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Chapleau M, La Joie R, Yong K, Agosta F, Allen IE, Apostolova L, Best J, Boon BDC, Crutch S, Filippi M, Fumagalli GG, Galimberti D, Graff-Radford J, Grinberg LT, Irwin DJ, Josephs KA, Mendez MF, Mendez PC, Migliaccio R, Miller ZA, Montembeault M, Murray ME, Nemes S, Pelak V, Perani D, Phillips J, Pijnenburg Y, Rogalski E, Schott JM, Seeley W, Sullivan AC, Spina S, Tanner J, Walker J, Whitwell JL, Wolk DA, Ossenkoppele R, Rabinovici GD. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis. Lancet Neurol 2024; 23:168-177. [PMID: 38267189 DOI: 10.1016/s1474-4422(23)00414-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/22/2023] [Accepted: 10/18/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING None.
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Affiliation(s)
- Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Keir Yong
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Federica Agosta
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - John Best
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Baayla D C Boon
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Sebastian Crutch
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Massimo Filippi
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | | | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | | | - Lea T Grinberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Mario F Mendez
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Patricio Chrem Mendez
- Memory Center, Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia, Buenos Aires Argentina
| | - Raffaella Migliaccio
- Paris Brain Institute (ICM), FrontLab, Institut de la mémoire et de la maladie d'Alzheimer (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, Paris, France
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maxime Montembeault
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Sára Nemes
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Victoria Pelak
- Departments of Neurology and Ophthalmology, Divisions of Neuro-Ophthalmology and Behavioral Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Daniela Perani
- Vita-Salute, San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele, San Raffaele University, Milan, Italy
| | - Jeffrey Phillips
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology & Alzheimer's Disease, Northwestern University, Evanston, IL, USA
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands
| | - William Seeley
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - A Campbell Sullivan
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Jeremy Tanner
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jamie Walker
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | | | - David A Wolk
- Alzheimer's Disease Research Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands; Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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Ofori E, Vaillancourt DE, Greig-Custo MT, Barker W, Hanson K, DeKosky ST, Garvan CS, Adjouadi M, Golde T, Loewenstein DA, Stecher C, Fowers R, Duara R. Free-water imaging reveals unique brain microstructural deficits in hispanic individuals with Dementia. Brain Imaging Behav 2024; 18:106-116. [PMID: 37903991 PMCID: PMC11157151 DOI: 10.1007/s11682-023-00819-w] [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] [Accepted: 10/22/2023] [Indexed: 11/01/2023]
Abstract
Prior evidence suggests that Hispanic and non-Hispanic individuals differ in potential risk factors for the development of dementia. Here we determine whether specific brain regions are associated with cognitive performance for either ethnicity along various stages of Alzheimer's disease. For this cross-sectional study, we examined 108 participants (61 Hispanic vs. 47 Non-Hispanic individuals) from the 1Florida Alzheimer's Disease Research Center (1Florida ADRC), who were evaluated at baseline with diffusion-weighted and T1-weighted imaging, and positron emission tomography (PET) amyloid imaging. We used FreeSurfer to segment 34 cortical regions of interest. Baseline Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used as measures of cognitive performance. Group analyses assessed free-water measures (FW) and volume. Statistically significant FW regions based on ethnicity x group interactions were used in a stepwise regression function to predict total MMSE and MoCA scores. Random forest models were used to identify the most predictive brain-based measures of a dementia diagnosis separately for Hispanic and non-Hispanic groups. Results indicated elevated FW values for the left inferior temporal gyrus, left middle temporal gyrus, left banks of the superior temporal sulcus, left supramarginal gyrus, right amygdala, and right entorhinal cortex in Hispanic AD subjects compared to non-Hispanic AD subjects. These alterations occurred in the absence of different volumes of these regions in the two AD groups. FW may be useful in detecting individual differences potentially reflective of varying etiology that can influence cognitive decline and identify MRI predictors of cognitive performance, particularly among Hispanics.
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Affiliation(s)
- Edward Ofori
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA.
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Maria T Greig-Custo
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
| | - Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
| | - Kevin Hanson
- Clinical and Translational Science Institute, University of Florida, Gainesville, FL, USA
| | - Steven T DeKosky
- Emory Center for Neurodegenerative Disease, Departments of Pharmacology, Chemical Biology, & Neurology, Atlanta, GA, USA
| | - Cynthia S Garvan
- Department of Anesthesiology, University of Florida, Gainesville, FL, USA
| | - Malek Adjouadi
- Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Todd Golde
- Emory Center for Neurodegenerative Disease, Departments of Pharmacology, Chemical Biology, & Neurology, Atlanta, GA, USA
- Department of Psychiatry, Miller School of Medicine, Center for Cognitive Neuroscience and Aging University of Miami, Miami, FL, USA
| | - David A Loewenstein
- Department of Psychiatry, Miller School of Medicine, Center for Cognitive Neuroscience and Aging University of Miami, Miami, FL, USA
| | - Chad Stecher
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA
| | - Rylan Fowers
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
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3
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Isella V, Licciardo D, Nastasi G, Impagnatiello V, Ferri F, Mapelli C, Crivellaro C, Musarra M, Morzenti S, Appollonio I, Ferrarese C. Clinical and metabolic imaging features of late-onset and early-onset posterior cortical atrophy. Eur J Neurol 2022; 29:3147-3157. [PMID: 35950612 PMCID: PMC9804481 DOI: 10.1111/ene.15520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/12/2022] [Accepted: 08/04/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND AND PURPOSE Late-onset (LO) and early-onset (EO) dementia show neurobiological and clinical differences. Clinical and 18 fluoro-deoxy-glucose positron emission tomography (FDG-PET) features of LO and EO posterior cortical atrophy (LO_PCA, EO_PCA), the visual variant of Alzheimer's disease (AD), were compared. LO_PCA patients were also compared with a group of patients with LO typical AD (tAD). METHODS Thirty-seven LO_PCA patients (onset age ≥ 65 years), 29 EO_PCA patients and 40 tAD patients who all underwent a standard neuropsychological battery were recruited; PCA patients were also assessed for the presence of posterior signs and symptoms. Brain FDG-PET was available in 32 LO_PCA cases, 23 EO_PCA cases and all tAD cases, and their scans were compared with scans from 30 healthy elderly controls. Within the entire PCA sample FDG uptake was also correlated with age at onset as a continuous variable. RESULTS The main difference between the two PCA groups was a higher prevalence of Bálint-Holmes symptoms in EO cases, which was associated with the presence of severe bilateral occipito-temporo-parietal hypometabolism, whilst LO_PCA patients showed reduction of FDG uptake mainly in the right posterior regions. The latter group also showed mesial temporal hypometabolism, similarly to the tAD group, although with a right rather than left lateralization. Correlation analysis confirmed the association between older age and decreased limbic metabolism and between younger age and decreased left parietal metabolism. CONCLUSIONS The major involvement of the temporal cortex in LO cases and of the parietal cortex in EO cases reported previously within the AD spectrum holds true also for the visual variant of AD.
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Affiliation(s)
- Valeria Isella
- Neurology, School of MedicineUniversity of Milano—BicoccaMonzaItaly,Milan Center for NeurosciencesNeuroMIMilanItaly
| | - Daniele Licciardo
- Milan Center for NeurosciencesNeuroMIMilanItaly,Neurology DepartmentSan Gerardo HospitalMonzaLombardiaItaly
| | - Giulia Nastasi
- Neurology DepartmentASST of VimercateVimercateLombardiaItaly
| | - Valentina Impagnatiello
- Milan Center for NeurosciencesNeuroMIMilanItaly,Neurology DepartmentSan Gerardo HospitalMonzaLombardiaItaly
| | - Francesca Ferri
- Milan Center for NeurosciencesNeuroMIMilanItaly,Neurology DepartmentSan Gerardo HospitalMonzaLombardiaItaly
| | | | | | - Monica Musarra
- Nuclear Medicine UnitSan Gerardo HospitalMonzaLombardiaItaly
| | | | - Ildebrando Appollonio
- Neurology, School of MedicineUniversity of Milano—BicoccaMonzaItaly,Milan Center for NeurosciencesNeuroMIMilanItaly,Neurology DepartmentSan Gerardo HospitalMonzaLombardiaItaly
| | - Carlo Ferrarese
- Neurology, School of MedicineUniversity of Milano—BicoccaMonzaItaly,Milan Center for NeurosciencesNeuroMIMilanItaly,Neurology DepartmentSan Gerardo HospitalMonzaLombardiaItaly
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4
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Josephs KA, Pham NTT, Graff-Radford J, Machulda MM, Lowe VJ, Whitwell JL. Medial Temporal Atrophy in Posterior Cortical Atrophy and Its Relationship to the Cingulate Island Sign. J Alzheimers Dis 2022; 86:491-498. [DOI: 10.3233/jad-215263] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Background: It has been hypothesized that medial temporal sparing may be related to preserved posterior cingulate metabolism and the cingulate island sign (CIS) on [18F]fluorodeoxyglucose (FDG) PET in posterior cortical atrophy (PCA). Objective: To assess the severity of medial temporal atrophy in PCA and determine whether the presence of a CIS is related to medial temporal sparing. Methods: Fifty-five PCA patients underwent MRI and FDG-PET. The degree and symmetry of medial temporal atrophy on MRI was visually assessed using a five-point scale for both hemispheres. Visual assessments of FDG-PET coded the presence/absence of a CIS and whether the CIS was symmetric or asymmetric. Hippocampal volumes and a quantitative CIS were also measured. Results: Medial temporal atrophy was most commonly mild or moderate, was symmetric in 55% of patients, and when asymmetric was most commonly worse on the right (76%). Older age and worse memory performance were associated with greater medial temporal atrophy. The CIS was observed in 44% of the PCA patients and was asymmetric in 50% of these. The patients with a CIS showed greater medial temporal asymmetry, but did not show lower medial temporal atrophy scores, compared to those without a CIS. Hippocampal volumes were not associated with quantitative CIS. Conclusion: Mild medial temporal atrophy is a common finding in PCA and is associated with memory impairment. However, medial temporal sparing was not related to the presence of a CIS in PCA.
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Affiliation(s)
| | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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5
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Veale T, Malone IB, Poole T, Parker TD, Slattery CF, Paterson RW, Foulkes AJM, Thomas DL, Schott JM, Zhang H, Fox NC, Cash DM. Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study. Brain Commun 2021; 3:fcab272. [PMID: 34859218 PMCID: PMC8633427 DOI: 10.1093/braincomms/fcab272] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 09/24/2021] [Accepted: 10/18/2021] [Indexed: 11/22/2022] Open
Abstract
Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.
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Affiliation(s)
- Thomas Veale
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Teresa Poole
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Thomas D Parker
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Catherine F Slattery
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W Paterson
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Alexander J M Foulkes
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - David L Thomas
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan M Schott
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Nick C Fox
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - David M Cash
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
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6
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Spatial patterns of correlation between cortical amyloid and cortical thickness in a tertiary clinical population with memory deficit. Sci Rep 2020; 10:20717. [PMID: 33244036 PMCID: PMC7693188 DOI: 10.1038/s41598-020-77503-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/11/2020] [Indexed: 12/28/2022] Open
Abstract
To estimate regional Alzheimer disease (AD) pathology burden clinically, analysis methods that enable tracking brain amyloid or tau positron emission tomography (PET) with magnetic resonance imaging (MRI) measures are needed. We therefore developed a robust MRI analysis method to identify brain regions that correlate linearly with regional amyloid burden in congruent PET images. This method was designed to reduce data variance and improve the sensitivity of the detection of cortical thickness-amyloid correlation by using whole brain modeling, nonlinear image coregistration, and partial volume correction. Using this method, a cross-sectional analysis of 75 tertiary memory clinic AD patients was performed to test our hypothesis that regional amyloid burden and cortical thickness are inversely correlated in medial temporal neocortical regions. Medial temporal cortical thicknesses were not correlated with their regional amyloid burden, whereas cortical thicknesses in the lateral temporal, lateral parietal, and frontal regions were inversely correlated with amyloid burden. This study demonstrates the robustness of our technique combining whole brain modeling, nonlinear image coregistration, and partial volume correction to track the differential correlation between regional amyloid burden and cortical thinning in specific brain regions. This method could be used with amyloid and tau PET to assess corresponding cortical thickness changes.
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7
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Kraft JN, O'Shea A, Albizu A, Evangelista ND, Hausman HK, Boutzoukas E, Nissim NR, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, Porges E, DeKosky S, Hishaw GA, Wu S, Marsiske M, Cohen R, Alexander GE, Woods AJ. Structural Neural Correlates of Double Decision Performance in Older Adults. Front Aging Neurosci 2020; 12:278. [PMID: 33117145 PMCID: PMC7493680 DOI: 10.3389/fnagi.2020.00278] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 08/11/2020] [Indexed: 11/13/2022] Open
Abstract
Speed of processing is a cognitive domain that encompasses the speed at which an individual can perceive a given stimulus, interpret the information, and produce a correct response. Speed of processing has been shown to decline more rapidly than other cognitive domains in an aging population, suggesting that this domain is particularly vulnerable to cognitive aging (Chee et al., 2009). However, given the heterogeneity of neuropsychological measures used to assess the domains underpinning speed of processing, a diffuse pattern of brain regions has been implicated. The current study aims to investigate the structural neural correlates of speed of processing by assessing cortical volume and speed of processing scores on the POSIT Double Decision task within a healthy older adult population (N = 186; mean age = 71.70 ± 5.32 years). T1-weighted structural images were collected via a 3T Siemens scanner. The current study shows that less cortical thickness in right temporal, posterior frontal, parietal and occipital lobe structures were significantly associated with poorer Double Decision scores. Notably, these include the lateral orbitofrontal gyrus, precentral gyrus, superior, transverse, and inferior temporal gyrus, temporal pole, insula, parahippocampal gyrus, fusiform gyrus, lingual gyrus, superior and inferior parietal gyrus and lateral occipital gyrus. Such findings suggest that speed of processing performance is associated with a wide array of cortical regions that provide unique contributions to performance on the Double Decision task.
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Affiliation(s)
- Jessica N Kraft
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Emanuel Boutzoukas
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Nicole R Nissim
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Eric Porges
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Steven DeKosky
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, United States
| | - Samuel Wu
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Michael Marsiske
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Ronald Cohen
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Gene E Alexander
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States.,Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, United States
| | - Adam J Woods
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
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8
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Whitwell JL, Martin P, Graff-Radford J, Machulda MM, Senjem ML, Schwarz CG, Weigand SD, Spychalla AJ, Drubach DA, Jack CR, Lowe VJ, Josephs KA. The role of age on tau PET uptake and gray matter atrophy in atypical Alzheimer's disease. Alzheimers Dement 2019; 15:675-685. [PMID: 30853465 DOI: 10.1016/j.jalz.2018.12.016] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 11/02/2018] [Accepted: 12/29/2018] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Little is known about the role of age on neurodegeneration and protein deposition in atypical variants of Alzheimer's disease (AD). METHODS Regional tau and β-amyloid positron emission tomography standard uptake value ratios and gray matter volumes were calculated in a cohort of 42 participants with atypical AD. The relationship between regional metrics and age was modeled using a Bayesian hierarchical linear model. RESULTS Age was strongly associated with tau uptake across all cortical regions, particularly parietal, with greater uptake in younger participants. Younger age was associated with smaller parietal and lateral temporal volumes. Regional β-amyloid differed little by age. Age showed a stronger association with tau than volume and β-amyloid in all cortical regions. Age was not associated with cognitive performance. DISCUSSION Age is an important determinant of severity of cortical tau uptake in atypical AD, with young participants more likely to show widespread and severe cortical tau uptake.
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Affiliation(s)
| | - Peter Martin
- Department of Health Science Research, Mayo Clinic, Rochester MN, USA
| | | | - Mary M Machulda
- Department of Psychology and Psychiatry, Mayo Clinic, Rochester MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester MN, USA; Department of Information Technology, Mayo Clinic, Rochester MN, USA
| | | | - Stephen D Weigand
- Department of Health Science Research, Mayo Clinic, Rochester MN, USA
| | | | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester MN, USA
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9
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Whitwell JL, Graff-Radford J, Tosakulwong N, Weigand SD, Machulda MM, Senjem ML, Spychalla AJ, Vemuri P, Jones DT, Drubach DA, Knopman DS, Boeve BF, Ertekin-Taner N, Petersen RC, Lowe VJ, Jack CR, Josephs KA. Imaging correlations of tau, amyloid, metabolism, and atrophy in typical and atypical Alzheimer's disease. Alzheimers Dement 2018; 14:1005-1014. [PMID: 29605222 DOI: 10.1016/j.jalz.2018.02.020] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Revised: 12/18/2017] [Accepted: 02/07/2018] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Neuroimaging modalities can measure different aspects of the disease process in Alzheimer's disease, although the relationship between these modalities is unclear. METHODS We assessed subject-level regional correlations between tau on [18F]AV-1451 positron emission tomography (PET), β amyloid on Pittsburgh compound B PET, hypometabolism on [18F] fluorodeoxyglucose PET, and cortical thickness on magnetic resonance imaging in 96 participants with typical and atypical Alzheimer's disease presentations. We also assessed how correlations between modalities varied according to age, presenting syndrome, tau-PET severity, and asymmetry. RESULTS [18F]AV-1451 uptake showed the strongest regional correlation with hypometabolism. Correlations between [18F]AV-1451 uptake and both hypometabolism and cortical thickness were stronger in participants with greater cortical tau severity. In addition, age, tau asymmetry, and clinical diagnosis influenced the strength of the correlation between [18F]AV-1451 uptake and cortical thickness. DISCUSSION These findings support a close relationship between tau and hypometabolism in Alzheimer's disease but show that correlations between neuroimaging modalities vary across participants.
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Affiliation(s)
| | | | | | - Stephen D Weigand
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychology and Psychiatry, Mayo Clinic, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA; Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Nilüfer Ertekin-Taner
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA; Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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10
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Fiford CM, Ridgway GR, Cash DM, Modat M, Nicholas J, Manning EN, Malone IB, Biessels GJ, Ourselin S, Carmichael OT, Cardoso MJ, Barnes J. Patterns of progressive atrophy vary with age in Alzheimer's disease patients. Neurobiol Aging 2018; 63:22-32. [PMID: 29220823 PMCID: PMC5805840 DOI: 10.1016/j.neurobiolaging.2017.11.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 10/14/2017] [Accepted: 11/06/2017] [Indexed: 01/18/2023]
Abstract
Age is not only the greatest risk factor for Alzheimer's disease (AD) but also a key modifier of disease presentation and progression. Here, we investigate how longitudinal atrophy patterns vary with age in mild cognitive impairment (MCI) and AD. Data comprised serial longitudinal 1.5-T magnetic resonance imaging scans from 153 AD, 339 MCI, and 191 control subjects. Voxel-wise maps of longitudinal volume change were obtained and aligned across subjects. Local volume change was then modeled in terms of diagnostic group and an interaction between group and age, adjusted for total intracranial volume, white-matter hyperintensity volume, and apolipoprotein E genotype. Results were significant at p < 0.05 with family-wise error correction for multiple comparisons. An age-by-group interaction revealed that younger AD patients had significantly faster atrophy rates in the bilateral precuneus, parietal, and superior temporal lobes. These results suggest younger AD patients have predominantly posterior progressive atrophy, unexplained by white-matter hyperintensity, apolipoprotein E, or total intracranial volume. Clinical trials may benefit from adapting outcome measures for patient groups with lower average ages, to capture progressive atrophy in posterior cortices.
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Affiliation(s)
- Cassidy M Fiford
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
| | - Gerard R Ridgway
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Marc Modat
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | | | - Emily N Manning
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Ian B Malone
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Sebastien Ourselin
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | | | - M Jorge Cardoso
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
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