs other biomarker groups were all 5 or greater. Many A+T+ nonprogressors also showed longitudinal cognitive decline, while cognitive trajectories in other groups remained predominantly stable. Conclusions and Relevance The clinical prognostic value of NIA-AA research criteria was confirmed in 4 independent cohorts, with most A+T+(N+) older individuals without cognitive impairment developing AD symptoms within 2 to 3 years.
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Affiliation(s)
- Cherie Strikwerda-Brown
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Diana A. Hobbs
- Washington University School of Medicine, St Louis, Missouri
| | - Julie Gonneaud
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | - Frédéric St-Onge
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Alexa Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hazal Ozlen
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Karine Provost
- Centre Hospitalier de l’Université de Montréal, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada
| | - Rachel F. Buckley
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | | | - John C. Morris
- Washington University School of Medicine, St Louis, Missouri
| | | | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Victoria, Australia
| | - Reisa A. Sperling
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Keith A. Johnson
- Department of Neurology, Massachusetts General Hospital, Boston
- Center for Alzheimer Research and Treatment, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Christopher C. Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Victoria, Australia
| | - Brian A. Gordon
- Washington University School of Medicine, St Louis, Missouri
| | - Judes Poirier
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - John C. S. Breitner
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Sylvia Villeneuve
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec, Canada
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Lao PJ, Boehme AK, Morales C, Laing KK, Chesebro A, Igwe KC, Gutierrez J, Gu Y, Stern Y, Schupf N, Manly JJ, Mayeux R, Brickman AM. Amyloid, cerebrovascular disease, and neurodegeneration biomarkers are associated with cognitive trajectories in a racially and ethnically diverse, community-based sample. Neurobiol Aging 2022; 117:83-96. [PMID: 35679806 PMCID: PMC9997572 DOI: 10.1016/j.neurobiolaging.2022.05.004] [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: 10/19/2021] [Revised: 05/03/2022] [Accepted: 05/06/2022] [Indexed: 02/01/2023]
Abstract
We characterized the additive contribution of cerebrovascular biomarkers to amyloid and neurodegeneration biomarkers (AV(N)) when modeling prospective, longitudinal cognitive trajectories within 3 major racial/ethnic groups. Participants (n = 172; age = 69-96 years; 62% women; 31%/49%/20% Non-Hispanic White/Non-Hispanic Black/Hispanic) from the Washington Heights-Inwood Columbia Aging Project were assessed for amyloid (Florbetaben PET), neurodegeneration (cortical thickness, hippocampal volume), and cerebrovascular disease (white matter hyperintensity (WMH), infarcts). Neuropsychological assessments occurred every 2.3 ± 0.6 years for up to 6 visits (follow-up time: 4.2 ± 3.2 years). Linear mixed-effects models were stratified by race/ethnicity groups. Higher amyloid was associated with faster memory decline in all 3 racial/ethnic groups, but was related to faster cognitive decline beyond memory in minoritized racial/ethnic groups. Higher WMH was associated with faster language, processing speed/executive function, and visuospatial ability decline in Non-Hispanic Black participants, while infarcts were associated with faster processing speed/executive function decline in Non-Hispanic White participants. Complementary information from AD, neurodegenerative, and cerebrovascular biomarkers explain decline in multiple cognitive domains, which may differ within each racial/ethnic group. Importantly, treatment strategies exist to minimize vascular contributions to cognitive decline.
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Affiliation(s)
- Patrick J Lao
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Amelia K Boehme
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Clarissa Morales
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Krystal K Laing
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Anthony Chesebro
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Kay C Igwe
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Jose Gutierrez
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Yian Gu
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Yaakov Stern
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Nicole Schupf
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Jennifer J Manly
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Richard Mayeux
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University, New York, NY, USA; Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Adam M Brickman
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Gertrude H. Sergievsky, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
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Gjini K, Casey C, Tanabe S, Bo A, Parker M, White M, Kunkel D, Lennertz R, Pearce RA, Betthauser T, Christian BT, Johnson SC, Bendlin BB, Sanders RD. Greater tau pathology is associated with altered predictive coding. Brain Commun 2022; 4:fcac209. [PMID: 36226138 PMCID: PMC9547525 DOI: 10.1093/braincomms/fcac209] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 05/04/2022] [Accepted: 08/12/2022] [Indexed: 01/25/2023] Open
Abstract
Altered predictive coding may underlie the reduced auditory mismatch negativity amplitude observed in patients with dementia. We hypothesized that accumulating dementia-associated pathologies, including amyloid and tau, lead to disturbed predictions of our sensory environment. This would manifest as increased reliance on 'observed' sensory information with an associated increase in feedforward, and decrease in feedback, signalling. To test this hypothesis, we studied a cross-sectional cohort of participants who underwent PET imaging and high-density EEG during an oddball paradigm, and used dynamic casual modelling and Bayesian statistics to make inferences about the neuronal architectures (generators) and mechanisms (effective connectivity) underlying the observed auditory-evoked responses. Amyloid-β imaging with [C-11] Pittsburgh Compound-B PET was qualitatively rated using established criteria. Tau-positive PET scans, with [F-18]MK-6240, were defined by an MK-6240 standardized uptake value ratio positivity threshold at 2 standard deviations above the mean of the Amyloid(-) group in the entorhinal cortex (entorhinal MK-6240 standardized uptake value ratio > 1.27). The cross-sectional cohort included a total of 56 participants [9 and 13 participants in the Tau(+) and Amyloid(+) subgroups, respectively: age interquartile range of (73.50-75.34) and (70.5-75.34) years, 56 and 69% females, respectively; 46 and 43 participants in the Tau(-) and Amyloid(-) subgroups, respectively: age interquartile range of (62.72-72.5) and (62.64-72.48) years, 67 and 65% females, respectively]. Mismatch negativity amplitudes were significantly smaller in Tau+ subgroup than Tau- subgroup (cluster statistics corrected for multiple comparisons: P = 0.028). Dynamic causal modelling showed that tau pathology was associated with increased feedforward connectivity and decreased feedback connectivity, with increased excitability of superior temporal gyrus but not inferior frontal regions. This effect on superior temporal gyrus was consistent with the distribution of tau disease on PET in these participants, indicating that the observed differences in mismatch negativity reflect pathological changes evolving in preclinical dementia. Exclusion of participants with diagnosed mild cognitive impairment or dementia did not affect the results. These observational data provide proof of concept that abnormalities in predictive coding may be detected in the preclinical phase of Alzheimer's disease. This framework also provides a construct to understand how progressive impairments lead to loss of orientation to the sensory world in dementia. Based on our modelling results, plus animal models indicating that Alzheimer's disease pathologies produce hyperexcitability of higher cortical regions through local disinhibition, mismatch negativity might be a useful monitor to deploy as strategies that target interneuron dysfunction are developed.
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Affiliation(s)
- Klevest Gjini
- Department of Neurology, University of Wisconsin, Madison, WI, USA
| | - Cameron Casey
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Sean Tanabe
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Amber Bo
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Margaret Parker
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Marissa White
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - David Kunkel
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Richard Lennertz
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Robert A Pearce
- Department of Anesthesiology, University of Wisconsin, Madison, WI, USA
| | - Tobey Betthauser
- Department of Medicine, University of Wisconsin, Madison, WI, USA
| | | | | | | | - Robert D Sanders
- Specialty of Anaesthetics, University of Sydney, Camperdown, Australia
- Department of Anaesthetics, Royal Prince Alfred Hospital, Camperdown, Australia
- Central Clinical School & NHMRC Clinical Trials Centre, Institute of Academic Surgery, Camperdown, Australia
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Pirani A, Nasreddine Z, Neviani F, Fabbo A, Rocchi MB, Bertolotti M, Tulipani C, Galassi M, Belvedere Murri M, Neri M. MoCA 7.1: Multicenter Validation of the First Italian Version of Montreal Cognitive Assessment. J Alzheimers Dis Rep 2022; 6:509-520. [PMID: 36186724 PMCID: PMC9484132 DOI: 10.3233/adr-210053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Accepted: 07/13/2022] [Indexed: 12/04/2022] Open
Abstract
Background: The early detection of neurocognitive disorders, especially when mild, is a key issue of health care systems including the Italian Dementia National Plan. The Mini-Mental State Examination (MMSE), i.e., the reference screening tool for dementia in Italian Memory Clinics, has low sensitivity in detecting mild cognitive impairment (MCI) or mild dementia. Objective: Availability of a 10-minute screening test sensitive to MCI and mild dementia, such as the Montreal Cognitive Assessment (MoCA), is relevant in the field. This study presents initial validity and reliability data for the Italian version of MoCA 7.1 that is being collected as part of a large ongoing longitudinal study to evaluate the rate of incident MCI and dementia in older adults. Methods: MoCA 7.1 and MMSE were administered to cognitive impaired patients (n = 469; 214 with MCI, 255 with dementia; mean age: 75.5; 52% females,) and healthy older adults (n = 123, mean age: 69.7, 64 % females). Results: Test-retest (0.945, p < 0.001) and inter-rater (0.999, p < 0.001) reliability of MoCA 7.1, assessed on randomly selected participants with normal cognition, MCI, dementia, were significant. MoCA 7.1 showed adequate sensitivity (95.3%) and specificity (84.5%) in detecting MCI compared to MMSE (sensitivity: 53.8%; specificity: 87.5%). The Area Under the Curve of MoCA 7.1 was significantly greater than that of MMSE (0.963 versus 0.742). MoCA 7.1 showed similar results in detecting both MCI and dementia. Conclusion: MoCA 7.1 is a reliable and useful tool that can aid in the diagnosis of MCI and dementia in the Italian population.
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Affiliation(s)
- Alessandro Pirani
- Center for Cognitive Disorders and Dementia, Health County of Ferrara, Cento, Italy
- Alzheimer’s Association “Francesco Mazzuca”, Cento, (Fe), Italy
| | | | - Francesca Neviani
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
| | - Andrea Fabbo
- Dementia Program, HealthTrust, Health County of Modena, Italy
| | | | - Marco Bertolotti
- Division of Geriatric Medicine, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia and University Hospital of Modena, Modena, Italy
- Center for Gerontological Evaluation and Research, University of Modena and Reggio Emilia, Modena, Italy
| | - Cristina Tulipani
- Center for Cognitive Disorders and Dementia, Health County of Ferrara, Cento, Italy
- Alzheimer’s Association “Francesco Mazzuca”, Cento, (Fe), Italy
| | - Matteo Galassi
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
| | - Martino Belvedere Murri
- Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Italy
| | - Mirco Neri
- Center for Cognitive Disorders and Dementia. Chair of Geriatrics, University of Modenaand Reggio Emilia, Italy
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Farrell C, Mumford P, Wiseman FK. Rodent Modeling of Alzheimer's Disease in Down Syndrome: In vivo and ex vivo Approaches. Front Neurosci 2022; 16:909669. [PMID: 35747206 PMCID: PMC9209729 DOI: 10.3389/fnins.2022.909669] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/16/2022] [Indexed: 12/30/2022] Open
Abstract
There are an estimated 6 million people with Down syndrome (DS) worldwide. In developed countries, the vast majority of these individuals will develop Alzheimer's disease neuropathology characterized by the accumulation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles within the brain, which leads to the early onset of dementia (AD-DS) and reduced life-expectancy. The mean age of onset of clinical dementia is ~55 years and by the age of 80, approaching 100% of individuals with DS will have a dementia diagnosis. DS is caused by trisomy of chromosome 21 (Hsa21) thus an additional copy of a gene(s) on the chromosome must cause the development of AD neuropathology and dementia. Indeed, triplication of the gene APP which encodes the amyloid precursor protein is sufficient and necessary for early onset AD (EOAD), both in people who have and do not have DS. However, triplication of other genes on Hsa21 leads to profound differences in neurodevelopment resulting in intellectual disability, elevated incidence of epilepsy and perturbations to the immune system. This different biology may impact on how AD neuropathology and dementia develops in people who have DS. Indeed, genes on Hsa21 other than APP when in three-copies can modulate AD-pathogenesis in mouse preclinical models. Understanding this biology better is critical to inform drug selection for AD prevention and therapy trials for people who have DS. Here we will review rodent preclinical models of AD-DS and how these can be used for both in vivo and ex vivo (cultured cells and organotypic slice cultures) studies to understand the mechanisms that contribute to the early development of AD in people who have DS and test the utility of treatments to prevent or delay the development of disease.
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Blessing EM, Parekh A, Betensky RA, Babb J, Saba N, Debure L, Varga AW, Ayappa I, Rapoport DM, Butler TA, de Leon MJ, Wisniewski T, Lopresti BJ, Osorio RS. Association between lower body temperature and increased tau pathology in cognitively normal older adults. Neurobiol Dis 2022; 171:105748. [PMID: 35550158 DOI: 10.1016/j.nbd.2022.105748] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 04/25/2022] [Accepted: 05/05/2022] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND Preclinical studies suggest body temperature (Tb) and consequently brain temperature has the potential to bidirectionally interact with tau pathology in Alzheimer's Disease (AD). Tau phosphorylation is substantially increased by a small (<1 °C) decrease in temperature within the human physiological range, and thermoregulatory nuclei are affected by tau pathology early in the AD continuum. In this study we evaluated whether Tb (as a proxy for brain temperature) is cross-sectionally associated with clinically utilized markers of tau pathology in cognitively normal older adults. METHODS Tb was continuously measured with ingestible telemetry sensors for 48 h. This period included two nights of nocturnal polysomnography to delineate whether Tb during waking vs sleep is differentially associated with tau pathology. Tau phosphorylation was assessed with plasma and cerebrospinal fluid (CSF) tau phosphorylated at threonine 181 (P-tau), sampled the day following Tb measurement. In addition, neurofibrillary tangle (NFT) burden in early Braak stage regions was imaged with PET-MR using the [18F]MK-6240 radiotracer on average one month later. RESULTS Lower Tb was associated with increased NFT burden, as well as increased plasma and CSF P-tau levels (p < 0.05). NFT burden was associated with lower Tb during waking (p < 0.05) but not during sleep intervals. Plasma and CSF P-tau levels were highly correlated with each other (p < 0.05), and both variables were correlated with tau tangle radiotracer uptake (p < 0.05). CONCLUSIONS These results, the first available for human, suggest that lower Tb in older adults may be associated with increased tau pathology. Our findings add to the substantial preclinical literature associating lower body and brain temperature with tau hyperphosphorylation. CLINICAL TRIAL NUMBER NCT03053908.
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Affiliation(s)
- Esther M Blessing
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
| | - Ankit Parekh
- Mount Sinai Integrative Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States of America.
| | - Rebecca A Betensky
- Department of NYU School of Global Public Health, New York, NY 10016, United States of America.
| | - James Babb
- Alzheimer's Disease Research Center, Department of Neurology, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
| | - Natalie Saba
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
| | - Ludovic Debure
- Alzheimer's Disease Research Center, Department of Neurology, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
| | - Andrew W Varga
- Mount Sinai Integrative Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States of America.
| | - Indu Ayappa
- Mount Sinai Integrative Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States of America.
| | - David M Rapoport
- Mount Sinai Integrative Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States of America.
| | - Tracy A Butler
- Department of Neurology, Weill Cornell Medicine, New York, NY 10065, United States of America.
| | - Mony J de Leon
- Department of Neurology, Weill Cornell Medicine, New York, NY 10065, United States of America.
| | - Thomas Wisniewski
- Alzheimer's Disease Research Center, Department of Neurology, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, United States of America.
| | - Ricardo S Osorio
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, United States of America; Alzheimer's Disease Research Center, Department of Neurology, NYU Grossman School of Medicine, New York, NY 10016, United States of America.
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Young CB, Winer JR, Younes K, Cody KA, Betthauser TJ, Johnson SC, Schultz A, Sperling RA, Greicius MD, Cobos I, Poston KL, Mormino EC. Divergent Cortical Tau Positron Emission Tomography Patterns Among Patients With Preclinical Alzheimer Disease. JAMA Neurol 2022; 79:592-603. [PMID: 35435938 PMCID: PMC9016616 DOI: 10.1001/jamaneurol.2022.0676] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease. Objective To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+). Design, Setting, and Participants This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022. Main Outcomes and Measures Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical+) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined. Results The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL+). Individuals in the A+T cortical+ group were younger than those in the A+T MTL+ group (t61.867 = -2.597; P = .03). Across the A+T cortical+ and A+T MTL+ groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical+ and A+T MTL+ groups, whereas executive functioning scores were lower for the A+T cortical+ group than for the A+T MTL+ group. The prevalence of the A+T cortical+ group and tau patterns within the A+T cortical+ group were consistent in ADNI, HABS, and Wisconsin. Conclusions and Relevance This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.
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Affiliation(s)
- Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Joseph R Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Kyan Younes
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Karly A Cody
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.,Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison
| | - Aaron Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston.,Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Inma Cobos
- Department of Pathology, Stanford University School of Medicine, Stanford, California
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California
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Li TR, Yang Q, Hu X, Han Y. Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage. Curr Neuropharmacol 2022; 20:713-737. [PMID: 34030620 PMCID: PMC9878962 DOI: 10.2174/1570159x19666210524153901] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 04/27/2021] [Accepted: 05/08/2021] [Indexed: 11/22/2022] Open
Abstract
Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.
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Affiliation(s)
- Tao-Ran Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Qin Yang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Xiaochen Hu
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, 50924, Germany
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China;,Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China;,National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China;,School of Biomedical Engineering, Hainan University, Haikou, 570228, China;,Address correspondence to this author at the Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China; Tel: +86 13621011941; E-mail:
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45
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Kreisl WC, Lao PJ, Johnson A, Tomljanovic Z, Klein J, Polly K, Maas B, Laing KK, Chesebro AG, Igwe K, Razlighi QR, Honig LS, Yan X, Lee S, Mintz A, Luchsinger JA, Stern Y, Devanand DP, Brickman AM. Patterns of tau pathology identified with 18 F-MK-6240 PET imaging. Alzheimers Dement 2022; 18:272-282. [PMID: 34057284 PMCID: PMC8630090 DOI: 10.1002/alz.12384] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 04/11/2021] [Accepted: 04/14/2021] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Positron emission tomography (PET) imaging for neurofibrillary tau allows investigation of the in vivo spatiotemporal progression of Alzheimer's disease (AD) pathology. We evaluated the suitability of 18 F-MK-6240 in a clinical sample and determined the relationships among 18 F-MK-6240 binding, age, cognition, and cerebrospinal fluid (CSF)-based AD biomarkers. METHODS Participants (n = 101, 72 ± 9 years, 52% women) underwent amyloid PET, tau PET, structural T1-weighted magnetic resonance imaging, and neuropsychological evaluation. Twenty-one participants had lumbar puncture for CSF measurement of amyloid beta (Aβ)42 , tau, and phosphorylated tau (p-tau). RESULTS 18 F-MK-6240 recapitulated Braak staging and correlated with CSF tau and p-tau, normalized to Aβ42 . 18 F-MK-6240 negatively correlated with age across Braak regions in amyloid-positive participants, consistent with greater tau pathology in earlier onset AD. Domain-specific, regional patterns of 18 F-MK-6240 binding were associated with reduced memory, executive, and language performance, but only in amyloid-positive participants. DISCUSSION 18 F-MK-6240 can approximate Braak staging across the AD continuum and provide region-dependent insights into biomarker-based AD models.
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Affiliation(s)
- William Charles Kreisl
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Patrick J Lao
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Aubrey Johnson
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Zeljko Tomljanovic
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Julia Klein
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Krista Polly
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Benjamin Maas
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Krystal K Laing
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Anthony G Chesebro
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Kay Igwe
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | | | - Lawrence S Honig
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Xinyu Yan
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Seonjoo Lee
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
- Division of Mental Health Data Science, New York State Psychiatric Institute, New York, NY, USA
| | - Akiva Mintz
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
| | - José A Luchsinger
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, USA
| | - Yaakov Stern
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - D P Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
- Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA
| | - Adam M Brickman
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Brumberg J, Varrone A. New PET radiopharmaceuticals for imaging CNS diseases. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00002-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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Rivera‐Rivera LA, Eisenmenger L, Cody KA, Reher T, Betthauser T, Cadman RV, Rowley HA, Carlsson CM, Chin NA, Johnson SC, Johnson KM. Cerebrovascular stiffness and flow dynamics in the presence of amyloid and tau biomarkers. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12253. [PMID: 35005194 PMCID: PMC8719432 DOI: 10.1002/dad2.12253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 09/30/2021] [Indexed: 06/14/2023]
Abstract
INTRODUCTION This work investigated the relationship between cerebrovascular disease (CVD) markers and Alzheimer's disease (AD) biomarkers of amyloid beta deposition, and neurofibrillary tau tangles in subjects spanning the AD clinical spectrum. METHODS A total of 136 subjects participated in this study. Four groups were established based on AD biomarker positivity from positron emission tomography (amyloid [A] and tau [T]) and clinical diagnosis (cognitively normal [CN] and impaired [IM]). CVD markers were derived from structural and quantitative magnetic resonance imaging data. RESULTS Transcapillary pulse wave delay was significantly longer in controls compared to AT biomarker-confirmed groups (A+/T-/CN P < .001, A+/T+/CN P < .001, A+/T+/IM P = .003). Intracranial low-frequency oscillations were diminished in AT biomarker-confirmed groups both CN and impaired (A+/T-/CN P = .039, A+/T+/CN P = .007, A+/T+/IM P = .011). A significantly higher presence of microhemorrhages was measured in A+/T+/CN compared to controls (P = .006). DISCUSSION Cerebrovascular markers indicate increased vessel stiffness and reduced vasomotion in AT biomarker-positive subjects during preclinical AD.
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Affiliation(s)
- Leonardo A. Rivera‐Rivera
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of Medical PhysicsUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Laura Eisenmenger
- Department of RadiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Karly A. Cody
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Thomas Reher
- Department of RadiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Tobey Betthauser
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Robert V. Cadman
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Howard A. Rowley
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of RadiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterWilliam S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Kevin M. Johnson
- Department of Medical PhysicsUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of RadiologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
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Zou J, Park D, Johnson A, Feng X, Pardo M, France J, Tomljanovic Z, Brickman AM, Devanand DP, Luchsinger JA, Kreisl WC, Provenzano FA. Deep learning improves utility of tau PET in the study of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12264. [PMID: 35005197 PMCID: PMC8719427 DOI: 10.1002/dad2.12264] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 10/04/2021] [Accepted: 10/07/2021] [Indexed: 06/14/2023]
Abstract
INTRODUCTION Positron emission tomography (PET) imaging targeting neurofibrillary tau tangles is increasingly used in the study of Alzheimer's disease (AD), but its utility may be limited by conventional quantitative or qualitative evaluation techniques in earlier disease states. Convolutional neural networks (CNNs) are effective in learning spatial patterns for image classification. METHODS 18F-MK6240 (n = 320) and AV-1451 (n = 446) PET images were pooled from multiple studies. We performed iterations with differing permutations of radioligands, heuristics, and architectures. Performance was compared to a standard region of interest (ROI)-based approach on prediction of memory impairment. We visualized attention of the network to illustrate decision making. RESULTS Overall, models had high accuracy (> 80%) with good average sensitivity and specificity (75% and 82%, respectively), and had comparable or higher accuracy to the ROI standard. Visualizations of model attention highlight known characteristics of tau radioligand binding. DISCUSSION CNNs could improve tau PET's role in early disease and extend the utility of tau PET across generations of radioligands.
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Affiliation(s)
- James Zou
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - David Park
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Aubrey Johnson
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Xinyang Feng
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Michelle Pardo
- Department of MedicineColumbia University Medical CenterNew YorkNew YorkUSA
| | - Jeanelle France
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Zeljko Tomljanovic
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Adam M. Brickman
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
- Department of NeurologyCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Devangere P. Devanand
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
- New York State Psychiatric Institute and Department of PsychiatryColumbia University Medical CenterNew YorkNew YorkUSA
| | - José A. Luchsinger
- Department of MedicineColumbia University Medical CenterNew YorkNew YorkUSA
- Department of EpidemiologyColumbia University Medical CenterNew YorkNew YorkUSA
| | - William C. Kreisl
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
| | - Frank A. Provenzano
- The Taub Institute for Research on Alzheimer's Disease and the Aging BrainNew YorkNew YorkUSA
- Department of NeurologyCollege of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
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Ma LZ, Hu H, Wang ZT, Ou YN, Dong Q, Tan L, Yu JT. P-tau and neurodegeneration mediate the effect of β-amyloid on cognition in non-demented elders. Alzheimers Res Ther 2021; 13:200. [PMID: 34911582 PMCID: PMC8675473 DOI: 10.1186/s13195-021-00943-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/05/2021] [Indexed: 04/12/2023]
Abstract
BACKGROUND There are many pathological changes in the brains of Alzheimer's disease (AD) patients. For many years, the mainstream view on the pathogenesis of AD believes that β-amyloid (Aβ) usually acts independently in addition to triggering functions. However, the evidence now accumulating indicates another case that these pathological types have synergies. The objective of this study was to investigate whether effects of Aβ pathology on cognition were mediated by AD pathologies, including tau-related pathology (p-tau), neurodegeneration (t-tau, MRI measurements), axonal injury (NFL), synaptic dysfunction (neurogranin), and neuroinflammation (sTREM2, YKL-40). METHODS Three hundred seventy normal controls (CN) and 623 MCI patients from the ADNI (Alzheimer's Disease Neuroimaging Initiative) database were recruited in this research. Linear mixed-effects models were used to evaluate the associations of baseline Aβ with cognitive decline and biomarkers of several pathophysiological pathways. Causal mediation analyses with 10,000 bootstrapped iterations were conducted to explore the mediation effects of AD pathologies on cognition. RESULTS Tau-related pathology, neurodegeneration, neuroinflammation are correlated with the concentration of Aβ, even in CN participants. The results show that age, gender, and APOE ε4 carrier status have a moderating influence on some of these relationships. There is a stronger association of Aβ with biomarkers and cognitive changes in the elderly and females. In CN group, Aβ pathology is directly related to poor cognition and has no mediating effect (p < 0.05). In mild cognitive impairment, tau-related pathology (26.15% of total effect) and neurodegeneration (14.8% to 47.0% of total effect) mediate the impact of Aβ on cognition. CONCLUSIONS In conclusion, early Aβ accumulation has an independent effect on cognitive decline in CN and a tau, neurodegeneration-dependent effect in the subsequent cognitive decline in MCI patients.
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Affiliation(s)
- Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Hao Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Zuo-Teng Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China.
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