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Debatisse J, Leng F, Ashraf A, Edison P. Cortical Diffusivity, a Biomarker for Early Neuronal Damage, Is Associated with Amyloid-β Deposition: A Pilot Study. Cells 2025; 14:155. [PMID: 39936947 PMCID: PMC11817142 DOI: 10.3390/cells14030155] [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: 12/08/2024] [Revised: 01/09/2025] [Accepted: 01/17/2025] [Indexed: 02/13/2025] Open
Abstract
Pathological alterations in Alzheimer's disease (AD) begin several years prior to symptom onset. Cortical mean diffusivity (cMD) may be used as a measure of early grey matter damage in AD as it reflects the breakdown of microstructural barriers preceding volumetric changes and affecting cognitive function. We investigated cMD changes early in the disease trajectory and evaluated the influence of amyloid-β (Aβ) and tau deposition. In this cross-sectional study, we analysed multimodal PET, DTI, and MRI data of 87 participants, and stratified them into Aβ-negative and -positive, cognitively normal, mildly cognitively impaired, and AD patients. cMD was significantly increased in Aβ-positive MCI and AD compared with CN in the frontal, parietal, temporal cortex, hippocampus, and medial temporal lobe. cMD was significantly correlated with cortical thickness only in patients without Aβ deposition but not in Aβ-positive patients. Our results suggest that cMD is an early marker of neuronal damage since it is observed simultaneously with Aβ deposition and is correlated with cortical thickness only in subjects without Aβ deposition. cMD changes may be driven by Aβ but not tau, suggesting that direct Aβ toxicity or associated inflammation causes damage to neurons. cMD may provide information about early microstructural changes before macrostructural changes.
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Affiliation(s)
- Justine Debatisse
- Division of Neurology, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK; (J.D.); (F.L.); (A.A.)
| | - Fangda Leng
- Division of Neurology, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK; (J.D.); (F.L.); (A.A.)
| | - Azhaar Ashraf
- Division of Neurology, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK; (J.D.); (F.L.); (A.A.)
| | - Paul Edison
- Division of Neurology, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK; (J.D.); (F.L.); (A.A.)
- School of Medicine, Cardiff University, Wales CF14 4YS, UK
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Sun P, He Z, Li A, Yang J, Zhu Y, Cai Y, Ma T, Ma S, Guo T. Spatial and temporal patterns of cortical mean diffusivity in Alzheimer's disease and suspected non-Alzheimer's disease pathophysiology. Alzheimers Dement 2024; 20:7048-7061. [PMID: 39132849 PMCID: PMC11485315 DOI: 10.1002/alz.14176] [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: 04/12/2024] [Revised: 07/12/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION The spatial and temporal patterns of cortical mean diffusivity (cMD), as well as its association with Alzheimer's disease (AD) and suspected non-Alzheimer's pathophysiology (SNAP), are not yet fully understood. METHODS We compared baseline (n = 617) and longitudinal changes (n = 421) of cMD, cortical thickness, and gray matter volume and their relations to vascular risk factors, amyloid beta (Aβ), and tau positron emission tomography (PET), and longitudinal cognitive decline in Aβ PET negative and positive older adults. RESULTS cMD increases were more sensitive to detecting brain structural alterations than cortical thinning and gray matter atrophy. Tau-related cMD increases partially mediated Aβ-related cognitive decline in AD, whereas vascular disease-related increased cMD levels substantially mediated age-related cognitive decline in SNAP. DISCUSSION These findings revealed the dynamic changes of microstructural and macrostructural indicators and their associations with AD and SNAP, providing novel insights into understanding upstream and downstream events of cMD in neurodegenerative disease. HIGHLIGHTS Cortical mean diffusivity (cMD) was more sensitive to detecting structural changes than macrostructural factors. Tau-related cMD increases partially mediated amyloid beta-related cognitive decline in Alzheimer's disease (AD). White matter hyperintensity-related higher cMD mainly explained the age-related cognitive decline in suspected non-Alzheimer's pathophysiology (SNAP). cMD may assist in tracking earlier neurodegenerative signs in AD and SNAP.
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Affiliation(s)
- Pan Sun
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
- Tsinghua Shenzhen International Graduate School (SIGS)Tsinghua UniversityShenzhenChina
| | - Zhengbo He
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Anqi Li
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Jie Yang
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Yalin Zhu
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Yue Cai
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Ting Ma
- School of Electronic and Information EngineeringHarbin Institute of Technology (Shenzhen)ShenzhenChina
| | - Shaohua Ma
- Tsinghua Shenzhen International Graduate School (SIGS)Tsinghua UniversityShenzhenChina
| | - Tengfei Guo
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
- Institute of Biomedical EngineeringPeking University Shenzhen Graduate SchoolShenzhenChina
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Torso M, Fumagalli G, Ridgway GR, Contarino VE, Hardingham I, Scarpini E, Galimberti D, Chance SA, Arighi A. Clinical utility of diffusion MRI-derived measures of cortical microstructure in a real-world memory clinic setting. Ann Clin Transl Neurol 2024; 11:1964-1976. [PMID: 39049198 PMCID: PMC11330221 DOI: 10.1002/acn3.52097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/09/2024] [Accepted: 05/12/2024] [Indexed: 07/27/2024] Open
Abstract
OBJECTIVE To investigate cortical microstructural measures from diffusion MRI as "neurodegeneration" markers that could improve prognostic accuracy in mild cognitive impairment (MCI). METHODS The prognostic power of Amyloid/Tau/Neurodegeneration (ATN) biomarkers to predict progression from MCI to AD or non-AD dementia was investigated. Ninety patients underwent clinical evaluation (follow-up interval 32 ± 18 months), lumbar puncture, and MRI. Participants were grouped by clinical stage and cerebrospinal fluid Amyloid and Tau status. T1-structural and diffusion MRI scans were analyzed to calculate diffusion metrics related to cortical columnar structure (AngleR, ParlPD, PerpPD+), cortical mean diffusivity, and fractional anisotropy. Statistical tests were corrected for multiple comparisons. Prognostic power was assessed using receiver operating characteristic (ROC) analysis and related indices. RESULTS A progressive increase of whole-brain cortical diffusion values was observed along the AD continuum, with all A+ groups showing significantly higher AngleR than A-T-. Investigating clinical progression to dementia, the AT biomarkers together showed good positive predictive value (with 90.91% of MCI A+T+ converting to dementia) but poor negative predictive value (with 40% of MCI A-T- progressing to a mix of AD and non-AD dementias). Adding whole-brain AngleR as an N marker, produced good differentiation between stable and converting MCI A-T- patients (0.8 area under ROC curve) and substantially improved negative predictive value (+21.25%). INTERPRETATION Results support the clinical utility of cortical microstructure to aid prognosis, especially in A-T- patients. Further work will investigate other complexities of the real-world clinical setting, including A-T+ groups. Diffusion MRI measures of neurodegeneration may complement fluid AT markers to support clinical decision-making.
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Affiliation(s)
| | - Giorgio Fumagalli
- Center For Mind/Brain Sciences‐CIMeCUniversity of TrentoRoveretoItaly
| | | | | | | | - Elio Scarpini
- Neurodegenerative Disease UnitFondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly
| | - Daniela Galimberti
- Neurodegenerative Disease UnitFondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly
- Dept. of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | | | - Andrea Arighi
- Neurodegenerative Disease UnitFondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly
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Mencarelli L, Torso M, Borghi I, Assogna M, Pezzopane V, Bonnì S, Di Lorenzo F, Santarnecchi E, Giove F, Martorana A, Bozzali M, Ridgway GR, Chance SA, Koch G. Macro and micro structural preservation of grey matter integrity after 24 weeks of rTMS in Alzheimer's disease patients: a pilot study. Alzheimers Res Ther 2024; 16:152. [PMID: 38970141 PMCID: PMC11225141 DOI: 10.1186/s13195-024-01501-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 06/12/2024] [Indexed: 07/07/2024]
Abstract
Alzheimer's Disease (AD) is characterized by structural and functional dysfunction involving the Default Mode Network (DMN), for which the Precuneus (PC) is a key node. We proposed a randomized double-blind pilot study to determine neurobiological changes after 24 weeks of PC-rTMS in patients with mild-to-moderate AD. Sixteen patients were randomly assigned to SHAM or PC-rTMS, and received an intensive 2-weeks course with daily rTMS sessions, followed by a maintenance phase in which rTMS has been applied once a week. Before and after the treatment structural and functional MRIs were collected. Our results showed macro- and micro-structural preservation in PC-rTMS compared to SHAM-rTMS group after 24 weeks of treatment, correlated to an increase of functional connectivity (FC) within the PC in the PC-rTMS group. Even if preliminary, these results trigger the possibility of using PC-rTMS to arrest atrophy progression by manipulating distributed network connectivity patterns.
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Affiliation(s)
- Lucia Mencarelli
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Mario Torso
- Oxford Brain Diagnostics Ltd, New Rd, Oxford, OX1 1BY, UK
| | - Ilaria Borghi
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari, 46, Ferrara, 44121, Italy
| | - Martina Assogna
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Valentina Pezzopane
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Via Fossato di Mortara, 19, Ferrara, 44121, Italy
| | - Sonia Bonnì
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Francesco Di Lorenzo
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Massachusetts General Hospital & Harvard Medical School, 125 Nashua Street, Boston, MA, 02114- 1107, USA
| | - Federico Giove
- Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Via Ardeatina 306, Rome, 00179, Italy
- MARBILab, Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Via Panisperna 89 A, Rome, 00184, Italy
| | - Alessandro Martorana
- Department of Systems Medicine, Memory Clinic, University of Tor Vergata, Via Montpellier 1, Rome, 00133, Italy
| | - Marco Bozzali
- Neuroscience Department "Rita Levi Montalcini", University of Turin, Via Cherasco, 15, Turin, 10126, Italy
| | | | | | - Giacomo Koch
- Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Via Ardeatina, 306, Rome, 00179, Italy.
- Department of Neuroscience and Rehabilitation, University of Ferrara, Via Luigi Borsari, 46, Ferrara, 44121, Italy.
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Via Fossato di Mortara, 19, Ferrara, 44121, Italy.
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Langley J, Bennett IJ, Hu XP. Examining iron-related off-target binding effects of 18F-AV1451 PET in the cortex of Aβ+ individuals. Eur J Neurosci 2024; 60:3614-3628. [PMID: 38722153 DOI: 10.1111/ejn.16362] [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: 02/10/2023] [Revised: 12/22/2023] [Accepted: 04/01/2024] [Indexed: 07/06/2024]
Abstract
The presence of neurofibrillary tangles containing hyper-phosphorylated tau is a characteristic of Alzheimer's disease (AD) pathology. The positron emission tomography (PET) radioligand sensitive to tau neurofibrillary tangles (18F-AV1451) also binds with iron. This off-target binding effect may be enhanced in older adults on the AD spectrum, particularly those with amyloid-positive biomarkers. Here, we examined group differences in 18F-AV1451 PET after controlling for iron-sensitive measures from magnetic resonance imaging (MRI) and its relationships to tissue microstructure and cognition in 40 amyloid beta positive (Aβ+) individuals, 20 amyloid beta negative (Aβ-) with MCI and 31 Aβ- control participants. After controlling for iron, increased 18F-AV1451 PET uptake was found in the temporal lobe and hippocampus of Aβ+ participants compared to Aβ- MCI and control participants. Within the Aβ+ group, significant correlations were seen between 18F-AV1451 PET uptake and tissue microstructure and these correlations remained significant after controlling for iron. These findings indicate that off-target binding of iron to the 18F-AV1451 ligand may not affect its sensitivity to Aβ status or cognition in early-stage AD.
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Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
| | - Ilana J Bennett
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Xiaoping P Hu
- Center for Advanced Neuroimaging, University of California Riverside, Riverside, California, USA
- Department of Bioengineering, University of California Riverside, Riverside, California, USA
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Reveley C, Ye FQ, Leopold DA. Diffusion kurtosis MRI tracks gray matter myelin content in the primate cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.584058. [PMID: 38496676 PMCID: PMC10942417 DOI: 10.1101/2024.03.08.584058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) has been widely employed to model the trajectory of myelinated fiber bundles in white matter. Increasingly, dMRI is also used to assess local tissue properties throughout the brain. In the cerebral cortex, myelin content is a critical indicator of the maturation, regional variation, and disease related degeneration of gray matter tissue. Gray matter myelination can be measured and mapped using several non-diffusion MRI strategies; however, first order diffusion statistics such as fractional anisotropy (FA) show only weak spatial correlation with cortical myelin content. Here we show that a simple higher order diffusion parameter, the mean diffusion kurtosis (MK), is strongly correlated with the laminar and regional variation of myelin in the primate cerebral cortex. We carried out ultra-high resolution, multi-shelled dMRI in ex vivo marmoset monkey brains and compared dMRI parameters from a number of higher order models (diffusion kurtosis, NODDI and MAP MRI) to the distribution of myelin obtained using histological staining, and via Magnetization Transfer Ratio MRI (MTR), a non-diffusion MRI method. In contrast to FA, MK closely matched the myelin content assessed by histology and by MTR in the same sample. The parameter maps from MAP-MRI and NODDI also showed good correspondence with cortical myelin content. The results demonstrate that dMRI can be used to assess the variation of local myelin content in the primate cortical cortex, which may be of great value for assessing tissue integrity and tracking disease in living human patients.
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Affiliation(s)
- Colin Reveley
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
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Spotorno N, Strandberg O, Stomrud E, Janelidze S, Blennow K, Nilsson M, van Westen D, Hansson O. Diffusion MRI tracks cortical microstructural changes during the early stages of Alzheimer's disease. Brain 2024; 147:961-969. [PMID: 38128551 PMCID: PMC10907088 DOI: 10.1093/brain/awad428] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 11/02/2023] [Accepted: 12/03/2023] [Indexed: 12/23/2023] Open
Abstract
There is increased interest in developing markers reflecting microstructural changes that could serve as outcome measures in clinical trials. This is especially important after unexpected results in trials evaluating disease-modifying therapies targeting amyloid-β (Aβ), where morphological metrics from MRI showed increased volume loss despite promising clinical treatment effects. In this study, changes over time in cortical mean diffusivity, derived using diffusion tensor imaging, were investigated in a large cohort (n = 424) of non-demented participants from the Swedish BioFINDER study. Participants were stratified following the Aβ/tau (AT) framework. The results revealed a widespread increase in mean diffusivity over time, including both temporal and parietal cortical regions, in Aβ-positive but still tau-negative individuals. These increases were steeper in Aβ-positive and tau-positive individuals and robust to the inclusion of cortical thickness in the model. A steeper increase in mean diffusivity was also associated with both changes over time in fluid markers reflecting astrocytic activity (i.e. plasma level of glial fibrillary acidic protein and CSF levels of YKL-40) and worsening of cognitive performance (all P < 0.01). By tracking cortical microstructural changes over time and possibly reflecting variations related to the astrocytic response, cortical mean diffusivity emerges as a promising marker for tracking treatments-induced microstructural changes in clinical trials.
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Affiliation(s)
- Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 214 28 Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 431 80 Mölndal, Sweden
| | - Markus Nilsson
- Diagnostic Radiology, Institution for Clinical Sciences, Lund University, 221 85 Lund, Sweden
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
- Diagnostic Radiology, Institution for Clinical Sciences, Lund University, 221 85 Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, 223 62 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 214 28 Malmö, Sweden
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Mak E, Dounavi ME, Operto G, Ziukelis ET, Jones PS, Low A, Swann P, Newton C, Muniz Terrera G, Malhotra P, Koychev I, Falcon C, Mackay C, Lawlor B, Naci L, Wells K, Ritchie C, Ritchie K, Su L, Gispert JD, O’Brien JT. APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure. Brain Commun 2024; 6:fcad351. [PMID: 38384997 PMCID: PMC10881196 DOI: 10.1093/braincomms/fcad351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 10/20/2023] [Accepted: 02/09/2024] [Indexed: 02/23/2024] Open
Abstract
The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
| | - Elina T Ziukelis
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Swann
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Coco Newton
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Paresh Malhotra
- Department of Brain Sciences, Imperial College, London W12 0NN, UK
| | - Ivan Koychev
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - Clare Mackay
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Brian Lawlor
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Lorina Naci
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Katie Wells
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Karen Ritchie
- Institut National de la Santé et de la Recherche Médicale, U1061 Neuropsychiatrie, Montpellier 34093, France
- Faculty of Medicine, University of Montpellier, Montpellier 34093, France
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - John T O’Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
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Silva-Rudberg JA, Salardini E, O'Dell RS, Chen MK, Ra J, Georgelos JK, Morehouse MR, Melino KP, Varma P, Toyonaga T, Nabulsi NB, Huang Y, Carson RE, van Dyck CH, Mecca AP. Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET. Am J Geriatr Psychiatry 2024; 32:17-28. [PMID: 37673749 PMCID: PMC10840732 DOI: 10.1016/j.jagp.2023.08.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/19/2023] [Accepted: 08/05/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVE Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.
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Affiliation(s)
- Jason A Silva-Rudberg
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT.
| | - Elaheh Salardini
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Ryan S O'Dell
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Ming-Kai Chen
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Jocelyn Ra
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Jamie K Georgelos
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Mackenzie R Morehouse
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Kaitlyn P Melino
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Pradeep Varma
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Takuya Toyonaga
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Nabeel B Nabulsi
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Yiyun Huang
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Christopher H van Dyck
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Neuroscience (CHvD), Yale University School of Medicine, New Haven, CT; Department of Neurology (CHvD), Yale University School of Medicine, New Haven, CT
| | - Adam P Mecca
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT.
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10
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Fide E, Yerlikaya D, Güntekin B, Babiloni C, Yener GG. Coherence in event-related EEG oscillations in patients with Alzheimer's disease dementia and amnestic mild cognitive impairment. Cogn Neurodyn 2023; 17:1621-1635. [PMID: 37974589 PMCID: PMC10640558 DOI: 10.1007/s11571-022-09920-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 11/02/2022] [Accepted: 12/05/2022] [Indexed: 12/23/2022] Open
Abstract
Objectives Working memory performances are based on brain functional connectivity, so that connectivity may be deranged in individuals with mild cognitive impairment (MCI) and patients with dementia due to Alzheimer's disease (ADD). Here we tested the hypothesis of abnormal functional connectivity as revealed by the imaginary part of coherency (ICoh) at electrode pairs from event-related electroencephalographic oscillations in ADD and MCI patients. Methods The study included 43 individuals with MCI, 43 with ADD, and 68 demographically matched healthy controls (HC). Delta, theta, alpha, beta, and gamma bands event-related ICoh was measured during an oddball paradigm. Inter-hemispheric, midline, and intra-hemispheric ICoh values were compared in ADD, MCI, and HC groups. Results The main results of the present study can be summarized as follows: (1) A significant increase of midline frontal and temporal theta coherence in the MCI group as compared to the HC group; (2) A significant decrease of theta, delta, and alpha intra-hemispheric coherence in the ADD group as compared to the HC and MCI groups; (3) A significant decrease of theta midline coherence in the ADD group as compared to the HC and MCI groups; (4) Normal inter-hemispheric coherence in the ADD and MCI groups. Conclusions Compared with the MCI and HC, the ADD group showed disrupted event-related intra-hemispheric and midline low-frequency band coherence as an estimate of brain functional dysconnectivity underlying disabilities in daily living. Brain functional connectivity during attention and short memory demands is relatively resilient in elderly subjects even with MCI (with preserved abilities in daily activities), and it shows reduced efficiency at multiple operating oscillatory frequencies only at an early stage of ADD. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09920-0.
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Affiliation(s)
- Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Deniz Yerlikaya
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
- REMER Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, Sapienza University of Rome, Rome, Italy
- Hospital San Raffaele of Cassino, Cassino, Italy
| | - Görsev G. Yener
- Faculty of Medicine, Izmir University of Economics, 35330 Izmir, Turkey
- Brain Dynamics Multidisciplinary Research Center, Dokuz Eylul University, Izmir, Turkey
- Izmir Biomedicine and Genome Center, Izmir, Turkey
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11
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Torso M, Ridgway GR, Valotti M, Hardingham I, Chance SA. In vivo cortical diffusion imaging relates to Alzheimer's disease neuropathology. Alzheimers Res Ther 2023; 15:165. [PMID: 37794477 PMCID: PMC10548768 DOI: 10.1186/s13195-023-01309-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 09/17/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND There has been increasing interest in cortical microstructure as a complementary and earlier measure of neurodegeneration than macrostructural atrophy, but few papers have related cortical diffusion imaging to post-mortem neuropathology. This study aimed to characterise the associations between the main Alzheimer's disease (AD) neuropathological hallmarks and multiple cortical microstructural measures from in vivo diffusion MRI. Comorbidities and co-pathologies were also investigated. METHODS Forty-three autopsy cases (8 cognitively normal, 9 mild cognitive impairment, 26 AD) from the National Alzheimer's Coordinating Center and Alzheimer's Disease Neuroimaging Initiative databases were included. Structural and diffusion MRI scans were analysed to calculate cortical minicolumn-related measures (AngleR, PerpPD+, and ParlPD) and mean diffusivity (MD). Neuropathological hallmarks comprised Thal phase, Braak stage, neuritic plaques, and combined AD neuropathological changes (ADNC-the "ABC score" from NIA-AA recommendations). Regarding comorbidities, relationships between cortical microstructure and severity of white matter rarefaction (WMr), cerebral amyloid angiopathy (CAA), atherosclerosis of the circle of Willis (ACW), and locus coeruleus hypopigmentation (LCh) were investigated. Finally, the effect of coexistent pathologies-Lewy body disease and TAR DNA-binding protein 43 (TDP-43)-on cortical microstructure was assessed. RESULTS Cortical diffusivity measures were significantly associated with Thal phase, Braak stage, ADNC, and LCh. Thal phase was associated with AngleR in temporal areas, while Braak stage was associated with PerpPD+ in a wide cortical pattern, involving mainly temporal and limbic areas. A similar association was found between ADNC (ABC score) and PerpPD+. LCh was associated with PerpPD+, ParlPD, and MD. Co-existent neuropathologies of Lewy body disease and TDP-43 exhibited significantly reduced AngleR and MD compared to ADNC cases without co-pathology. CONCLUSIONS Cortical microstructural diffusion MRI is sensitive to AD neuropathology. The associations with the LCh suggest that cortical diffusion measures may indirectly reflect the severity of locus coeruleus neuron loss, perhaps mediated by the severity of microglial activation and tau spreading across the brain. Recognizing the impact of co-pathologies is important for diagnostic and therapeutic decision-making. Microstructural markers of neurodegeneration, sensitive to the range of histopathological features of amyloid, tau, and monoamine pathology, offer a more complete picture of cortical changes across AD than conventional structural atrophy.
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12
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Reveley C, Ye FQ, Mars RB, Matrov D, Chudasama Y, Leopold DA. Diffusion MRI anisotropy in the cerebral cortex is determined by unmyelinated tissue features. Nat Commun 2022; 13:6702. [PMID: 36335105 PMCID: PMC9637141 DOI: 10.1038/s41467-022-34328-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/19/2022] [Indexed: 11/07/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) is commonly used to assess the tissue and cellular substructure of the human brain. In the white matter, myelinated axons are the principal neural elements that shape dMRI through the restriction of water diffusion; however, in the gray matter the relative contributions of myelinated axons and other tissue features to dMRI are poorly understood. Here we investigate the determinants of diffusion in the cerebral cortex. Specifically, we ask whether myelinated axons significantly shape dMRI fractional anisotropy (dMRI-FA), a measure commonly used to characterize tissue properties in humans. We compared ultra-high resolution ex vivo dMRI data from the brain of a marmoset monkey with both myelin- and Nissl-stained histological sections obtained from the same brain after scanning. We found that the dMRI-FA did not match the spatial distribution of myelin in the gray matter. Instead dMRI-FA was more closely related to the anisotropy of stained tissue features, most prominently those revealed by Nissl staining and to a lesser extent those revealed by myelin staining. Our results suggest that unmyelinated neurites such as large caliber apical dendrites are the primary features shaping dMRI measures in the cerebral cortex.
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Affiliation(s)
- Colin Reveley
- grid.4991.50000 0004 1936 8948Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU UK ,grid.12082.390000 0004 1936 7590Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QJ UK
| | - Frank Q. Ye
- grid.94365.3d0000 0001 2297 5165Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD USA
| | - Rogier B. Mars
- grid.4991.50000 0004 1936 8948Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU UK ,grid.5590.90000000122931605Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Denis Matrov
- grid.94365.3d0000 0001 2297 5165Section on Behavioral Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Yogita Chudasama
- grid.94365.3d0000 0001 2297 5165Section on Behavioral Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - David A. Leopold
- grid.94365.3d0000 0001 2297 5165Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD USA ,grid.94365.3d0000 0001 2297 5165Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD USA
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13
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Maharjan S, Tsai AP, Lin PB, Ingraham C, Jewett MR, Landreth GE, Oblak AL, Wang N. Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging. Front Neurosci 2022; 16:964654. [PMID: 36061588 PMCID: PMC9428354 DOI: 10.3389/fnins.2022.964654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 07/18/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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Affiliation(s)
- Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Peter B. Lin
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Cynthia Ingraham
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Megan R. Jewett
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- Department of Anatomy, Cell Biology and Physiology, Indiana University, Indianapolis, IN, United States
| | - Adrian L. Oblak
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- *Correspondence: Nian Wang,
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14
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Patel R, Mackay CE, Jansen MG, Devenyi GA, O'Donoghue MC, Kivimäki M, Singh-Manoux A, Zsoldos E, Ebmeier KP, Chakravarty MM, Suri S. Inter- and intra-individual variation in brain structural-cognition relationships in aging. Neuroimage 2022; 257:119254. [PMID: 35490915 PMCID: PMC9393406 DOI: 10.1016/j.neuroimage.2022.119254] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/14/2022] [Accepted: 04/16/2022] [Indexed: 01/21/2023] Open
Abstract
The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.
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Affiliation(s)
- Raihaan Patel
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada
| | - Clare E Mackay
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - Michelle G Jansen
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Gabriel A Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Montréal, Québec, H3A 1A1, Canada
| | - M Clare O'Donoghue
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, WC1E 6BT, London, United Kingdom
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, WC1E 6BT, London, United Kingdom; Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, 7501020, Paris, France
| | - Enikő Zsoldos
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Functional MRI of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 9DU, Oxford, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - M Mallar Chakravarty
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada; Department of Psychiatry, McGill University, Montréal, Québec, H3A 1A1, Canada
| | - Sana Suri
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom.
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15
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Luo YQ, Liang RB, Xu SH, Pan YC, Li QY, Shu HY, Kang M, Yin P, Zhang LJ, Shao Y. Altered regional brain white matter in dry eye patients: a brain imaging study. Aging (Albany NY) 2022; 14:2805-2818. [PMID: 35332110 PMCID: PMC9004581 DOI: 10.18632/aging.203976] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 03/15/2022] [Indexed: 12/03/2022]
Abstract
This study aimed to investigate the regional changes of brain white matter (WM) in DE patients using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). A total of 25 dry eye patients (PAT) and 25 healthy controls (HC) were recruited. All subjects underwent DTI and NODDI, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (FISO), intra-cellular volume fraction (FICVF), and orientation dispersion index (ODI) were obtained respectively. Then complete Hospital Anxiety and Depression Scale (HADS), anxiety score (AS) or depression scores (DS) were obtained. Receiver operating characteristic (ROC) curve analysis was used to evaluate the reliability of DTI and NODDI in distinguishing the two groups. DTI revealed that PAT had lower FA in both the left superior longitudinal fasciculus (LSLF) and the corpus callosum (CC), and higher MD in the LSLF, the right posterior limb of the internal capsule and the right posterior thalamic radiation. PAT had significant AD changes in regions including the genu of the CC, the right posterior limb of internal capsule, and the right splenium of the CC. From NODDI, PAT showed increased ODI in the LSLF and increased FISO in the right splenium of the CC. FICVF showed a significant decrease in the LSLF while increased in the left anterior corona radiata and the CC. Furthermore, the average values of MD and FICVF were significantly correlated with DS and AS. Hence the results of this study suggest that there are regional changes in WM in DE patients which may contribute to further understanding of the pathological mechanism of DE.
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Affiliation(s)
- Yun-Qing Luo
- Department of Ophthalmology, The Second Affiliated Hospital of Nanchang University, Jiangxi Province Ocular Disease Clinical Research Center, Nanchang 330006, Jiangxi, PR China
| | - Rong-Bin Liang
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - San-Hua Xu
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Yi-Cong Pan
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Qiu-Yu Li
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Hui-Ye Shu
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Min Kang
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Pin Yin
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Li-Juan Zhang
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
| | - Yi Shao
- Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi, PR China
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16
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Torso M, Ridgway GR, Jenkinson M, Chance S. Intracortical diffusion tensor imaging signature of microstructural changes in frontotemporal lobar degeneration. Alzheimers Res Ther 2021; 13:180. [PMID: 34686217 PMCID: PMC8539736 DOI: 10.1186/s13195-021-00914-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 10/05/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND Frontotemporal lobar degeneration (FTLD) is a neuropathological construct with multiple clinical presentations, including the behavioural variant of frontotemporal dementia (bvFTD), primary progressive aphasia-both non-fluent variant (nfvPPA) and semantic variant (svPPA)-progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), characterised by the deposition of abnormal tau protein in the brain. A major challenge for treating FTLD is early diagnosis and accurate discrimination among different syndromes. The main goal here was to investigate the cortical architecture of FTLD syndromes using cortical diffusion tensor imaging (DTI) analysis and to test its power to discriminate between different clinical presentations. METHODS A total of 271 individuals were included in the study: 87 healthy subjects (HS), 31 semantic variant primary progressive aphasia (svPPA), 37 behavioural variant (bvFTD), 30 non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), 47 PSP Richardson's syndrome (PSP-RS) and 39 CBS cases. 3T MRI T1-weighted images and DTI scans were analysed to extract three cortical DTI derived measures (AngleR, PerpPD and ParlPD) and mean diffusivity (MD), as well as standard volumetric measurements. Whole brain and regional data were extracted. Linear discriminant analysis was used to assess the group discrimination capability of volumetric and DTI measures to differentiate the FTLD syndromes. In addition, in order to further investigate differential diagnosis in CBS and PSP-RS, a subgroup of subjects with autopsy confirmation in the training cohort was used to select features which were then tested in the test cohort. Three different challenges were explored: a binary classification (controls vs all patients), a multiclass classification (HS vs bvFTD vs svPPA vs nfvPPA vs CBS vs PSP-RS) and an additional binary classification to differentiate CBS and PSP-RS using features selected in an autopsy confirmed subcohort. RESULTS Linear discriminant analysis revealed that PerpPD was the best feature to distinguish between controls and all patients (ACC 86%). PerpPD regional values were able to classify correctly the different FTLD syndromes with an accuracy of 85.6%. The PerpPD and volumetric values selected to differentiate CBS and PSP-RS patients showed a classification accuracy of 85.2%. CONCLUSIONS (I) PerpPD achieved the highest classification power for differentiating healthy controls and FTLD syndromes and FTLD syndromes among themselves. (II) PerpPD regional values could provide an additional marker to differentiate FTD, PSP-RS and CBS.
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Affiliation(s)
- Mario Torso
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK.
- Oxford Brain Diagnostics Limited, Oxford, UK.
| | | | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Steven Chance
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- Oxford Brain Diagnostics Limited, Oxford, UK
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17
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Callow DD, Won J, Pena GS, Jordan LS, Arnold-Nedimala NA, Kommula Y, Nielson KA, Smith JC. Exercise Training-Related Changes in Cortical Gray Matter Diffusivity and Cognitive Function in Mild Cognitive Impairment and Healthy Older Adults. Front Aging Neurosci 2021; 13:645258. [PMID: 33897407 PMCID: PMC8060483 DOI: 10.3389/fnagi.2021.645258] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/15/2021] [Indexed: 12/12/2022] Open
Abstract
Individuals with Mild Cognitive Impairment (MCI) are at an elevated risk of dementia and exhibit deficits in cognition and cortical gray matter (GM) volume, thickness, and microstructure. Meanwhile, exercise training appears to preserve brain function and macrostructure may help delay or prevent the onset of dementia in individuals with MCI. Yet, our understanding of the neurophysiological effects of exercise training in individuals with MCI remains limited. Recent work suggests that the measures of gray matter microstructure using diffusion imaging may be sensitive to early cognitive and neurophysiological changes in the aging brain. Therefore, this study is aimed to determine the effects of exercise training in cognition and cortical gray matter microstructure in individuals with MCI vs. cognitively healthy older adults. Fifteen MCI participants and 17 cognitively intact controls (HC) volunteered for a 12-week supervised walking intervention. Following the intervention, MCI and HC saw improvements in cardiorespiratory fitness, performance on Trial 1 of the Rey Auditory Verbal Learning Test (RAVLT), a measure of verbal memory, and the Controlled Oral Word Association Test (COWAT), a measure of verbal fluency. After controlling for age, a voxel-wise analysis of cortical gray matter diffusivity showed individuals with MCI exhibited greater increases in mean diffusivity (MD) in the left insular cortex than HC. This increase in MD was positively associated with improvements in COWAT performance. Additionally, after controlling for age, the voxel-wise analysis indicated a main effect of Time with both groups experiencing an increase in left insular and left and right cerebellar MD. Increases in left insular diffusivity were similarly found to be positively associated with improvements in COWAT performance in both groups, while increases in cerebellar MD were related to gains in episodic memory performance. These findings suggest that exercise training may be related to improvements in neural circuits that govern verbal fluency performance in older adults through the microstructural remodeling of cortical gray matter. Furthermore, changes in left insular cortex microstructure may be particularly relevant to improvements in verbal fluency among individuals diagnosed with MCI.
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Affiliation(s)
- Daniel D Callow
- Department of Kinesiology, University of Maryland, College Park, MD, United States.,Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, United States
| | - Junyeon Won
- Department of Kinesiology, University of Maryland, College Park, MD, United States
| | - Gabriel S Pena
- Department of Kinesiology, University of Maryland, College Park, MD, United States
| | - Leslie S Jordan
- Department of Kinesiology, University of Maryland, College Park, MD, United States.,Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, United States
| | | | - Yash Kommula
- Department of Kinesiology, University of Maryland, College Park, MD, United States.,Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, United States
| | - Kristy A Nielson
- Department of Psychology, Marquette University, Milwaukee, WI, United States.,Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - J Carson Smith
- Department of Kinesiology, University of Maryland, College Park, MD, United States.,Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, United States
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18
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Cabeen RP, Toga AW, Allman JM. Frontoinsular cortical microstructure is linked to life satisfaction in young adulthood. Brain Imaging Behav 2021; 15:2775-2789. [PMID: 33825124 DOI: 10.1007/s11682-021-00467-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/01/2021] [Indexed: 10/21/2022]
Abstract
Life satisfaction is a component of subjective well-being that reflects a global judgement of the quality of life according to an individual's own needs and expectations. As a psychological construct, it has attracted attention due to its relationship to mental health, resilience to stress, and other factors. Neuroimaging studies have identified neurobiological correlates of life satisfaction; however, they are limited to functional connectivity and gray matter morphometry. We explored features of gray matter microstructure obtained through compartmental modeling of multi-shell diffusion MRI data, and we examined cortical microstructure in frontoinsular cortex in a cohort of 807 typical young adults scanned as part of the Human Connectome Project. Our experiments identified the orientation dispersion index (ODI), and analogously fractional anisotropy (FA), of frontoinsular cortex as a robust set of anatomically-specific lateralized diffusion MRI microstructure features that are linked to life satisfaction, independent of other demographic, socioeconomic, and behavioral factors. We further validated our findings in a secondary test-retest dataset and found high reliability of our imaging metrics and reproducibility of outcomes. In our analysis of twin and non-twin siblings, we found basic microstructure in frontoinsular cortex to be strongly genetically determined. We also found a more moderate but still very significant genetic role in determining microstructure as it relates to life satisfaction in frontoinsular cortex. Our findings suggest a potential linkage between well-being and microscopic features of frontoinsular cortex, which may reflect cellular morphology and architecture and may more broadly implicate the integrity of the homeostatic processing performed by frontoinsular cortex as an important component of an individual's judgements of life satisfaction.
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Affiliation(s)
- Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - John M Allman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
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19
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Rodriguez-Vieitez E, Montal V, Sepulcre J, Lois C, Hanseeuw B, Vilaplana E, Schultz AP, Properzi MJ, Scott MR, Amariglio R, Papp KV, Marshall GA, Fortea J, Johnson KA, Sperling RA, Vannini P. Association of cortical microstructure with amyloid-β and tau: impact on cognitive decline, neurodegeneration, and clinical progression in older adults. Mol Psychiatry 2021; 26:7813-7822. [PMID: 34588623 PMCID: PMC8873001 DOI: 10.1038/s41380-021-01290-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 08/16/2021] [Accepted: 09/03/2021] [Indexed: 02/07/2023]
Abstract
Noninvasive biomarkers of early neuronal injury may help identify cognitively normal individuals at risk of developing Alzheimer's disease (AD). A recent diffusion-weighted imaging (DWI) method allows assessing cortical microstructure via cortical mean diffusivity (cMD), suggested to be more sensitive than macrostructural neurodegeneration. Here, we aimed to investigate the association of cMD with amyloid-β and tau pathology in older adults, and whether cMD predicts longitudinal cognitive decline, neurodegeneration and clinical progression. The study sample comprised n = 196 cognitively normal older adults (mean[SD] 72.5 [9.4] years; 114 women [58.2%]) from the Harvard Aging Brain Study. At baseline, all participants underwent structural MRI, DWI, 11C-Pittsburgh compound-B-PET, 18F-flortaucipir-PET imaging, and cognitive assessments. Longitudinal measures of Preclinical Alzheimer Cognitive Composite-5 were available for n = 186 individuals over 3.72 (1.96)-year follow-up. Prospective clinical follow-up was available for n = 163 individuals over 3.2 (1.7) years. Surface-based image analysis assessed vertex-wise relationships between cMD, global amyloid-β, and entorhinal and inferior-temporal tau. Multivariable regression, mixed effects models and Cox proportional hazards regression assessed longitudinal cognition, brain structural changes and clinical progression. Tau, but not amyloid-β, was positively associated with cMD in AD-vulnerable regions. Correcting for baseline demographics and cognition, increased cMD predicted steeper cognitive decline, which remained significant after correcting for amyloid-β, thickness, and entorhinal tau; there was a synergistic interaction between cMD and both amyloid-β and tau on cognitive slope. Regional cMD predicted hippocampal atrophy rate, independently from amyloid-β, tau, and thickness. Elevated cMD predicted progression to mild cognitive impairment. Cortical microstructure is a noninvasive biomarker that independently predicts subsequent cognitive decline, neurodegeneration and clinical progression, suggesting utility in clinical trials.
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Affiliation(s)
- Elena Rodriguez-Vieitez
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.4714.60000 0004 1937 0626Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Victor Montal
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jorge Sepulcre
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Cristina Lois
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Bernard Hanseeuw
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA ,grid.7942.80000 0001 2294 713XSaint Luc University Hospital, Université Catholique de Louvain, Brussels, Belgium
| | - Eduard Vilaplana
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Aaron P. Schultz
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA
| | - Michael J. Properzi
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA
| | - Matthew R. Scott
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA
| | - Rebecca Amariglio
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Kathryn V. Papp
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Gad A. Marshall
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Juan Fortea
- grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Keith A. Johnson
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.512020.4Gordon Center for Medical Imaging, Boston, MA USA
| | - Reisa A. Sperling
- grid.38142.3c000000041936754XMassachusetts General Hospital, Harvard Medical School, Boston, MA USA ,grid.509504.d0000 0004 0475 2664Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA USA ,grid.38142.3c000000041936754XBrigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Patrizia Vannini
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA. .,Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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