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Wiesman AI, Gallego-Rudolf J, Villeneuve S, Baillet S, Wilson TW. Alignments between cortical neurochemical systems, proteinopathy and neurophysiological alterations along the Alzheimer's disease continuum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.13.24305551. [PMID: 38645027 PMCID: PMC11030470 DOI: 10.1101/2024.04.13.24305551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Two neuropathological hallmarks of Alzheimer's disease (AD) are the accumulation of amyloid-β (Aβ) proteins and alterations in cortical neurophysiological signaling. Despite parallel research indicating disruption of multiple neurotransmitter systems in AD, it has been unclear whether these two phenomena are related to the neurochemical organization of the cortex. We leveraged task-free magnetoencephalography and positron emission tomography, with a cortical atlas of 19 neurotransmitters to study the alignment and interactions between alterations of neurophysiological signaling, Aβ deposition, and the neurochemical gradients of the human cortex. In patients with amnestic mild cognitive impairment (N = 18) and probable AD (N = 20), we found that changes in rhythmic, but not arrhythmic, cortical neurophysiological signaling relative to healthy controls (N = 20) are topographically aligned with cholinergic, serotonergic, and dopaminergic neurochemical systems. These neuro-physio-chemical alignments are related to the severity of cognitive and behavioral impairments. We also found that cortical Aβ plaques are preferentially deposited along neurochemical boundaries, and mediate how beta-band rhythmic cortical activity maps align with muscarinic acetylcholine receptors. Finally, we show in an independent dataset that many of these alignments manifest in the asymptomatic stages of cortical Aβ accumulation (N = 33; N = 71 healthy controls), particularly the Aβ-neurochemical alignments (57.1%) and neuro-physio-chemical alignments in the alpha frequency band (62.5%). Overall, the present study demonstrates that the expression of pathology in pre-clinical and clinical AD aligns topographically with the cortical distribution of chemical neuromodulator systems, scaling with clinical severity and with implications for potential pharmacotherapeutic pathways.
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Momota Y, Bun S, Hirano J, Kamiya K, Ueda R, Iwabuchi Y, Takahata K, Yamamoto Y, Tezuka T, Kubota M, Seki M, Shikimoto R, Mimura Y, Kishimoto T, Tabuchi H, Jinzaki M, Ito D, Mimura M. Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders. Sci Rep 2024; 14:7633. [PMID: 38561395 PMCID: PMC10984960 DOI: 10.1038/s41598-024-58223-3] [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: 09/12/2023] [Accepted: 03/26/2024] [Indexed: 04/04/2024] Open
Abstract
Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer's disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful prediction model for amyloid-beta (Aβ) deposition using source-based morphometry, using a data-driven algorithm based on independent component analyses. Additionally, we assessed how the predictive accuracies varied with the feature combinations. Data from 118 participants clinically diagnosed with various conditions such as AD, mild cognitive impairment, frontotemporal lobar degeneration, corticobasal syndrome, progressive supranuclear palsy, and psychiatric disorders, as well as healthy controls were used for the development of the model. We used structural MR images, cognitive test results, and apolipoprotein E status for feature selection. Three-dimensional T1-weighted images were preprocessed into voxel-based gray matter images and then subjected to source-based morphometry. We used a support vector machine as a classifier. We applied SHapley Additive exPlanations, a game-theoretical approach, to ensure model accountability. The final model that was based on MR-images, cognitive test results, and apolipoprotein E status yielded 89.8% accuracy and a receiver operating characteristic curve of 0.888. The model based on MR-images alone showed 84.7% accuracy. Aβ-positivity was correctly detected in non-AD patients. One of the seven independent components derived from source-based morphometry was considered to represent an AD-related gray matter volume pattern and showed the strongest impact on the model output. Aβ-positivity across neurological and psychiatric disorders was predicted with moderate-to-high accuracy and was associated with a probable AD-related gray matter volume pattern. An MRI-based data-driven machine learning approach can be beneficial as a diagnostic aid.
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Affiliation(s)
- Yuki Momota
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
- Department of Functional Brain Imaging Research, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-Ku, Chiba-Shi, Chiba, 263-8555, Japan
| | - Shogyoku Bun
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
| | - Jinichi Hirano
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan.
| | - Kei Kamiya
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Ryo Ueda
- Office of Radiation Technology, Keio University Hospital, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Yu Iwabuchi
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Keisuke Takahata
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
- Department of Functional Brain Imaging Research, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-Ku, Chiba-Shi, Chiba, 263-8555, Japan
| | - Yasuharu Yamamoto
- Department of Functional Brain Imaging Research, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, 4-9-1 Anagawa, Inage-Ku, Chiba-Shi, Chiba, 263-8555, Japan
| | - Toshiki Tezuka
- Department of Neurology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Masahito Kubota
- Department of Neurology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Morinobu Seki
- Department of Neurology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Ryo Shikimoto
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Yu Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Taishiro Kishimoto
- Psychiatry Department, Donald and Barbara Zucker School of Medicine, Hempstead, NY, 11549, USA
- Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Mori JP Tower F7, 1-3-1 Azabudai, Minato-ku, Tokyo, 106-0041, Japan
| | - Hajime Tabuchi
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Daisuke Ito
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
- Memory Center, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-Ku, Tokyo, 160-8582, Japan
| | - Masaru Mimura
- Center for Preventive Medicine, Keio University, Mori JP Tower 7th Floor, 1-3-1 Azabudai, Minato-ku, Tokyo, 106-0041, Japan
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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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Fonseca CS, Baker SL, Dobyns L, Janabi M, Jagust WJ, Harrison TM. Tau accumulation and atrophy predict amyloid independent cognitive decline in aging. Alzheimers Dement 2024; 20:2526-2537. [PMID: 38334195 PMCID: PMC11032527 DOI: 10.1002/alz.13654] [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: 08/24/2023] [Revised: 11/15/2023] [Accepted: 11/30/2023] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Amyloid beta (Aβ) and tau pathology are cross-sectionally associated with atrophy and cognitive decline in aging and Alzheimer's disease (AD). METHODS We investigated relationships between concurrent longitudinal measures of Aβ (Pittsburgh compound B [PiB] positron emission tomography [PET]), tau (flortaucipir [FTP] PET), atrophy (structural magnetic resonance imaging), episodic memory (EM), and non-memory (NM) in 78 cognitively healthy older adults (OA). RESULTS Entorhinal FTP change was correlated with EM decline regardless of Aβ, but meta-temporal FTP and global PiB change were only associated with EM and NM decline in Aβ+ OA. Voxel-wise analyses revealed significant associations between temporal lobe FTP change and EM decline in all groups. PiB and FTP change were not associated with structural change, suggesting a functional or microstructural mechanism linking these measures to cognitive decline. DISCUSSION Our results show that longitudinal Aβ is linked to cognitive decline only in the presence of elevated Aβ, but longitudinal temporal lobe tau is associated with memory decline regardless of Aβ status. HIGHLIGHTS Entorhinal tau change was associated with memory decline in older adults (OA), regardless of amyloid beta (Aβ). Greater meta-region of interest (ROI) tau change correlated with memory decline in Aβ+ OA. Voxel-wise temporal tau change correlated with memory decline, regardless of Aβ. Meta-ROI tau and global amyloid change correlated with non-memory change in Aβ+ OA. Tau and amyloid accumulation were not associated with structural change in OA.
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Affiliation(s)
- Corrina S. Fonseca
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Lindsey Dobyns
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Mustafa Janabi
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - William J. Jagust
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
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Maturana-Quijada P, Chavarría-Elizondo P, Del Cerro I, Martínez-Zalacaín I, Juaneda-Seguí A, Guinea-Izquierdo A, Gascón-Bayarri J, Reñé R, Urretavizcaya M, Menchón JM, Ferrer I, Soria V, Soriano-Mas C. Effective connectivity of the locus coeruleus in patients with late-life Major Depressive Disorder or mild cognitive impairment. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2024:S2950-2853(24)00015-2. [PMID: 38453029 DOI: 10.1016/j.sjpmh.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 03/09/2024]
Abstract
INTRODUCTION We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs). PARTICIPANTS 23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs. MATERIAL AND METHODS Participants were assessed in two time-points, 2 years apart. They underwent a resting-state functional magnetic resonance imaging and a high-resolution anatomical acquisition, as well as clinical assessments. Functional imaging data were analyzed with dynamic causal modeling, and parametric empirical Bayes model was used to map effective connectivity between 7 distinct nodes: 4 from the locus coeruleus and 3 regions displaying gray matter decreases during the two-year follow-up period. RESULTS Longitudinal analysis of structural data identified three clusters of larger over-time gray matter volume reduction in patients (MDD+aMCI vs. HCs): the right precuneus, and the visual association and parahippocampal cortices. aMCI patients showed decreased effective connectivity from the left rostral to caudal portions of the LC, while connectivity from the left rostral LC to the parahippocampal cortex increased. In MDD, there was a decline in effective connectivity across LC caudal seeds, and increased connectivity from the left rostral to the left caudal LC seed over time. Connectivity alterations with cortical regions involved cross-hemisphere increases and same-hemisphere decreases. CONCLUSIONS Our discoveries provide insight into the dynamic changes in effective connectivity in individuals with late-life MDD and aMCI, also shedding light on the mechanisms potentially contributing to the onset of neurodegenerative disorders.
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Affiliation(s)
- Pablo Maturana-Quijada
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain
| | - Pamela Chavarría-Elizondo
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain
| | - Inés Del Cerro
- Department of Psychology, Medical School, Catholic University of Murcia, Murcia, Spain
| | - Ignacio Martínez-Zalacaín
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Radiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain
| | - Asier Juaneda-Seguí
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain
| | - Andrés Guinea-Izquierdo
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain
| | - Jordi Gascón-Bayarri
- Dementia Diagnostic and Treatment Unit, Department of Neurology, Bellvitge University Hospital, Barcelona, Spain
| | - Ramón Reñé
- Dementia Diagnostic and Treatment Unit, Department of Neurology, Bellvitge University Hospital, Barcelona, Spain
| | - Mikel Urretavizcaya
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain
| | - José M Menchón
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, Bellvitge Campus, University of Barcelona, Barcelona, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain
| | - Isidre Ferrer
- Department of Pathology and Experimental Therapeutics, Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Bellvitge Biomedical Research Institute-IDIBELL, Department of Pathologic Anatomy, Bellvitge University Hospital, Barcelona, Spain; Network Center for Biomedical Research on Neurodegenerative Diseases (CIBERNED), Barcelona, Spain
| | - Virginia Soria
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain; Department of Mental Health, Parc Taulí Hospital Universitari, Sabadell, Barcelona, Spain
| | - Carles Soriano-Mas
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain; Network Center for Biomedical Research on Mental Health (CIBERSAM), Carlos III Health Institute (ISCIII), Barcelona, Spain; Department of Social Psychology and Quantitative Psychology, Institute of Neurosciences, University of Barcelona, Barcelona, Spain.
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Papp KV, Jutten RJ, Soberanes D, Weizenbaum E, Hsieh S, Molinare C, Buckley R, Betensky RA, Marshall GA, Johnson KA, Rentz DM, Sperling R, Amariglio RE. Early Detection of Amyloid-Related Changes in Memory among Cognitively Unimpaired Older Adults with Daily Digital Testing. Ann Neurol 2024; 95:507-517. [PMID: 37991080 PMCID: PMC10922126 DOI: 10.1002/ana.26833] [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: 07/18/2023] [Revised: 09/28/2023] [Accepted: 10/23/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVE This study was undertaken to determine whether assessing learning over days reveals Alzheimer disease (AD) biomarker-related declines in memory consolidation that are otherwise undetectable with single time point assessments. METHODS Thirty-six (21.9%) cognitively unimpaired older adults (aged 60-91 years) were classified with elevated β-amyloid (Aβ+) and 128 (78%) were Aβ- using positron emission tomography with 11C Pittsburgh compound B. Participants completed the multiday Boston Remote Assessment for Neurocognitive Health (BRANCH) for 12 min/day on personal devices (ie, smartphones, laptops), which captures the trajectory of daily learning of the same content on 3 repeated tests (Digit Signs, Groceries-Prices, Face-Name). Learning is computed as a composite of accuracy across all 3 measures. Participants also completed standard in-clinic cognitive tests as part of the Preclinical Alzheimer's Cognitive Composite (PACC-5), with 123 participants undergoing PACC-5 follow-up after 1.07 (standard deviation = 0.25) years. RESULTS At the cross-section, there were no statistically significant differences in performance between Aβ+/- participants on any standard in-clinic cognitive tests (eg, PACC-5) or on day 1 of multiday BRANCH. Aβ+ participants exhibited diminished 7-day learning curves on multiday BRANCH after 4 days of testing relative to Aβ- participants (Cohen d = 0.49, 95% confidence interval = 0.10-0.87). Diminished learning curves were associated with greater annual PACC-5 decline (r = 0.54, p < 0.001). INTERPRETATION Very early Aβ-related memory declines can be revealed by assessing learning over days, suggesting that failures in memory consolidation predate other conventional amnestic deficits in AD. Repeated digital memory assessments, increasingly feasible and uniquely able to assess memory consolidation over short time periods, have the potential to be transformative for detecting the earliest cognitive changes in preclinical AD. ANN NEUROL 2024;95:507-517.
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Affiliation(s)
- Kathryn V. Papp
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Roos J. Jutten
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Daniel Soberanes
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Emma Weizenbaum
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129
| | - Stephanie Hsieh
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Cassidy Molinare
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Rachel Buckley
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Rebecca A. Betensky
- Department of Biostatistics, New York University School of Global Public Health, New York, NY, 10003
| | - Gad A. Marshall
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Keith A Johnson
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
- Department of Radiology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Dorene M. Rentz
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Reisa Sperling
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
| | - Rebecca E. Amariglio
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Department of Neurology, Massachusetts General Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
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Keegan AP, Savage K, Bousman CA, Nolidin K, Cribb L, Pipingas A, Stough C. Interleukin 10 (IL10) promoter region polymorphism is associated with IL10 serum concentrations and processing speed in healthy community-dwelling older adults. Behav Brain Res 2024; 458:114756. [PMID: 37951418 DOI: 10.1016/j.bbr.2023.114756] [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: 10/17/2023] [Revised: 11/07/2023] [Accepted: 11/08/2023] [Indexed: 11/14/2023]
Abstract
Inflammation is repressed by interleukin 10 (IL10), a potent anti-inflammatory cytokine, and unchecked inflammation can have detrimental effects on cognition. In healthy older adults enrolled in the Australian Research Council Longevity Intervention (ARCLI) cohort we explored whether a known functional single nucleotide polymorphism (SNP) in the promoter region of IL10, -1082 G/A (rs1800896), was associated with reaction times on computerized cognitive testing that included elements of processing speed (i.e., reaction time). Participants were aged 60-75 years (240 females, 158 males), free of dementia and psychiatric disorders, and provide a blood sample. Processing speed was measured using the Swinburne University Computerized Cognitive Assessment Battery (SUCCAB), which includes measures of reaction time (in milliseconds, ms) on six tasks. Blood-derived DNA was genotyped for the IL10 rs1800896 SNP and presence of the APOE E4 allele. General linear models for each SUCCAB subtest were fitted, with age, sex, education (years), APOE E4 carrier status, and IL10 genotype as independent variables. Carriers of the IL10 AA genotype had significantly slower reaction times on multiple tests compared to carriers of the minor allele (AG, GG) and lower IL10 serum levels. Although IL10 SNPs have not been detected in Alzheimer's disease genome-wide associated studies, these results support further exploration of IL10 mechanisms as a possible resilience factor.
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Affiliation(s)
| | - Karen Savage
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Chad A Bousman
- Department of Medical Genetics, Psychiatry, Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Karen Nolidin
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Lachlan Cribb
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Pipingas
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Con Stough
- School of Health Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
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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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9
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Walkiewicz G, Ronisz A, Van Ginderdeuren R, Lemmens S, Bouwman FH, Hoozemans JJM, Morrema THJ, Rozemuller AJ, Hart de Ruyter FJ, De Groef L, Stalmans I, Thal DR. Primary retinal tauopathy: A tauopathy with a distinct molecular pattern. Alzheimers Dement 2024; 20:330-340. [PMID: 37615275 PMCID: PMC10916964 DOI: 10.1002/alz.13424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 06/20/2023] [Accepted: 07/13/2023] [Indexed: 08/25/2023]
Abstract
BACKGROUND Phosphorylated tau (p-tau) accumulation, a hallmark of Alzheimer's disease (AD), can also be found in the retina. However, it is uncertain whether it is linked to AD or another tauopathy. METHODS Retinas from 164 individuals, with and without AD, were analyzed for p-tau accumulation and its relationship with age, dementia, and vision impairment. RESULTS Retinal p-tau pathology showed a consistent pattern with four stages and a molecular composition distinct from that of cerebral tauopathies. The stage of retinal p-tau pathology correlated with age (r = 0.176, P = 0.024) and was associated with AD (odds ratio [OR] 3.193; P = 0.001), and inflammation (OR = 2.605; P = 0.001). Vision impairment was associated with underlying eye diseases (β = 0.292; P = 0.001) and the stage of retinal p-tau pathology (β = 0.192; P = 0.030) in a linear regression model. CONCLUSIONS The results show the presence of a primary retinal tauopathy that is distinct from cerebral tauopathies.
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Affiliation(s)
- Grzegorz Walkiewicz
- Laboratory of NeuropathologyDepartment of Imaging and PathologyLeuven Brain InstituteKU LeuvenLeuvenBelgium
| | - Alicja Ronisz
- Laboratory of NeuropathologyDepartment of Imaging and PathologyLeuven Brain InstituteKU LeuvenLeuvenBelgium
| | - Rita Van Ginderdeuren
- Department of PathologyUZ LeuvenLeuvenBelgium
- Department of OphthalmologyUZ LeuvenLeuvenBelgium
| | | | | | | | - Tjado H. J. Morrema
- Amsterdam UMCDepartment of PathologyAmsterdam NeuroscienceAmsterdamthe Netherlands
| | | | - Frederique J. Hart de Ruyter
- Amsterdam UMCAlzheimer CenterNeurologyAmsterdamthe Netherlands
- Amsterdam UMCDepartment of PathologyAmsterdam NeuroscienceAmsterdamthe Netherlands
| | - Lies De Groef
- Cellular Communication and Neurodegeneration Research GroupDepartment of BiologyLeuven Brain InstituteKU LeuvenLeuvenBelgium
| | - Ingeborg Stalmans
- Department of OphthalmologyUZ LeuvenLeuvenBelgium
- Research Group OphthalmologyDepartment of NeuroscienceLeuven Brain InstituteKU LeuvenLeuvenBelgium
| | - Dietmar Rudolf Thal
- Laboratory of NeuropathologyDepartment of Imaging and PathologyLeuven Brain InstituteKU LeuvenLeuvenBelgium
- Department of PathologyUZ LeuvenLeuvenBelgium
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10
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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11
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Prokopiou PC, Engels-Domínguez N, Schultz AP, Sepulcre J, Koops EA, Papp KV, Marshall GA, Normandin MD, El Fakhri G, Rentz D, Sperling RA, Johnson KA, Jacobs HIL. Association of Novelty-Related Locus Coeruleus Function With Entorhinal Tau Deposition and Memory Decline in Preclinical Alzheimer Disease. Neurology 2023; 101:e1206-e1217. [PMID: 37491329 PMCID: PMC10516269 DOI: 10.1212/wnl.0000000000207646] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 05/31/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The predictable Braak staging scheme suggests that cortical tau progression may be related to synaptically connected neurons. Animal and human neuroimaging studies demonstrated that changes in neuronal activity contribute to tau spreading. Whether similar mechanisms explain tau progression from the locus coeruleus (LC), a tiny noradrenergic brainstem nucleus involved in novelty, learning, and memory and among the earliest regions to accumulate tau, has not yet been established. We aimed to investigate whether novelty-related LC activity was associated with the accumulation of cortical tau and its implications for cognitive decline. METHODS We combined functional MRI data of a novel vs repeated face-name learning paradigm, [18F]-FTP-PET, [11C]-PiB-PET, and longitudinal cognitive data from 92 well-characterized older individuals in the Harvard Aging Brain Study. We related novelty vs repetition LC activity to cortical tau deposition and to longitudinal decline in memory, executive function, and the Preclinical Alzheimer Disease Cognitive Composite (version 5; PACC5). Structural equation modeling was used to examine whether entorhinal cortical (EC) tau mediated the relationship between LC activity and cognitive decline and whether this depended on beta-amyloid deposition. RESULTS The participants' average age at baseline was 69.67 ± 10.14 years. Fifty-one participants were female. Ninety-one participants were cognitively normal (CDR global = 0), and one participant had mild cognitive impairment (CDR global = 0.5) at baseline. Lower novelty-related LC activity was specifically related to greater tau deposition in the medial-lateral temporal cortex and steeper memory decline. LC activity during novelty vs repetition was not related to executive dysfunction or decline on the PACC5. The relationship between LC activity and memory decline was partially mediated by EC tau, particularly in individuals with elevated beta-amyloid deposition. DISCUSSION Our results suggested that lower novelty-related LC activity is associated with the emergence of EC tau and that the downstream effects of this LC-EC pathway on memory decline also require the presence of elevated beta-amyloid. Longitudinal studies are required to investigate whether optimal LC activity has the potential to delay tau spread and memory decline, which may have implications for designing targeted interventions promoting resilience.
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Affiliation(s)
- Prokopis C Prokopiou
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Nina Engels-Domínguez
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Aaron P Schultz
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Jorge Sepulcre
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Elouise A Koops
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Kathryn V Papp
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Gad A Marshall
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Marc D Normandin
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Georges El Fakhri
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Dorene Rentz
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Reisa A Sperling
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Keith A Johnson
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Heidi I L Jacobs
- From the Gordon Center for Medical Imaging (P.C.P., N.E.-D., J.S., E.A.K., M.D.N., G.E.F., K.A.J., H.I.L.J.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston; Faculty of Health (N.E.-D., H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, The Netherlands; Department of Neurology (A.P.S., K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Massachusetts General Hospital, Harvard Medical School; The Athinoula A. Martinos Center for Biomedical Imaging (A.P.S.), Department of Radiology, Massachusetts General Hospital, Harvard Medical School; and Center for Alzheimer Research and Treatment (K.V.P., G.A.M., D.R., R.A.S., K.A.J.), Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
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12
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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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13
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Hammers DB, Kostadinova RV, Spencer RJ, Ikanga JN, Unverzagt FW, Risacher SL, Apostolova LG. Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:866-884. [PMID: 36074015 PMCID: PMC9992455 DOI: 10.1080/13825585.2022.2120957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/30/2022] [Indexed: 10/14/2022]
Abstract
Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.
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Affiliation(s)
- Dustin B. Hammers
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
| | | | - Robert J. Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA
- Michigan Medicine, Department of Psychiatry, Neuropsychology Section, Ann Arbor MI, USA
| | - Jean N. Ikanga
- Emory University, School of Medicine, Department of Rehabilitation Medicine, GA, USA
- University of Kinshasa, Department of Psychiatry, Democratic Republic of Congo (DRC)
| | | | - Shannon L. Risacher
- Indiana University School of Medicine, Department of Radiology, Indianapolis, IN, USA
| | - Liana G. Apostolova
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
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14
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruiz E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts M, Jacobs HIL, Pereira JB. Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions. eLife 2023; 12:RP87188. [PMID: 37650882 PMCID: PMC10471162 DOI: 10.7554/elife.87188] [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: 09/01/2023] Open
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg UniversityGoteborgSweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- University of Eastern FinlandKuopioFinland
| | - Per Svenningsson
- University of Eastern FinlandKuopioFinland
- Department of Clinical Neuroscience, Karolinska InstitutetStockholmSweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative Disease, UCL Institute of NeurologyLondonUnited Kingdom
- UK Dementia Research Institute at UCLLondonUnited Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water BayHong KongChina
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-MadisonMadisonUnited States
| | - Giovanni Volpe
- Department of Physics, Goteborg UniversityGoteborgSweden
| | - Matthew Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University MagdeburgMagdeburgGermany
- Center for Behavioral Brain Sciences, University of MagdeburgMagdeburgGermany
| | - Heidi IL Jacobs
- Maastricht UniversityMaastrichtNetherlands
- Massachusetts General HospitalBostonUnited States
| | - Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska InstitutetStockholmSweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund UniversityLundSweden
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15
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Gong HJ, Tang X, Chai YH, Qiao YS, Xu H, Patel I, Zhang JY, Zhou JB. Predicted lean body mass in relation to cognitive function in the older adults. Front Endocrinol (Lausanne) 2023; 14:1172233. [PMID: 37484948 PMCID: PMC10358760 DOI: 10.3389/fendo.2023.1172233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/16/2023] [Indexed: 07/25/2023] Open
Abstract
Background Previous findings about lean body mass (LBM) and cognitive function remain unclear. We aimed to examine this association by using data from the National Health and Nutrition Examination Survey (NHANES). Methods Using data from the NHANES 2011-2014, we conducted logistic regression models to investigate the relation between the predicted LBM and domain-specific cognitive function assessed by Digit Symbol Substitution Test (DSST), Consortium to Establish a Registry for Alzheimer's Disease Word Learning test (CERAD-WL) and Delayed Recall test (CERAD-DR), and Animal Fluency (AF) for information processing speed, memory, and executive function, respectively. Cognitive impairment was defined as the lowest quartile of each cognitive test in the total population. Sex-stratified analysis was further made. Results A total of 2955 participants aged 60 and above (mean [SD] age, 69.17[0.20] years; 1511 female [51.13%]) were included in the study. After being adjusted for social economic factors, anthropometric parameters, and diseases, we found a positive association between predicted LBM and information processing speed (Odds ratio of DSST impairment= 0.95, 95%CI= 0.91 to 0.99) regardless of body mass index and sex. Compared with patients in the first quartile of predicted LBM, those in the fourth quartile had an odds ratio of 0.355 (95% confidence interval 0.153-0.822) for DSST impairment. No significant relation in other cognitive tests and predicted LBM was found whether stratified by sex or not. Conclusion Our findings point to the association between predicted lean body mass and cognitive dysfunction in information processing speed, which could be used for early detection and prevention of deterioration of cognitive function among older adults.
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Affiliation(s)
- Hong-Jian Gong
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Xingyao Tang
- Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yin-He Chai
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yu-Shun Qiao
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Hui Xu
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ikramulhaq Patel
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jin-Yan Zhang
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jian-Bo Zhou
- Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
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16
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Veréb D, Mijalkov M, Canal-Garcia A, Chang YW, Gomez-Ruis E, Gerboles BZ, Kivipelto M, Svenningsson P, Zetterberg H, Volpe G, Betts MJ, Jacobs H, Pereira JB. Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.25.23286442. [PMID: 37333117 PMCID: PMC10274957 DOI: 10.1101/2023.02.25.23286442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
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Affiliation(s)
- Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Yu-Wei Chang
- Department of Physics, Goteborg University, Goteborg, Sweden
| | | | - Blanca Zufiria Gerboles
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- University of Eastern Finland, Kuopio, Finland
| | - Per Svenningsson
- University of Eastern Finland, Kuopio, Finland
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Mathew J. Betts
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany
| | - Heidi Jacobs
- Maastricht University, Maastricht, The Netherlands
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Joana B. Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
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17
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Dobyns L, Zhuang K, Baker SL, Mungas D, Jagust WJ, Harrison TM. An empirical measure of resilience explains individual differences in the effect of tau pathology on memory change in aging. NATURE AGING 2023; 3:229-237. [PMID: 37118122 PMCID: PMC10148952 DOI: 10.1038/s43587-022-00353-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/19/2022] [Indexed: 04/30/2023]
Abstract
Accurately measuring resilience to preclinical Alzheimer's disease (AD) pathology is essential to understanding an important source of variability in cognitive aging. In a cohort of cognitively normal older adults (n = 123, age 76.75 ± 6.15 yr), we built a multifactorial measure of resilience which moderated the effect of AD pathology on longitudinal cognitive change. Linear residuals-based measures of resilience, along with other proxy measures (education and vocabulary), were entered into a hierarchical partial least-squares path model defining a putative consolidated resilience latent factor (model goodness of fit = 0.77). In a set of validation analyses using linear mixed models predicting longitudinal cognitive change, there was a significant three-way interaction among consolidated resilience, tau and time on episodic memory change (P = 0.001) such that higher resilience blunted the effect of tau pathology on episodic memory decline. Interactions between consolidated resilience and amyloid pathology on non-memory cognition decline suggested that resilience moderates pathology-specific effects on different cognitive domains.
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Affiliation(s)
- Lindsey Dobyns
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Kailin Zhuang
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | | | - Dan Mungas
- Department of Neurology, University of California, Davis, Sacramento, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
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18
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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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19
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Butts AM, Machulda MM, Martin P, Przybelski SA, Duffy JR, Graff-Radford J, Knopman DS, Petersen RC, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Temporal Cortical Thickness and Cognitive Associations among Typical and Atypical Phenotypes of Alzheimer's Disease. J Alzheimers Dis Rep 2022; 6:479-491. [PMID: 36186727 PMCID: PMC9484150 DOI: 10.3233/adr-220010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 06/29/2022] [Indexed: 11/15/2022] Open
Abstract
Background The hippocampus and temporal lobe are atrophic in typical amnestic Alzheimer's disease (tAD) and are used as imaging biomarkers in treatment trials. However, a better understanding of how temporal structures differ across atypical AD phenotypes and relate to cognition is needed. Objective Our goal was to compare temporal lobe regions between tAD and two atypical AD phenotypes (logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA)), and assess cognitive associations. Methods We age and gender-matched 77 tAD participants to 50 LPA and 27 PCA participants, all of which were amyloid-positive. We used linear mixed-effects models to compare FreeSurfer-derived hippocampal volumes and cortical thickness of entorhinal, inferior and middle temporal, and fusiform gyri, and to assess relationships between imaging and memory, naming, and visuospatial function across and within AD phenotype. Results Hippocampal volume and entorhinal thickness were smaller bilaterally in tAD than LPA and PCA. PCA showed greater right inferior temporal and bilateral fusiform thinning and LPA showed greater left middle and inferior temporal and left fusiform thinning. Atypical AD phenotypes differed with greater right hemisphere thinning in PCA and greater left hemisphere thinning in LPA. Verbal and visual memory related most strongly to hippocampal volume; naming related to left temporal thickness; and visuospatial related to bilateral fusiform thickness. Fewer associations remained when examined within AD group. Conclusion Atypical AD phenotypes are associated with greater thinning of lateral temporal structures, with relative sparing of medial temporal lobe, compared to tAD. These findings may have implications for future clinical trials in AD.
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Affiliation(s)
- Alissa M. Butts
- Department of Neurology, Division of Neuropsychology, Medical College of Wisconsin, Milwaukee, WI, USA,External Research Collaborator, Mayo Clinic, Rochester, MN, USA
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Division of Neuropsychology, Mayo Clinic, Rochester, MN, USA
| | - Peter Martin
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Jennifer L. Whitwell
- Department of Radiology, Mayo Clinic, Rochester, MN, USA,Correspondence to: Jennifer L. Whitwell, PhD, Professor of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA. E-mail:
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20
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Petersen RC. Detecting Alzheimer Disease Clinically: How Early Can We Go? Neurology 2022; 98:607-608. [PMID: 35338082 DOI: 10.1212/wnl.0000000000200172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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