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Bachmann D, Saake A, Studer S, Buchmann A, Rauen K, Gruber E, Michels L, Nitsch RM, Hock C, Gietl A, Treyer V. Hypertension and cerebral blood flow in the development of Alzheimer's disease. Alzheimers Dement 2024. [PMID: 39254220 DOI: 10.1002/alz.14233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/11/2024]
Abstract
INTRODUCTION We investigated the interactive associations between amyloid and hypertension on the entorhinal cortex (EC) tau and atrophy and the role of cerebral blood flow (CBF) as a shared mechanism by which amyloid and hypertension contribute to EC tau and regional white matter hyperintensities (WMHs). METHODS We analyzed data from older adults without dementia participating in the Add-Tau study (NCT02958670, n = 138) or Alzheimer's Disease Neuroimaging Initiative (ADNI) (n = 523) who had available amyloid-positron emission tomography (PET), tau-PET, fluid-attenuated inversion recovery (FLAIR), and T1-weighted magnetic resonance imaging (MRI). A subsample in both cohorts had available arterial spin labeling (ASL) MRI (Add-Tau: n = 78; ADNI: n = 89). RESULTS The detrimental effects of hypertension on AD pathology and EC thickness were more pronounced in the Add-Tau cohort. Increased amyloid burden was associated with decreased occipital gray matter CBF in the ADNI cohort. In both cohorts, lower regional gray matter CBF was associated with higher EC tau and posterior WMH burden. DISCUSSION Reduced cerebral perfusion may be one common mechanism through which hypertension and amyloid are related to increased EC tau and WMH volume. HIGHLIGHTS Hypertension is associated with increased entorhinal cortex (EC) tau, particularly in the presence of amyloid. Decreased cortical cerebral blood flow (CBF) is associated with higher regional white matter hyperintensity volume. Increasing amyloid burden is associated with decreasing CBF in the occipital lobe. MTL CBF and amyloid are synergistically associated with EC tau.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Lars Michels
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, Zurich, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Neurimmune, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Neurimmune, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
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Wallace ML, Redline S, Oryshkewych N, Hoepel SJW, Luik AI, Stone KL, Kolko RP, Chung J, Leng Y, Robbins R, Zhang Y, Barnes LL, Lim AS, Yu L, Buysse DJ. Pioneering a multi-phase framework to harmonize self-reported sleep data across cohorts. Sleep 2024; 47:zsae115. [PMID: 38752786 PMCID: PMC11381567 DOI: 10.1093/sleep/zsae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/29/2024] [Indexed: 06/15/2024] Open
Abstract
STUDY OBJECTIVES Harmonizing and aggregating data across studies enables pooled analyses that support external validation and enhance replicability and generalizability. However, the multidimensional nature of sleep poses challenges for data harmonization and aggregation. Here we describe and implement our process for harmonizing self-reported sleep data. METHODS We established a multi-phase framework to harmonize self-reported sleep data: (1) compile items, (2) group items into domains, (3) harmonize items, and (4) evaluate harmonizability. We applied this process to produce a pooled multi-cohort sample of five US cohorts plus a separate yet fully harmonized sample from Rotterdam, Netherlands. Sleep and sociodemographic data are described and compared to demonstrate the utility of harmonization and aggregation. RESULTS We collected 190 unique self-reported sleep items and grouped them into 15 conceptual domains. Using these domains as guiderails, we developed 14 harmonized items measuring aspects of satisfaction, alertness/sleepiness, timing, efficiency, duration, insomnia, and sleep apnea. External raters determined that 13 of these 14 items had moderate-to-high harmonizability. Alertness/Sleepiness items had lower harmonizability, while continuous, quantitative items (e.g. timing, total sleep time, and efficiency) had higher harmonizability. Descriptive statistics identified features that are more consistent (e.g. wake-up time and duration) and more heterogeneous (e.g. time in bed and bedtime) across samples. CONCLUSIONS Our process can guide researchers and cohort stewards toward effective sleep harmonization and provide a foundation for further methodological development in this expanding field. Broader national and international initiatives promoting common data elements across cohorts are needed to enhance future harmonization and aggregation efforts.
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Affiliation(s)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | | | - Sanne J W Hoepel
- Department of Epidemiology, Erasmus MC University Medical Centre, Rotterdam, Netherlands
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC University Medical Centre, Rotterdam, Netherlands
- Trimbos Institute - The Netherlands Institute of Mental Health and Addiction, Utrecht, Netherlands
| | - Katie L Stone
- California Pacific Medical Center, San Francisco, CA, USA
| | - Rachel P Kolko
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joon Chung
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Yue Leng
- Department of Psychiatry and Behavioral Sciences, University of California at San Francisco, San Franciso, CA, USA
| | - Rebecca Robbins
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Ying Zhang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Lisa L Barnes
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Andrew S Lim
- Department of Neurology, University of Toronto, Toronto, ON, Canada
| | - Lan Yu
- Department of Medicine, University of Pittsburgh School, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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Arenaza‐Urquijo EM, Boyle R, Casaletto K, Anstey KJ, Vila‐Castelar C, Colverson A, Palpatzis E, Eissman JM, Kheng Siang Ng T, Raghavan S, Akinci M, Vonk JMJ, Machado LS, Zanwar PP, Shrestha HL, Wagner M, Tamburin S, Sohrabi HR, Loi S, Bartrés‐Faz D, Dubal DB, Vemuri P, Okonkwo O, Hohman TJ, Ewers M, Buckley RF. Sex and gender differences in cognitive resilience to aging and Alzheimer's disease. Alzheimers Dement 2024; 20:5695-5719. [PMID: 38967222 PMCID: PMC11350140 DOI: 10.1002/alz.13844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 03/08/2024] [Accepted: 03/21/2024] [Indexed: 07/06/2024]
Abstract
Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.
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Affiliation(s)
- Eider M. Arenaza‐Urquijo
- Environment and Health Over the Life Course Programme, Climate, Air Pollution, Nature and Urban Health ProgrammeBarcelona Institute for Global Health (ISGlobal)BarcelonaSpain
- University of Pompeu FabraBarcelonaBarcelonaSpain
| | - Rory Boyle
- Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Kaitlin Casaletto
- Department of NeurologyMemory and Aging CenterUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Kaarin J. Anstey
- University of New South Wales Ageing Futures InstituteSydneyNew South WalesAustralia
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of Psychology, University of New South WalesSidneyNew South WalesAustralia
| | | | - Aaron Colverson
- University of Florida Center for Arts in Medicine Interdisciplinary Research LabUniversity of Florida, Center of Arts in MedicineGainesvilleFloridaUSA
| | - Eleni Palpatzis
- Environment and Health Over the Life Course Programme, Climate, Air Pollution, Nature and Urban Health ProgrammeBarcelona Institute for Global Health (ISGlobal)BarcelonaSpain
- University of Pompeu FabraBarcelonaBarcelonaSpain
| | - Jaclyn M. Eissman
- Vanderbilt Memory and Alzheimer's Center, Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Ted Kheng Siang Ng
- Rush Institute for Healthy Aging and Department of Internal MedicineRush University Medical CenterChicagoIllinoisUSA
| | | | - Muge Akinci
- Environment and Health Over the Life Course Programme, Climate, Air Pollution, Nature and Urban Health ProgrammeBarcelona Institute for Global Health (ISGlobal)BarcelonaSpain
- University of Pompeu FabraBarcelonaBarcelonaSpain
| | - Jet M. J. Vonk
- Department of NeurologyMemory and Aging CenterUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Luiza S. Machado
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, FarroupilhaPorto AlegreBrazil
| | - Preeti P. Zanwar
- Jefferson College of Population Health, Thomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
- The Network on Life Course and Health Dynamics and Disparities, University of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Maude Wagner
- Rush Alzheimer's Disease Center, Rush University Medical CenterChicagoIllinoisUSA
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement SciencesUniversity of VeronaVeronaItaly
| | - Hamid R. Sohrabi
- Centre for Healthy AgeingHealth Future InstituteMurdoch UniversityMurdochWestern AustraliaAustralia
- School of Psychology, Murdoch UniversityMurdochWestern AustraliaAustralia
| | - Samantha Loi
- Neuropsychiatry Centre, Royal Melbourne HospitalParkvilleVictoriaAustralia
- Department of PsychiatryUniversity of MelbourneParkvilleVictoriaAustralia
| | - David Bartrés‐Faz
- Department of MedicineFaculty of Medicine and Health Sciences & Institut de NeurociènciesUniversity of BarcelonaBarcelonaBarcelonaSpain
- Institut d'Investigacions Biomèdiques (IDIBAPS)BarcelonaBarcelonaSpain
- Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la Universitat Autónoma de BarcelonaBadalonaBarcelonaSpain
| | - Dena B. Dubal
- Department of Neurology and Weill Institute of NeurosciencesUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Biomedical and Neurosciences Graduate ProgramsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | | | - Ozioma Okonkwo
- Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's Center, Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Michael Ewers
- Institute for Stroke and Dementia ResearchKlinikum der Universität MünchenLudwig Maximilians Universität (LMU)MunichGermany
- German Center for Neurodegenerative Diseases (DZNE, Munich)MunichGermany
| | - Rachel F. Buckley
- Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
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Younes K, Smith V, Johns E, Carlson ML, Winer J, He Z, Henderson VW, Greicius MD, Young CB, Mormino EC. Temporal tau asymmetry spectrum influences divergent behavior and language patterns in Alzheimer's disease. Brain Behav Immun 2024; 119:807-817. [PMID: 38710339 DOI: 10.1016/j.bbi.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 03/31/2024] [Accepted: 05/02/2024] [Indexed: 05/08/2024] Open
Abstract
Understanding the psychiatric symptoms of Alzheimer s disease (AD) is crucial for advancing precision medicine and therapeutic strategies. The relationship between AD behavioral symptoms and asymmetry in spatial tau PET patterns is not well-known. Braak tau progression implicates the temporal lobes early. However, the clinical and pathological implications of temporal tau laterality remain unexplored. This cross-sectional study investigated the correlation between temporal tau PET asymmetry and behavior assessed using the neuropsychiatric inventory and composite scores for memory, executive function, and language, using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In the entire cohort, continuous right and left temporal tau contributions to behavior and cognition were evaluated, controlling for age, sex, education, and tau burden on the contralateral side. Additionally, a temporal tau laterality index was calculated to define "asymmetry-extreme" groups (individuals with laterality indices greater than two standard deviations from the mean). 695 individuals (age = 73.9 ± 7.6 years, 372 (53.5 %) females) were included, comprising 281 (40%) cognitively unimpaired (CU) amyloid negative, 185 (27%) CU amyloid positive, and 229 (33%) impaired (CI) amyloid positive participants. In the full cohort analysis, right temporal tau was associated with worse behavior (B = 8.14, p-value = 0.007), and left temporal tau was associated with worse language (B = 1.4, p-value < 0.001). Categorization into asymmetry-extreme groups revealed 20 right- and 27 left-asymmetric participants. Within these extreme groups, there was additional heterogeneity along the anterior-posterior dimension. Asymmetrical tau burden is associated with distinct behavioral and cognitive profiles. Wide multi-cultural implementation of social cognition measures is needed to understand right-sided asymmetry in AD.
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Affiliation(s)
- Kyan Younes
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA.
| | - Viktorija Smith
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Emily Johns
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Mackenzie L Carlson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Joseph Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA; Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Victor W Henderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA; Department of Epidemiology and Population Health, Stanford University, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, USA; Wu Tsai Neuroscience Institute, Stanford, CA, USA
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5
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Mohanty R, Ferreira D, Westman E. Multi-pathological contributions toward atrophy patterns in the Alzheimer's disease continuum. Front Neurosci 2024; 18:1355695. [PMID: 38655107 PMCID: PMC11036869 DOI: 10.3389/fnins.2024.1355695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/07/2024] [Indexed: 04/26/2024] Open
Abstract
Introduction Heterogeneity in downstream atrophy in Alzheimer's disease (AD) is predominantly investigated in relation to pathological hallmarks (Aβ, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aβ, tau, and cerebrovascular burden. Methods We included 149 Aβ + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aβ- cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aβ (global Aβ PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition. Results (a) In the AD continuum, typicality (r = -0.31, p < 0.001) and severity (r = -0.37, p < 0.001) were associated with tau burden after controlling for Aβ, cerebrovascular burden and age. Findings imply greater tau pathology in limbic predominant atrophy and diffuse atrophy. (b) Typicality was associated with memory (r = 0.49, p < 0.001) and language scores (r = 0.19, p = 0.02). Severity was associated with memory (r = 0.26, p < 0.001), executive function (r = 0.24, p = 0.003) and language scores (r = 0.29, p < 0.001). Findings imply better cognitive performance in hippocampal sparing and minimal atrophy patterns. Beyond typicality/severity, tau burden but not Aβ and cerebrovascular burden explained cognition. Conclusion In the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aβ and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aβ or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.
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Affiliation(s)
- Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas, Spain
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
- Department of Neuroimaging, Center for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom
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Ferrari-Souza JP, Brum WS, Hauschild LA, Da Ros LU, Ferreira PCL, Bellaver B, Leffa DT, Bieger A, Tissot C, Lussier FZ, De Bastiani MA, Povala G, Benedet AL, Therriault J, Wang YT, Ashton NJ, Zetterberg H, Blennow K, Martins SO, Souza DO, Rosa-Neto P, Karikari TK, Pascoal TA, Zimmer ER. Vascular risk burden is a key player in the early progression of Alzheimer's disease. Neurobiol Aging 2024; 136:88-98. [PMID: 38335912 DOI: 10.1016/j.neurobiolaging.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 12/21/2023] [Accepted: 12/29/2023] [Indexed: 02/12/2024]
Abstract
Understanding whether vascular risk factors (VRFs) synergistically potentiate Alzheimer's disease (AD) progression is important in the context of emerging treatments for preclinical AD. In a group of 503 cognitively unimpaired individuals, we tested whether VRF burden interacts with AD pathophysiology to accelerate neurodegeneration and cognitive decline. Baseline VRF burden was calculated considering medical data and AD pathophysiology was assessed based on cerebrospinal fluid (CSF) amyloid-β1-42 (Aβ1-42) and tau phosphorylated at threonine 181 (p-tau181). Neurodegeneration was assessed with plasma neurofilament light (NfL) and global cognition with the modified version of the Preclinical Alzheimer's Cognitive Composite. The mean (SD) age of participants was 72.9 (6.1) years, and 220 (43.7%) were men. Linear mixed-effects models revealed that an elevated VRF burden synergistically interacted with AD pathophysiology to drive longitudinal plasma NfL increase and cognitive decline. Additionally, VRF burden was not associated with CSF Aβ1-42 or p-tau181 changes over time. Our results suggest that VRF burden and AD pathophysiology are independent processes; however, they synergistically lead to neurodegeneration and cognitive deterioration. In preclinical stages, the combination of therapies targeting VRFs and AD pathophysiology might potentiate treatment outcomes.
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Affiliation(s)
- João Pedro Ferrari-Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wagner S Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Lucas A Hauschild
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Lucas U Da Ros
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Pâmela C L Ferreira
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bruna Bellaver
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Douglas T Leffa
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrei Bieger
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Cécile Tissot
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Firoza Z Lussier
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Marco Antônio De Bastiani
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Guilherme Povala
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China; UW Department of Medicine, School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Sheila O Martins
- Department of Neurology, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Diogo O Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
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St-Onge F, Chapleau M, Breitner JCS, Villeneuve S, Pichet Binette A. Tau accumulation and its spatial progression across the Alzheimer's disease spectrum. Brain Commun 2024; 6:fcae031. [PMID: 38410618 PMCID: PMC10896475 DOI: 10.1093/braincomms/fcae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/30/2023] [Accepted: 02/05/2024] [Indexed: 02/28/2024] Open
Abstract
The accumulation of tau abnormality in sporadic Alzheimer's disease is believed typically to follow neuropathologically defined Braak staging. Recent in-vivo PET evidence challenges this belief, however, as accumulation patterns for tau appear heterogeneous among individuals with varying clinical expressions of Alzheimer's disease. We, therefore, sought a better understanding of the spatial distribution of tau in the preclinical and clinical phases of sporadic Alzheimer's disease and its association with cognitive decline. Longitudinal tau-PET data (1370 scans) from 832 participants (463 cognitively unimpaired, 277 with mild cognitive impairment and 92 with Alzheimer's disease dementia) were obtained from the Alzheimer's Disease Neuroimaging Initiative. Among these, we defined thresholds of abnormal tau deposition in 70 brain regions from the Desikan atlas, and for each group of regions characteristic of Braak staging. We summed each scan's number of regions with abnormal tau deposition to form a spatial extent index. We then examined patterns of tau pathology cross-sectionally and longitudinally and assessed their heterogeneity. Finally, we compared our spatial extent index of tau uptake with a temporal meta-region of interest-a commonly used proxy of tau burden-assessing their association with cognitive scores and clinical progression. More than 80% of amyloid-beta positive participants across diagnostic groups followed typical Braak staging, both cross-sectionally and longitudinally. Within each Braak stage, however, the pattern of abnormality demonstrated significant heterogeneity such that the overlap of abnormal regions across participants averaged less than 50%, particularly in persons with mild cognitive impairment. Accumulation of tau progressed more rapidly among cognitively unimpaired and participants with mild cognitive impairment (1.2 newly abnormal regions per year) compared to participants with Alzheimer's disease dementia (less than 1 newly abnormal region per year). Comparing the association of tau pathology and cognitive performance our spatial extent index was superior to the temporal meta-region of interest for identifying associations with memory in cognitively unimpaired individuals and explained more variance for measures of executive function in patients with mild cognitive impairments and Alzheimer's disease dementia. Thus, while participants broadly followed Braak stages, significant individual regional heterogeneity of tau binding was observed at each clinical stage. Progression of the spatial extent of tau pathology appears to be fastest in cognitively unimpaired and persons with mild cognitive impairment. Exploring the spatial distribution of tau deposits throughout the entire brain may uncover further pathological variations and their correlation with cognitive impairments.
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Affiliation(s)
- Frédéric St-Onge
- Integrated Program in Neuroscience, Faculty of Medicine, McGill University, Montreal, QC H3A 2B4, Canada
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
| | - Marianne Chapleau
- Faculty of Medicine, University of California San Francisco, San Francisco, CA 94143, USA
| | - John C S Breitner
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC H3A 1Y2, Canada
| | - Sylvia Villeneuve
- Research Center of the Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC H3A 1Y2, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC H3A 2B4, Canada
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Malmö 205 02, Sweden
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Eissman JM, Archer DB, Mukherjee S, Lee ML, Choi S, Scollard P, Trittschuh EH, Mez JB, Bush WS, Kunkle BW, Naj AC, Gifford KA, Cuccaro ML, Cruchaga C, Pericak‐Vance MA, Farrer LA, Wang L, Schellenberg GD, Mayeux RP, Haines JL, Jefferson AL, Kukull WA, Keene CD, Saykin AJ, Thompson PM, Martin ER, Bennett DA, Barnes LL, Schneider JA, Crane PK, Hohman TJ, Dumitrescu L. Sex-specific genetic architecture of late-life memory performance. Alzheimers Dement 2024; 20:1250-1267. [PMID: 37984853 PMCID: PMC10917043 DOI: 10.1002/alz.13507] [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: 04/04/2023] [Revised: 08/08/2023] [Accepted: 09/07/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND Women demonstrate a memory advantage when cognitively healthy yet lose this advantage to men in Alzheimer's disease. However, the genetic underpinnings of this sex difference in memory performance remain unclear. METHODS We conducted the largest sex-aware genetic study on late-life memory to date (Nmales = 11,942; Nfemales = 15,641). Leveraging harmonized memory composite scores from four cohorts of cognitive aging and AD, we performed sex-stratified and sex-interaction genome-wide association studies in 24,216 non-Hispanic White and 3367 non-Hispanic Black participants. RESULTS We identified three sex-specific loci (rs67099044-CBLN2, rs719070-SCHIP1/IQCJ-SCHIP), including an X-chromosome locus (rs5935633-EGL6/TCEANC/OFD1), that associated with memory. Additionally, we identified heparan sulfate signaling as a sex-specific pathway and found sex-specific genetic correlations between memory and cardiovascular, immune, and education traits. DISCUSSION This study showed memory is highly and comparably heritable across sexes, as well as highlighted novel sex-specific genes, pathways, and genetic correlations that related to late-life memory. HIGHLIGHTS Demonstrated the heritable component of late-life memory is similar across sexes. Identified two genetic loci with a sex-interaction with baseline memory. Identified an X-chromosome locus associated with memory decline in females. Highlighted sex-specific candidate genes and pathways associated with memory. Revealed sex-specific shared genetic architecture between memory and complex traits.
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9
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Nir TM, Villalón-Reina JE, Salminen LE, Haddad E, Zheng H, Thomopoulos SI, Jack CR, Weiner MW, Thompson PM, Jahanshad N. Cortical microstructural associations with CSF amyloid and pTau. Mol Psychiatry 2024; 29:257-268. [PMID: 38092890 PMCID: PMC11116103 DOI: 10.1038/s41380-023-02321-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 12/26/2023]
Abstract
Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.
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Affiliation(s)
- Talia M Nir
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Julio E Villalón-Reina
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Hong Zheng
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Michael W Weiner
- Department of Radiology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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10
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Archer DB, Eissman JM, Mukherjee S, Lee ML, Choi S, Scollard P, Trittschuh EH, Mez JB, Bush WS, Kunkle BW, Naj AC, Gifford KA, Cuccaro ML, Pericak‐Vance MA, Farrer LA, Wang L, Schellenberg GD, Mayeux RP, Haines JL, Jefferson AL, Kukull WA, Keene CD, Saykin AJ, Thompson PM, Martin ER, Bennett DA, Barnes LL, Schneider JA, Crane PK, Dumitrescu L, Hohman TJ. Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease. Alzheimers Dement 2024; 20:1268-1283. [PMID: 37985223 PMCID: PMC10896586 DOI: 10.1002/alz.13508] [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: 06/19/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 11/22/2023]
Abstract
INTRODUCTION Although large-scale genome-wide association studies (GWAS) have been conducted on AD, few have been conducted on continuous measures of memory performance and memory decline. METHODS We conducted a cross-ancestry GWAS on memory performance (in 27,633 participants) and memory decline (in 22,365 participants; 129,201 observations) by leveraging harmonized cognitive data from four aging cohorts. RESULTS We found high heritability for two ancestry backgrounds. Further, we found a novel ancestry locus for memory decline on chromosome 4 (rs6848524) and three loci in the non-Hispanic Black ancestry group for memory performance on chromosomes 2 (rs111471504), 7 (rs4142249), and 15 (rs74381744). In our gene-level analysis, we found novel genes for memory decline on chromosomes 1 (SLC25A44), 11 (BSX), and 15 (DPP8). Memory performance and memory decline shared genetic architecture with AD-related traits, neuropsychiatric traits, and autoimmune traits. DISCUSSION We discovered several novel loci, genes, and genetic correlations associated with late-life memory performance and decline. HIGHLIGHTS Late-life memory has high heritability that is similar across ancestries. We discovered four novel variants associated with late-life memory. We identified four novel genes associated with late-life memory. Late-life memory shares genetic architecture with psychiatric/autoimmune traits.
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11
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Telpoukhovskaia MA, Murdy TJ, Marola OJ, Charland K, MacLean M, Luquez T, Lish AM, Neuner S, Dunn A, Onos KD, Wiley J, Archer D, Huentelman MJ, Arnold M, Menon V, Goate A, Van Eldik LJ, Territo PR, Howell GR, Carter GW, O'Connell KMS, Kaczorowski CC. New directions for Alzheimer's disease research from the Jackson Laboratory Center for Alzheimer's and Dementia Research 2022 workshop. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12458. [PMID: 38469553 PMCID: PMC10925728 DOI: 10.1002/trc2.12458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 03/13/2024]
Abstract
INTRODUCTION In September 2022, The Jackson Laboratory Center for Alzheimer's and Dementia Research (JAX CADR) hosted a workshop with leading researchers in the Alzheimer's disease and related dementias (ADRD) field. METHODS During the workshop, the participants brainstormed new directions to overcome current barriers to providing patients with effective ADRD therapeutics. The participants outlined specific areas of focus. Following the workshop, each group used standard literature search methods to provide background for each topic. RESULTS The team of invited experts identified four key areas that can be collectively addressed to make a significant impact in the field: (1) Prioritize the diversification of disease targets, (2) enhance factors promoting resilience, (3) de-risk clinical pipeline, and (4) centralize data management. DISCUSSION In this report, we review these four objectives and propose innovations to expedite ADRD therapeutic pipelines.
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Affiliation(s)
| | - Thomas J. Murdy
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Kevin Charland
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Michael MacLean
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Tain Luquez
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alexandra M. Lish
- Ann Romney Center for Neurologic DiseasesDepartment of NeurologyBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Sarah Neuner
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Amy Dunn
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Kristen D. Onos
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Derek Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Matthew J. Huentelman
- Neurogenomics DivisionTranslational Genomics Research Institute (TGen)PhoenixArizonaUSA
| | - Matthias Arnold
- Institute of Computational BiologyHelmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - Vilas Menon
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alison Goate
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | | | - Paul R. Territo
- Department of MedicineDivision of Clinical PharmacologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neuroscience Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gareth R. Howell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Gregory W. Carter
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Kristen M. S. O'Connell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Catherine C. Kaczorowski
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Department of NeurologyUniversity of MichiganAnn ArborMichiganUSA
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Ryoo HG, Choi H, Shi K, Rominger A, Lee DY, Lee DS. Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters. Eur J Nucl Med Mol Imaging 2024; 51:443-454. [PMID: 37735259 DOI: 10.1007/s00259-023-06440-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023]
Abstract
PURPOSE Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to extract representations of unique brain metabolism patterns different from disease progression to identify objective subtypes of AD. METHODS A total of 3620 FDG brain PET images with AD, mild cognitive impairment (MCI), and cognitively normal (CN) were obtained from the ADNI database from 1607 participants at enrollment and follow-up visits. A conditional variational autoencoder model was trained on FDG brain PET images of AD patients with the corresponding condition of AD severity score. The k-means algorithm was applied to generate clusters from the encoded representations. The trained deep learning-based cluster model was also transferred to FDG PET of MCI patients and predicted the prognosis of subtypes for conversion from MCI to AD. Spatial metabolism patterns, clinical and biological characteristics, and conversion rate from MCI to AD were compared across the subtypes. RESULTS Four distinct subtypes of spatial metabolism patterns in AD with different brain pathologies and clinical profiles were identified: (i) angular, (ii) occipital, (iii) orbitofrontal, and (iv) minimal hypometabolic patterns. The deep learning model was also successfully transferred for subtyping MCI, and significant differences in frequency (P < 0.001) and risk of conversion (log-rank P < 0.0001) from MCI to AD were observed across the subtypes, highest in S2 (35.7%) followed by S1 (23.4%). CONCLUSION We identified distinct subtypes of AD with different clinicopathologic features. The deep learning-based approach to distinguish AD subtypes on FDG PET could have implications for predicting individual outcomes and provide a clue to understanding the heterogeneous pathophysiology of AD.
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Affiliation(s)
- Hyun Gee Ryoo
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine or College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010, Bern, Switzerland
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010, Bern, Switzerland
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine or College of Pharmacy, Seoul National University, Seoul, Republic of Korea
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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Younes K, Smith V, Johns E, Carlson ML, Winer J, He Z, Henderson VW, Greicius MD, Young CB, Mormino EC. Temporal tau asymmetry spectrum influences divergent behavior and language patterns in Alzheimer`s disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.10.23296836. [PMID: 37986964 PMCID: PMC10659470 DOI: 10.1101/2023.11.10.23296836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Understanding psychiatric symptoms in Alzheimer`s disease (AD) is crucial for advancing precision medicine and therapeutic strategies. The relationship between AD behavioral symptoms and asymmetry in spatial tau PET patterns is unknown. Braak tau progression implicates the temporal lobes early. However, the clinical and pathological implications of temporal tau laterality remain unexplored. This cross-sectional study investigated the correlation between temporal tau PET asymmetry and behavior assessed using the neuropsychiatric inventory, and composite scores for memory, executive function, and language; using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. In the entire cohort, continuous right and left temporal tau contributions to behavior and cognition were evaluated controlling for age, sex, education, and tau burden on the contralateral side. Additionally, a temporal tau laterality index was calculated to define "asymmetry-extreme" groups (individuals with laterality indices greater than two standard deviations from the mean). 858 individuals (age=73.9±7.7 years, 434(50%) females) were included, comprising 438 cognitively unimpaired (CU) (53.4%) and 420 impaired (CI) participants (48.9%). In the full cohort analysis, right temporal tau was associated with worse behavior (B(SE)=7.19 (2.9), p-value=0.01) and left temporal tau was associated with worse language (B(SE)=1.4(0.2), p-value<0.0001). Categorization into asymmetry-extreme groups revealed 20 right- and 27 left-asymmetric participants. Within these extreme groups, four patterns of tau PET uptake were observed: anterior temporal, typical AD, typical AD with frontal involvement, and posterior. Asymmetrical tau burden is associated with distinct behavioral and cognitive profiles. Behavioral and socioemotional measures are needed to understand right-sided asymmetry in AD.
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Affiliation(s)
- Kyan Younes
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Viktorija Smith
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Emily Johns
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Mackenzie L. Carlson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Joseph Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
| | - Victor W. Henderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Department of Epidemiology and Population Health, Stanford University
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Christina B. Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine
- Wu Tsai Neuroscience Institute, Stanford, CA, USA
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Britton GB, Huang L, Villarreal AE, Levey A, Philippakis A, Hu C, Yang CC, Mushi D, Oviedo DC, Rangel G, Ho JS, Thompson L, Khemakhem M, Ross M, Carreira MB, Kim N, Joung P, Albastaki O, Kuo PC, Low S, Paddick S, Kuan Y, Au R. Digital phenotyping: An equal opportunity approach to reducing disparities in Alzheimer's disease and related dementia research. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12495. [PMID: 38034851 PMCID: PMC10687344 DOI: 10.1002/dad2.12495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 07/12/2023] [Accepted: 09/25/2023] [Indexed: 12/02/2023]
Abstract
A rapidly aging world population is fueling a concomitant increase in Alzheimer's disease (AD) and related dementias (ADRD). Scientific inquiry, however, has largely focused on White populations in Australia, the European Union, and North America. As such, there is an incomplete understanding of AD in other populations. In this perspective, we describe research efforts and challenges of cohort studies from three regions of the world: Central America, East Africa, and East Asia. These cohorts are engaging with the Davos Alzheimer's Collaborative (DAC), a global partnership that brings together cohorts from around the world to advance understanding of AD. Each cohort is poised to leverage the widespread use of mobile devices to integrate digital phenotyping into current methodologies and mitigate the lack of representativeness in AD research of racial and ethnic minorities across the globe. In addition to methods that these three cohorts are already using, DAC has developed a digital phenotyping protocol that can collect ADRD-related data remotely via smartphone and/or in clinic via a tablet to generate a common data elements digital dataset that can be harmonized with additional clinical and molecular data being collected at each cohort site and when combined across cohorts and made accessible can provide a global data resource that is more racially/ethnically represented of the world population.
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Affiliation(s)
- Gabrielle B. Britton
- Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP)Panamá CityPanama
- Universidad Santa María La Antigua, Vía Ricardo J. AlfaroPanamá CityPanama
| | - Li‐Kai Huang
- Taipei Medical University Shuang‐Ho HospitalTaipeiTaiwan
| | - Alcibiades E. Villarreal
- Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP)Panamá CityPanama
| | - Allan Levey
- Emory University School of MedicineAtlantaGeorgiaUSA
| | - Anthony Philippakis
- Broad Institute at Massachusetts Institute of Technology and Harvard UniversityCambridgeMassachusettsUSA
| | - Chaur‐Jong Hu
- Taipei Medical University Shuang‐Ho HospitalTaipeiTaiwan
| | | | - Declare Mushi
- Kilimanjaro Christian Medical University CollegeMoshiTanzania
| | - Diana C. Oviedo
- Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP)Panamá CityPanama
- Universidad Santa María La Antigua, Vía Ricardo J. AlfaroPanamá CityPanama
| | - Giselle Rangel
- Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP)Panamá CityPanama
| | - Jor Sam Ho
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
- Boston University School of Public HealthBostonMassachusettsUSA
| | - Louisa Thompson
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
- Alpert Medical School of Brown UniversityProvidenceRhode IslandUSA
| | | | - Makayla Ross
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
- Boston University School of Public HealthBostonMassachusettsUSA
| | - María B. Carreira
- Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP)Panamá CityPanama
| | - Nicole Kim
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
| | - Philip Joung
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
| | | | - Po Chih Kuo
- National Tsing Hua University, East DistrictHsinChuTaiwan
| | - Spencer Low
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
- Boston University School of Public HealthBostonMassachusettsUSA
- Boston University Chobanian and Avedisian School of MedicineBostonMassachusettsUSA
- Boston University Alzheimer's Disease CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | | | - Yi‐Chun Kuan
- Taipei Medical University Shuang‐Ho HospitalTaipeiTaiwan
| | - Rhoda Au
- Davos Alzheimer's CollaborativeWaynePennsylvaniaUSA
- Boston University School of Public HealthBostonMassachusettsUSA
- Boston University Chobanian and Avedisian School of MedicineBostonMassachusettsUSA
- Boston University Alzheimer's Disease CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyBoston University Chobanian & Avedisian School of Medicine, Boston University School of Public HealthFraminghamMassachusettsUSA
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15
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Gross AL, Li C, Briceño EM, Arce Rentería M, Jones RN, Langa KM, Manly JJ, Nichols E, Weir D, Wong R, Berkman L, Lee J, Kobayashi LC. Harmonisation of later-life cognitive function across national contexts: results from the Harmonized Cognitive Assessment Protocols. THE LANCET. HEALTHY LONGEVITY 2023; 4:e573-e583. [PMID: 37804847 PMCID: PMC10637129 DOI: 10.1016/s2666-7568(23)00170-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 10/09/2023] Open
Abstract
BACKGROUND The Harmonized Cognitive Assessment Protocol (HCAP) is an innovative instrument for cross-national comparisons of later-life cognitive function, yet its suitability across diverse populations is unknown. We aimed to harmonise general and domain-specific cognitive scores from HCAP studies across six countries, and evaluate reliability and criterion validity of the resulting harmonised scores. METHODS We statistically harmonised general and domain-specific cognitive function scores across publicly available HCAP partner studies in China, England, India, Mexico, South Africa, and the USA conducted between October, 2015 and January, 2020. Participants missing all cognitive test items in a given HCAP were excluded. We used an item banking approach that leveraged common cognitive test items across studies and tests that were unique to studies. We generated harmonised factor scores to represent a person's relative functioning on the latent factors of general cognitive function, memory, executive function, orientation, and language using confirmatory factor analysis. We evaluated the marginal reliability, or precision, of the factor scores using test information plots. Criterion validity of factor scores was assessed by regressing the scores on age, gender, and educational attainment in a multivariable analysis adjusted for these characteristics. FINDINGS We included 21 144 participants from the six HCAP studies of interest (11 480 women [54·3%] and 9664 [45·7%] men), with a median age of 69 years (IQR 64-76). Confirmatory factor analysis models of cognitive function in each country fit well: 31 (88·6%) of 35 models had adequate or good fit to the data (comparative fit index ≥0·90, root mean square error of approximation ≤0·08, and standardised root mean residual ≤0·08). Marginal reliability of the harmonised general cognitive function factor was high (>0·9) for 19 044 (90·1%) of 21 144 participant scores across the six countries. Marginal reliability of the harmonised factor was above 0·85 for 19 281 (91·2%) of 21 142 participant factor scores for memory, 7805 (41·0%) of 19 015 scores for executive function, 3446 (16·3%) of 21 103 scores for orientation, and 4329 (20·5%) of 21 113 scores for language. In each country, general cognitive function scores were lower with older age and higher with greater levels of educational attainment. INTERPRETATION We statistically harmonised cognitive function measures across six large population-based studies of cognitive ageing. These harmonised cognitive function scores empirically reflect comparable domains of cognitive function among older adults across the six countries, have high reliability, and are useful for population-based research. This work provides a foundation for international networks of researchers to make improved inferences and direct comparisons of cross-national associations of risk factors for cognitive outcomes in pooled analyses. FUNDING US National Institute on Aging.
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Affiliation(s)
- Alden L Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Center on Aging and Health, Johns Hopkins University, Baltimore, MD, USA.
| | - Chihua Li
- Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA; Survey Research Center, University of Michigan Institute for Social Research, Ann Arbor, MI, USA
| | - Emily M Briceño
- Department of Physical Medicine and Rehabilitation, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Miguel Arce Rentería
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Richard N Jones
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Kenneth M Langa
- Survey Research Center, University of Michigan Institute for Social Research, Ann Arbor, MI, USA; Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA; Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, USA
| | - Jennifer J Manly
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Emma Nichols
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Center on Aging and Health, Johns Hopkins University, Baltimore, MD, USA; Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - David Weir
- Survey Research Center, University of Michigan Institute for Social Research, Ann Arbor, MI, USA
| | - Rebeca Wong
- School of Public and Population Health, and Sealy Center on Aging, University of Texas Medical Branch, Galveston, TX, USA
| | - Lisa Berkman
- Harvard Center for Population and Development Studies and Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Cambridge, MA, USA
| | - Jinkook Lee
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA; Department of Economics, University of Southern California, Los Angeles, CA, USA
| | - Lindsay C Kobayashi
- Center for Social Epidemiology and Population Health, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA; Survey Research Center, University of Michigan Institute for Social Research, Ann Arbor, MI, USA
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Walters S, Contreras AG, Eissman JM, Mukherjee S, Lee ML, Choi SE, Scollard P, Trittschuh EH, Mez JB, Bush WS, Kunkle BW, Naj AC, Peterson A, Gifford KA, Cuccaro ML, Cruchaga C, Pericak-Vance MA, Farrer LA, Wang LS, Haines JL, Jefferson AL, Kukull WA, Keene CD, Saykin AJ, Thompson PM, Martin ER, Bennett DA, Barnes LL, Schneider JA, Crane PK, Hohman TJ, Dumitrescu L. Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults. JAMA Neurol 2023; 80:929-939. [PMID: 37459083 PMCID: PMC10352930 DOI: 10.1001/jamaneurol.2023.2169] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/15/2023] [Indexed: 07/20/2023]
Abstract
Importance Sex differences are established in associations between apolipoprotein E (APOE) ε4 and cognitive impairment in Alzheimer disease (AD). However, it is unclear whether sex-specific cognitive consequences of APOE are consistent across races and extend to the APOE ε2 allele. Objective To investigate whether sex and race modify APOE ε4 and ε2 associations with cognition. Design, Setting, and Participants This genetic association study included longitudinal cognitive data from 4 AD and cognitive aging cohorts. Participants were older than 60 years and self-identified as non-Hispanic White or non-Hispanic Black (hereafter, White and Black). Data were previously collected across multiple US locations from 1994 to 2018. Secondary analyses began December 2021 and ended September 2022. Main Outcomes and Measures Harmonized composite scores for memory, executive function, and language were generated using psychometric approaches. Linear regression assessed interactions between APOE ε4 or APOE ε2 and sex on baseline cognitive scores, while linear mixed-effect models assessed interactions on cognitive trajectories. The intersectional effect of race was modeled using an APOE × sex × race interaction term, assessing whether APOE × sex interactions differed by race. Models were adjusted for age at baseline and corrected for multiple comparisons. Results Of 32 427 participants who met inclusion criteria, there were 19 007 females (59%), 4453 Black individuals (14%), and 27 974 White individuals (86%); the mean (SD) age at baseline was 74 years (7.9). At baseline, 6048 individuals (19%) had AD, 4398 (14%) were APOE ε2 carriers, and 12 538 (38%) were APOE ε4 carriers. Participants missing APOE status were excluded (n = 9266). For APOE ε4, a robust sex interaction was observed on baseline memory (β = -0.071, SE = 0.014; P = 9.6 × 10-7), whereby the APOE ε4 negative effect was stronger in females compared with males and did not significantly differ among races. Contrastingly, despite the large sample size, no APOE ε2 × sex interactions on cognition were observed among all participants. When testing for intersectional effects of sex, APOE ε2, and race, an interaction was revealed on baseline executive function among individuals who were cognitively unimpaired (β = -0.165, SE = 0.066; P = .01), whereby the APOE ε2 protective effect was female-specific among White individuals but male-specific among Black individuals. Conclusions and Relevance In this study, while race did not modify sex differences in APOE ε4, the APOE ε2 protective effect could vary by race and sex. Although female sex enhanced ε4-associated risk, there was no comparable sex difference in ε2, suggesting biological pathways underlying ε4-associated risk are distinct from ε2 and likely intersect with age-related changes in sex biology.
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Affiliation(s)
- Skylar Walters
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alex G. Contreras
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jaclyn M. Eissman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Michael L. Lee
- Department of Medicine, University of Washington, Seattle
| | - Seo-Eun Choi
- Department of Medicine, University of Washington, Seattle
| | | | - Emily H. Trittschuh
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle
- Geriatric Research Education and Clinical Center (GRECC), VA Puget Sound Health Care System, Seattle, Washington
| | - Jesse B. Mez
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - William S. Bush
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Brian W. Kunkle
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Adam C. Naj
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Amalia Peterson
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Katherine A. Gifford
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, Missouri
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - Lindsay A. Farrer
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Jonathan L. Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Angela L. Jefferson
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Walter A. Kukull
- Department of Epidemiology, School of Public Health, University of Washington, Seattle
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Andrew J. Saykin
- Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Paul M. Thompson
- Keck School of Medicine, University of Southern California, Los Angeles
| | - Eden R. Martin
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Lisa L. Barnes
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Julie A. Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Logan Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
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Giorgio J, Tanna A, Malpetti M, White SR, Wang J, Baker S, Landau S, Tanaka T, Chen C, Rowe JB, O'Brien J, Fripp J, Breakspear M, Jagust W, Kourtzi Z. A robust harmonization approach for cognitive data from multiple aging and dementia cohorts. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12453. [PMID: 37502020 PMCID: PMC10369372 DOI: 10.1002/dad2.12453] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 05/19/2023] [Accepted: 05/23/2023] [Indexed: 07/29/2023]
Abstract
INTRODUCTION Although many cognitive measures have been developed to assess cognitive decline due to Alzheimer's disease (AD), there is little consensus on optimal measures, leading to varied assessments across research cohorts and clinical trials making it difficult to pool cognitive measures across studies. METHODS We used a two-stage approach to harmonize cognitive data across cohorts and derive a cross-cohort score of cognitive impairment due to AD. First, we pool and harmonize cognitive data from international cohorts of varying size and ethnic diversity. Next, we derived cognitive composites that leverage maximal data from the harmonized dataset. RESULTS We show that our cognitive composites are robust across cohorts and achieve greater or comparable sensitivity to AD-related cognitive decline compared to the Mini-Mental State Examination and Preclinical Alzheimer Cognitive Composite. Finally, we used an independent cohort validating both our harmonization approach and composite measures. DISCUSSION Our easy to implement and readily available pipeline offers an approach for researchers to harmonize their cognitive data with large publicly available cohorts, providing a simple way to pool data for the development or validation of findings related to cognitive decline due to AD.
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Affiliation(s)
- Joseph Giorgio
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
- School of Psychological SciencesCollege of Engineering, Science and the EnvironmentUniversity of NewcastleNewcastleNew South WalesAustralia
| | - Ankeet Tanna
- Department of PsychologyUniversity of CambridgeCambridgeUK
| | - Maura Malpetti
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Simon R. White
- Department of PsychiatryUniversity of CambridgeCambridgeUK
- MRC Biostatistics UnitUniversity of CambridgeshireCambridgeUK
| | - Jingshen Wang
- Division of BiostatisticsUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Suzanne Baker
- Molecular Biophysics & Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Susan Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Tomotaka Tanaka
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
| | - Christopher Chen
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
| | - John O'Brien
- Department of PsychiatryUniversity of CambridgeCambridgeUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
| | - Jurgen Fripp
- The Australian eHealth Research CentreCSIRO Health and BiosecurityBrisbaneQueenslandAustralia
| | - Michael Breakspear
- School of Psychological SciencesCollege of Engineering, Science and the EnvironmentUniversity of NewcastleNewcastleNew South WalesAustralia
| | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
- Molecular Biophysics & Integrated BioimagingLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Zoe Kourtzi
- Department of PsychologyUniversity of CambridgeCambridgeUK
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Kang M, Ang TFA, Devine SA, Sherva R, Mukherjee S, Trittschuh EH, Gibbons LE, Scollard P, Lee M, Choi SE, Klinedinst B, Nakano C, Dumitrescu LC, Durant A, Hohman TJ, Cuccaro ML, Saykin AJ, Kukull WA, Bennett DA, Wang LS, Mayeux RP, Haines JL, Pericak-Vance MA, Schellenberg GD, Crane PK, Au R, Lunetta KL, Mez JB, Farrer LA. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Mol Neurodegener 2023; 18:40. [PMID: 37349795 PMCID: PMC10286470 DOI: 10.1186/s13024-023-00633-4] [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: 02/17/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. METHODS We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. RESULTS Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. CONCLUSION Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.
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Affiliation(s)
- Moonil Kang
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Ting Fang Alvin Ang
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Sherral A. Devine
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Shubhabrata Mukherjee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Emily H. Trittschuh
- Geriatric Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, WA USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Laura E. Gibbons
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Phoebe Scollard
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Michael Lee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Seo-Eun Choi
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Brandon Klinedinst
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Connie Nakano
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Logan C. Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Alaina Durant
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, Miami, FL USA
| | - Andrew J. Saykin
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, WA USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Richard P. Mayeux
- Department of Neurology, Columbia University School of Medicine, New York, NY USA
| | - Jonathan L. Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH USA
| | | | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Paul K. Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
| | - Kathryn L. Lunetta
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Jesse B. Mez
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
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Gross AL, Li C, Briceno EM, Rentería MA, Jones RN, Langa KM, Manly JJ, Nichols EL, Weir D, Wong R, Berkman L, Lee J, Kobayashi LC. Harmonization of Later-Life Cognitive Function Across National Contexts: Results from the Harmonized Cognitive Assessment Protocols (HCAPs). MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.09.23291217. [PMID: 37398152 PMCID: PMC10312860 DOI: 10.1101/2023.06.09.23291217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background The Harmonized Cognitive Assessment Protocol (HCAP) is an innovative instrument for cross-national comparisons of later-life cognitive function, yet its suitability across diverse populations is unknown. We aimed to harmonize general and domain-specific cognitive scores from HCAPs across six countries, and evaluate precision and criterion validity of the resulting harmonized scores. Methods We statistically harmonized general and domain-specific cognitive function across the six publicly available HCAP partner studies in the United States, England, India, Mexico, China, and South Africa (N=21,141). We used an item banking approach that leveraged common cognitive test items across studies and tests that were unique to studies, as identified by a multidisciplinary expert panel. We generated harmonized factor scores for general and domain- specific cognitive function using serially estimated graded-response item response theory (IRT) models. We evaluated precision of the factor scores using test information plots and criterion validity using age, gender, and educational attainment. Findings IRT models of cognitive function in each country fit well. We compared measurement reliability of the harmonized general cognitive function factor across each cohort using test information plots; marginal reliability was high (r> 0·90) for 93% of respondents across six countries. In each country, general cognitive function scores were lower with older ages and higher with greater levels of educational attainment. Interpretation We statistically harmonized cognitive function measures across six large, population-based studies of cognitive aging in the US, England, India, Mexico, China, and South Africa. Precision of the estimated scores was excellent. This work provides a foundation for international networks of researchers to make stronger inferences and direct comparisons of cross-national associations of risk factors for cognitive outcomes. Funding National Institute on Aging (R01 AG070953, R01 AG030153, R01 AG051125, U01 AG058499; U24 AG065182; R01AG051158).
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St-Onge F, Chapleau M, Breitner JCS, Villeneuve S, Binette AP. Tau accumulation and its spatial progression across the Alzheimer's disease spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290880. [PMID: 37333413 PMCID: PMC10274981 DOI: 10.1101/2023.06.02.23290880] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The spread of tau abnormality in sporadic Alzheimer's disease is believed typically to follow neuropathologically defined Braak staging. Recent in-vivo positron emission tomography (PET) evidence challenges this belief, however, as spreading patterns for tau appear heterogenous among individuals with varying clinical expression of Alzheimer's disease. We therefore sought better understanding of the spatial distribution of tau in the preclinical and clinical phases of sporadic Alzheimer's disease and its association with cognitive decline. Longitudinal tau-PET data (1,370 scans) from 832 participants (463 cognitively unimpaired, 277 with mild cognitive impairment (MCI) and 92 with Alzheimer's disease dementia) were obtained from the Alzheimer's Disease Neuroimaging Initiative. Among these, we defined thresholds of abnormal tau deposition in 70 brain regions from the Desikan atlas, and for each group of regions characteristic of Braak staging. We summed each scan's number of regions with abnormal tau deposition to form a spatial extent index. We then examined patterns of tau pathology cross-sectionally and longitudinally and assessed their heterogeneity. Finally, we compared our spatial extent index of tau uptake with a temporal meta region of interest-a commonly used proxy of tau burden-assessing their association with cognitive scores and clinical progression. More than 80% of amyloid-beta positive participants across diagnostic groups followed typical Braak staging, both cross-sectionally and longitudinally. Within each Braak stage, however, the pattern of abnormality demonstrated significant heterogeneity such that overlap of abnormal regions across participants averaged less than 50%. The annual rate of change in number of abnormal tau-PET regions was similar among individuals without cognitive impairment and those with Alzheimer's disease dementia. Spread of disease progressed more rapidly, however, among participants with MCI. The latter's change on our spatial extent measure amounted to 2.5 newly abnormal regions per year, as contrasted with 1 region/year among the other groups. Comparing the association of tau pathology and cognitive performance in MCI and Alzheimer's disease dementia, our spatial extent index was superior to the temporal meta-ROI for measures of executive function. Thus, while participants broadly followed Braak stages, significant individual regional heterogeneity of tau binding was observed at each clinical stage. Progression of spatial extent of tau pathology appears to be fastest in persons with MCI. Exploring the spatial distribution of tau deposits throughout the entire brain may uncover further pathological variations and their correlation with impairments in cognitive functions beyond memory.
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Affiliation(s)
- Frédéric St-Onge
- Integrated Program in Neuroscience, Faculty of medicine, McGill University, Montreal, Qc, H3A 2B4, Canada
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
| | - Marianne Chapleau
- Faculty of medicine, University of California San Francisco, San Francisco, CA, 94143, United-States
| | - John CS Breitner
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
- Department of psychiatry, Faculty of medicine, McGill University, Montreal, QC, H3A 1Y2, Canada
| | - Sylvia Villeneuve
- Research Center of the Douglas Mental Health University Institute, Montreal, Qc, H4H 1R3, Canada
- Department of psychiatry, Faculty of medicine, McGill University, Montreal, QC, H3A 1Y2, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, H3A 2B4, Canada
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Malmö, 205 02, Sweden
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21
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Scollard P, Choi SE, Lee ML, Mukherjee S, Trittschuh EH, Sanders RE, Gibbons LE, Joshi P, Devine S, Au R, Dams-O’Connor K, Saykin AJ, Seshadri S, Beiser A, Aparicio HJ, Salinas J, Gonzales MM, Pase MP, Ghosh S, Finney R, Mez J, Crane PK. Ceiling effects and differential measurement precision across calibrated cognitive scores in the Framingham Study. Neuropsychology 2023; 37:383-397. [PMID: 37276135 PMCID: PMC10247160 DOI: 10.1037/neu0000828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023] Open
Abstract
OBJECTIVE To calibrate cognitive assessment data across multiple waves of the Framingham Heart Study (FHS), addressing study design considerations, ceiling effects, and measurement precision. METHOD FHS participants completed several cognitive assessments including screening instruments and more comprehensive batteries at different study visits. We used expert opinion to assign each cognitive test item to a single domain-memory, executive function, language, visuospatial abilities, or none of the above. As part of a larger cross-study harmonization effort, we calibrated each domain separately using bifactor confirmatory factor analysis (CFA) models, incorporating item parameters for anchor items previously calibrated from other studies and freely estimating item parameters for FHS-specific items. We obtained scores and standard errors (SEs) for each participant at each study visit. We addressed psychometric considerations of ceiling effects and measurement precision. RESULTS Overall, memory domain scores were the most precisely estimated. Scores for all domains from visits where the Mini-Mental State Examination (MMSE) was the only test administered were imprecisely estimated and suffered from ceiling effects. Scores from visits with a more extensive battery were estimated more precisely and better differentiated between ability levels. CONCLUSIONS The harmonized and calibrated cognitive data from the FHS should prove useful for future analyses examining cognition and cognitive decline. They will be of particular interest when combining FHS with other studies that have been similarly calibrated. Researchers should be aware of varying levels of measurement precision and the possibility of ceiling effects in their planned analyses of data from the FHS and similar studies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Phoebe Scollard
- Department of Medicine, University of Washington, Seattle, WA USA
| | - Seo-Eun Choi
- Department of Medicine, University of Washington, Seattle, WA USA
| | - Michael L. Lee
- Department of Medicine, University of Washington, Seattle, WA USA
| | | | - Emily H. Trittschuh
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA USA
- VA Puget Sound, Geriatric Research Education and Clinical Center
| | | | - Laura E. Gibbons
- Department of Medicine, University of Washington, Seattle, WA USA
| | - Prajakta Joshi
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA USA
- Department of General Dentistry, Boston University School of Dentistry, Boston, MA USA
| | - Sherral Devine
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY U.S.A
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY U.S.A
| | - Andrew J. Saykin
- Department of Radiology and Imaging Services, Indiana University, Indianapolis, IN USA
- Indiana Alzheimer’s Disease Research Center, Indiana University, Indianapolis, IN USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Alexa Beiser
- Department of Neurology, Boston University School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Hugo J. Aparicio
- Department of Neurology, Boston University School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Joel Salinas
- Department of Neurology, New York University Grossman School of Medicine, New York, NY USA
| | - Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX USA
| | - Matthew P. Pase
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC AUS
- Harvard T.H. Chan School of public health, Boston, MA USA
| | - Saptaparni Ghosh
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Rebecca Finney
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Alzheimer’s Disease Research Center, Boston, MA USA
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle, WA USA
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22
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Gavett BE, Ilango SD, Koscik R, Ma Y, Helfand B, Eng CW, Gross A, Trittschuh EH, Jones RN, Mungas D. Harmonization of cognitive screening tools for dementia across diverse samples: A simulation study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12438. [PMID: 37342610 PMCID: PMC10277671 DOI: 10.1002/dad2.12438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 03/29/2023] [Accepted: 04/10/2023] [Indexed: 06/23/2023]
Abstract
Introduction Research focusing on cognitive aging and dementia is a global endeavor. However, cross-national differences in cognition are embedded in other sociocultural differences, precluding direct comparisons of test scores. Such comparisons can be facilitated by co-calibration using item response theory (IRT). The goal of this study was to explore, using simulation, the necessary conditions for accurate harmonization of cognitive data. Method Neuropsychological test scores from the US Health and Retirement Study (HRS) and the Mexican Health and Aging Study (MHAS) were subjected to IRT analysis to estimate item parameters and sample means and standard deviations. These estimates were used to generate simulated item response patterns under 10 scenarios that adjusted the quality and quantity of linking items used in harmonization. IRT-derived factor scores were compared to the known population values to assess bias, efficiency, accuracy, and reliability of the harmonized data. Results The current configuration of HRS and MHAS data was not suitable for harmonization, as poor linking item quality led to large bias in both cohorts. Scenarios with more numerous and higher quality linking items led to less biased and more accurate harmonization. Discussion Linking items must possess low measurement error across the range of latent ability for co-calibration to be successful. HIGHLIGHTS We developed a statistical simulation platform to evaluate the degree to which cross-sample harmonization accuracy varies as a function of the quality and quantity of linking items.Two large studies of aging-one in Mexico and one in the United States-use three common items to measure cognition.These three common items have weak correspondence with the ability being measured and are all low in difficulty.Harmonized scores derived from the three common linking items will provide biased and inaccurate estimates of cognitive ability.Harmonization accuracy is greatest when linking items vary in difficulty and are strongly related to the ability being measured.
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Affiliation(s)
- Brandon E. Gavett
- School of Psychological ScienceUniversity of Western AustraliaPerthWestern AustraliaAustralia
| | - Sindana D. Ilango
- Department of EpidemiologyUniversity of Washington School of Public HealthSeattleWashingtonUSA
| | - Rebecca Koscik
- Wisconsin Alzheimer's InstituteUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Yue Ma
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Benjamin Helfand
- Department of Emergency MedicineUniversity of Massachusetts Medical SchoolWorcesterMassachusettsUSA
- Departments of Psychiatry and Human Behavior and NeurologyWarren Alpert Medical SchoolBrown UniversityProvidenceRhode IslandUSA
| | - Chloe W. Eng
- Department of Epidemiology and BiostatisticsUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Alden Gross
- Department of EpidemiologyJohns Hopkins Bloomberg School Public HealthBaltimoreMarylandUSA
| | - Emily H. Trittschuh
- VA Puget Sound Health Care SystemGeriatric Research Education and Clinical CareSeattleWashingtonUSA
- Department of Psychiatry and Behavioral SciencesUniversity of Washington School of MedicineSeattleWashingtonUSA
| | - Richard N. Jones
- Departments of Psychiatry and Human Behavior and NeurologyWarren Alpert Medical SchoolBrown UniversityProvidenceRhode IslandUSA
- Department of NeurologyBrown University Warren Alpert Medical SchoolProvidenceRhode IslandUSA
| | - Dan Mungas
- Department of NeurologyUniversity of CaliforniaSacramentoCaliforniaUSA
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23
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Sible IJ, Nation DA. Visit-to-Visit Blood Pressure Variability and Cognitive Decline in Apolipoprotein ɛ4 Carriers versus Apolipoprotein ɛ3 Homozygotes. J Alzheimers Dis 2023; 93:533-543. [PMID: 37066910 PMCID: PMC10852980 DOI: 10.3233/jad-221103] [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: 04/18/2023]
Abstract
BACKGROUND Blood pressure variability (BPV) is associated with cognitive decline and Alzheimer's disease (AD), but relationships with AD risk gene apolipoprotein (APOE) ɛ4 remain understudied. OBJECTIVE Examined the longitudinal relationship between BPV and cognitive change in APOE ɛ4 carriers and APOE ɛ3 homozygotes. METHODS 1,194 Alzheimer's Disease Neuroimaging Initiative participants (554 APOE ɛ4 carriers) underwent 3-4 blood pressure measurements between study baseline and 12-month follow-up. Visit-to-visit BPV was calculated as variability independent of mean over these 12 months. Participants subsequently underwent ≥1 neuropsychological exam at 12-month follow-up or later (up to 156 months later). Composite scores for the domains of memory, language, executive function, and visuospatial abilities were determined. Linear mixed models examined the 3-way interaction of BPV×APOE ɛ4 carrier status x time predicting change in composite scores. RESULTS Higher systolic BPV predicted greater decline in memory (+1 SD increase of BPV: β= -0.001, p < 0.001) and language (β= -0.002, p < 0.0001) among APOE ɛ4 carriers, but not APOE ɛ3 homozygotes (memory: +1 SD increase of BPV: β= 0.0001, p = 0.57; language: β= 0.0001, p = 0.72). Systolic BPV was not significantly associated with change in executive function or visuospatial abilities in APOE ɛ4 carriers (ps = 0.08-0.16) or APOE ɛ3 homozygotes (ps = 0.48-0.12). CONCLUSION Cognitive decline associated with high BPV may be specifically accelerated among APOE ɛ4 carriers.
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Affiliation(s)
- Isabel J. Sible
- Department of Psychology, University of Southern California, Los Angeles, CA 90007, USA
| | - Daniel A. Nation
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA 92697, USA
- Department of Psychological Science, University of California Irvine, Irvine, CA 92697, USA
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24
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Shaaban CE, Tudorascu DL, Glymour MM, Cohen AD, Thurston RC, Snyder HM, Hohman TJ, Mukherjee S, Yu L, Snitz BE. A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias. FRONTIERS IN NEUROIMAGING 2022; 1:978350. [PMID: 37464990 PMCID: PMC10353763 DOI: 10.3389/fnimg.2022.978350] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer's disease and related dementias (ADRD). Systematic harmonization of data elements is necessary to pool information from heterogeneous samples, and such pooling allows more expansive evaluations of health disparities, more precise effect estimates, and more opportunities to discover effective prevention or treatment strategies. The key goal of this Tutorial in Population Neuroimaging Curriculum, Instruction, and Pedagogy article is to guide researchers in creating a customized population neuroscience of ADRD harmonization training plan to fit their needs or those of their mentees. We provide brief guidance for retrospective data harmonization of multiple data types in this area, including: (1) clinical and demographic, (2) neuropsychological, and (3) neuroimaging data. Core competencies and skills are reviewed, and resources are provided to fill gaps in training as well as data needs. We close with an example study in which harmonization is a critical tool. While several aspects of this tutorial focus specifically on ADRD, the concepts and resources are likely to benefit population neuroscientists working in a range of research areas.
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Affiliation(s)
- C. Elizabeth Shaaban
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
| | - Dana L. Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Ann D. Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rebecca C. Thurston
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Heather M. Snyder
- Medical and Scientific Relations, Alzheimer’s Association, Chicago, IL, United States
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, United States
| | | | - Lan Yu
- Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Beth E. Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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