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Wagstyl K, Adler S, Seidlitz J, Vandekar S, Mallard TT, Dear R, DeCasien AR, Satterthwaite TD, Liu S, Vértes PE, Shinohara RT, Alexander-Bloch A, Geschwind DH, Raznahan A. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 2024; 12:RP86933. [PMID: 38324465 PMCID: PMC10945526 DOI: 10.7554/elife.86933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
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Affiliation(s)
- Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Sophie Adler
- UCL Great Ormond Street Institute for Child HealthHolbornUnited Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt UniversityNashvilleUnited States
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General HospitalBostonUnited States
- Department of Psychiatry, Harvard Medical SchoolBostonUnited States
| | - Richard Dear
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Alex R DeCasien
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of MedicinePhiladelphiaUnited States
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Petra E Vértes
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
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Graham NS, Cole JH, Bourke NJ, Schott JM, Sharp DJ. Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease. Alzheimers Dement 2023; 19:3065-3077. [PMID: 36696255 PMCID: PMC10955776 DOI: 10.1002/alz.12934] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Traumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI. METHODS A total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared. RESULTS AD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD. DISCUSSION Post-traumatic neurodegeneration 1.9-4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger. HIGHLIGHTS We compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging. Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging. This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration.
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Affiliation(s)
- Neil S.N. Graham
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
| | - James H. Cole
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
- Centre for Medical Image ComputingUCLLondonUK
| | - Niall J. Bourke
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
| | | | - David J. Sharp
- Department of Brain SciencesImperial College LondonLondonUK
- UK Dementia Research Institute Centre for Care Research and Technology at Imperial College LondonLondonUK
- Centre for Injury StudiesImperial College LondonLondonUK
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3
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Sauty B, Durrleman S. Impact of sex and APOE- ε4 genotype on patterns of regional brain atrophy in Alzheimer's disease and healthy aging. Front Neurol 2023; 14:1161527. [PMID: 37333001 PMCID: PMC10272760 DOI: 10.3389/fneur.2023.1161527] [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: 02/08/2023] [Accepted: 05/19/2023] [Indexed: 06/20/2023] Open
Abstract
Alzheimer's Disease (AD) is a heterogeneous disease that disproportionately affects women and people with the APOE-ε4 susceptibility gene. We aim to describe the not-well-understood influence of both risk factors on the dynamics of brain atrophy in AD and healthy aging. Regional cortical thinning and brain atrophy were modeled over time using non-linear mixed-effect models and the FreeSurfer software with t1-MRI scans from the Alzheimer's Disease Neuroimaging Initiative (N = 1,502 subjects, 6,728 images in total). Covariance analysis was used to disentangle the effect of sex and APOE genotype on the regional onset age and pace of atrophy, while correcting for educational level. A map of the regions mostly affected by neurodegeneration is provided. Results were confirmed on gray matter density data from the SPM software. Women experience faster atrophic rates in the temporal, frontal, parietal lobes and limbic system and earlier onset in the amygdalas, but slightly later onset in the postcentral and cingulate gyri as well as all regions of the basal ganglia and thalamus. APOE-ε4 genotypes leads to earlier and faster atrophy in the temporal, frontal, parietal lobes, and limbic system in AD patients, but not in healthy patients. Higher education was found to slightly delay atrophy in healthy patients, but not for AD patients. A cohort of amyloid positive patients with MCI showed a similar impact of sex as in the healthy cohort, while APOE-ε4 showed similar associations as in the AD cohort. Female sex is as strong a risk factor for AD as APOE-ε4 genotype regarding neurodegeneration. Women experience a sharper atrophy in the later stages of the disease, although not a significantly earlier onset. These findings may have important implications for the development of targeted intervention.
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4
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Saeed U, Desmarais P, Masellis M. The APOE ε4 variant and hippocampal atrophy in Alzheimer's disease and Lewy body dementia: a systematic review of magnetic resonance imaging studies and therapeutic relevance. Expert Rev Neurother 2021; 21:851-870. [PMID: 34311631 DOI: 10.1080/14737175.2021.1956904] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Introduction: The apolipoprotein E ɛ4-allele (APOE-ɛ4) increases the risk not only for Alzheimer's disease (AD) but also for Parkinson's disease dementia and dementia with Lewy bodies (collectively, Lewy body dementia [LBD]). Hippocampal volume is an important neuroimaging biomarker for AD and LBD, although its association with APOE-ɛ4 is inconsistently reported. We investigated the association of APOE-ε4 with hippocampal atrophy quantified using magnetic resonance imaging in AD and LBD.Areas covered: Databases were searched for volumetric and voxel-based morphometric studies published up until December 31st, 2020. Thirty-nine studies (25 cross-sectional, 14 longitudinal) were included. We observed that (1) APOE-ε4 was associated with greater rate of hippocampal atrophy in longitudinal studies in AD and in those who progressed from mild cognitive impairment to AD, (2) association of APOE-ε4 with hippocampal atrophy in cross-sectional studies was inconsistent, (3) APOE-ɛ4 may influence hippocampal atrophy in dementia with Lewy bodies, although longitudinal investigations are needed. We comprehensively discussed methodological aspects, APOE-based therapeutic approaches, and the association of APOE-ε4 with hippocampal sub-regions and cognitive performance.Expert opinion: The role of APOE-ɛ4 in modulating hippocampal phenotypes may be further clarified through more homogenous, well-powered, and pathology-proven, longitudinal investigations. Understanding the underlying mechanisms will facilitate the development of prevention strategies targeting APOE-ɛ4.
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Affiliation(s)
- Usman Saeed
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
| | - Philippe Desmarais
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
| | - Mario Masellis
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada.,Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada.,Cognitive and Movement Disorders Clinic, Sunnybrook Health Sciences Centre, Toronto, Canada
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5
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Piersson AD, Mohamad M, Suppiah S, Rajab NF. Topographical patterns of whole-brain structural alterations in association with genetic risk, cerebrospinal fluid, positron emission tomography biomarkers of Alzheimer’s disease, and neuropsychological measures. Clin Transl Imaging 2021. [DOI: 10.1007/s40336-021-00440-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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6
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Zhao L, Batta I, Matloff W, O'Driscoll C, Hobel S, Toga AW. Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies. Neuroinformatics 2021; 19:285-303. [PMID: 32822005 DOI: 10.1007/s12021-020-09486-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Large-scale, case-control genome-wide association studies (GWASs) have revealed genetic variations associated with diverse neurological and psychiatric disorders. Recent advances in neuroimaging and genomic databases of large healthy and diseased cohorts have empowered studies to characterize effects of the discovered genetic factors on brain structure and function, implicating neural pathways and genetic mechanisms in the underlying biology. However, the unprecedented scale and complexity of the imaging and genomic data requires new advanced biomedical data science tools to manage, process and analyze the data. In this work, we introduce Neuroimaging PheWAS (phenome-wide association study): a web-based system for searching over a wide variety of brain-wide imaging phenotypes to discover true system-level gene-brain relationships using a unified genotype-to-phenotype strategy. This design features a user-friendly graphical user interface (GUI) for anonymous data uploading, study definition and management, and interactive result visualizations as well as a cloud-based computational infrastructure and multiple state-of-art methods for statistical association analysis and multiple comparison correction. We demonstrated the potential of Neuroimaging PheWAS with a case study analyzing the influences of the apolipoprotein E (APOE) gene on various brain morphological properties across the brain in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Benchmark tests were performed to evaluate the system's performance using data from UK Biobank. The Neuroimaging PheWAS system is freely available. It simplifies the execution of PheWAS on neuroimaging data and provides an opportunity for imaging genetics studies to elucidate routes at play for specific genetic variants on diseases in the context of detailed imaging phenotypic data.
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Affiliation(s)
- Lu Zhao
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Ishaan Batta
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - William Matloff
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Caroline O'Driscoll
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Samuel Hobel
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA.
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Sintini I, Graff-Radford J, Senjem ML, Schwarz CG, Machulda MM, Martin PR, Jones DT, Boeve BF, Knopman DS, Kantarci K, Petersen RC, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Longitudinal neuroimaging biomarkers differ across Alzheimer's disease phenotypes. Brain 2020; 143:2281-2294. [PMID: 32572464 DOI: 10.1093/brain/awaa155] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 03/11/2020] [Accepted: 03/27/2020] [Indexed: 11/12/2022] Open
Abstract
Alzheimer's disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer's disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer's disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer's disease (18 with typical amnestic Alzheimer's disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer's disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer's disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer's disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer's disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer's disease.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, 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
| | | | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester MN, USA
| | - Peter R Martin
- Department of Health Science Research, Mayo Clinic, Rochester MN, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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8
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Abushakra S, Porsteinsson AP, Sabbagh M, Bracoud L, Schaerer J, Power A, Hey JA, Scott D, Suhy J, Tolar M. APOE ε4/ε4 homozygotes with early Alzheimer's disease show accelerated hippocampal atrophy and cortical thinning that correlates with cognitive decline. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12117. [PMID: 33304988 PMCID: PMC7716452 DOI: 10.1002/trc2.12117] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 10/26/2020] [Indexed: 01/06/2023]
Abstract
INTRODUCTION Hippocampal volume (HV) and cortical thickness are commonly used imaging biomarkers in Alzheimer's disease (AD) trials, and may have utility as selection criteria for enrichment strategies. Atrophy rates of these measures, in the high-risk apolipoprotein E (APOE) ε4/ε4 homozygous AD subjects are unknown. METHODS Data from Alzheimer's Disease Neuroimaging Initiative (ADNI-1) and a tramiprosate trial were analyzed in APOE ε4/ε4 and APOE ε3/ε3 subjects with mild cognitive impairment (MCI) or mild AD. Magnetic resonance imaging (MRI) data were centrally processed using FreeSurfer; total HV and composite average cortical thickness were derived and adjusted for age, head size, and education. Volumetric changes from baseline were assessed using Boundary Shift Integral, and correlated with cognitive changes. RESULTS APOE ε4/ε4 MCI subjects showed significantly higher % HV atrophy and cortical thinning at 12 months (4.4%, 3.1%, n = 29) compared to APOE ε3/ε3 subjects (2.8%, 1.8%, n = 93) and similarly in mild AD (7.4%, 4.7% n = 21 vs 5.4%, 3.3% n = 29). Differences were all significant at 24 months. Over 24 months, HV atrophy and cortical thinning correlated significantly with Alzheimer's Disease Assessment Scale-Cognitive subscale worsening in APOE ε4/ε4 MCI subjects, but not in mild AD. DISCUSSION Correlation of volumetric measures to cognitive change in APOE ε4/ε4 subjects with early AD supports their role as efficacy biomarkers. If confirmed in a Phase 3 trial with ALZ-801 (pro-drug of tramiprosate) in APOE ε4/ε4 early AD subjects, it may allow their use as surrogate outcomes in future treatment or prevention trials in AD.
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Affiliation(s)
| | - Anton P. Porsteinsson
- Alzheimer's Disease CareResearch and Education ProgramUniversity of RochesterRochesterNew YorkUSA
| | - Marwan Sabbagh
- Cleveland Clinic Lou Ruvo Center for Brain Health & University of NevadaLas VegasNevadaUSA
| | | | | | | | | | | | - Joyce Suhy
- BioclinicaLyonFrance
- BioclinicaNewarkCaliforniaUSA
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9
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Kang DW, Lim HK, Joo SH, Lee NR, Lee CU. Differential Associations Between Volumes of Atrophic Cortical Brain Regions and Memory Performances in Early and Late Mild Cognitive Impairment. Front Aging Neurosci 2019; 11:245. [PMID: 31551759 PMCID: PMC6738351 DOI: 10.3389/fnagi.2019.00245] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 08/20/2019] [Indexed: 11/13/2022] Open
Abstract
Background Early and late mild cognitive impairment (MCI) patients have been reported to have a distinctive prognosis of converting to Alzheimer’s disease. Objective To evaluate the difference in gray matter volume and assess the association between cognitive function evaluated by comprehensive cognitive function test, and cortical thickness across healthy controls (HCs) (n = 37), early (n = 30), and late MCI patients (n = 35). Methods Differences in gray matter volume were evaluated by whole brain voxel-based morphometry across the groups. Multiple regression analysis was used to analyze group by memory performance interactions for the normalized gray matter volume. Results The early MCI group showed reduced gray matter volume in the right middle temporal gyrus in comparison to the HC group. The late MCI group displayed atrophy in the left parahippocampal gyrus in comparison to the HC group. Late MCI patients exhibited a decreased gray matter volume in the left fusiform gyrus in comparison to patients in the early MCI group (Monte Carlo simulation corrected p < 0.01, Tukey post hoc tests). Furthermore, there was a significant group (HC vs. early MCI) by memory performance interaction for the normalized cortical volume of the right middle temporal gyrus. Additionally, a significant group (early MCI vs. late MCI) by memory performance interaction was found for the normalized gray matter volume of the left fusiform gyrus (p < 0.001). Conclusion Early and late MCI patients showed distinctive associations of gray matter volumes in compensatory brain regions with memory performances. The findings can contribute to a better understanding of the structural changes in compensatory brain regions to elucidate memory decline in the trajectory of the subdivided prodromal stages of the Alzheimer’s disease (AD).
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Affiliation(s)
- Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Soo-Hyun Joo
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Na Rae Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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Marizzoni M, Ferrari C, Jovicich J, Albani D, Babiloni C, Cavaliere L, Didic M, Forloni G, Galluzzi S, Hoffmann KT, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Ribaldi F, Rossini PM, Schönknecht P, Salvatore M, Soricelli A, Hensch T, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. Predicting and Tracking Short Term Disease Progression in Amnestic Mild Cognitive Impairment Patients with Prodromal Alzheimer’s Disease: Structural Brain Biomarkers. J Alzheimers Dis 2019; 69:3-14. [DOI: 10.3233/jad-180152] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Italy
| | - Diego Albani
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- IRCCS San Raffaele Pisana of Rome, Rome, Italy
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix-Marseille Université, Inserm, INS UMR_S 1106, Marseille, France
- APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
| | | | - José Luis Molinuevo
- Alzheimer’s Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, and Institut d’Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Clinical Neurology, Dept. of Neuroscience (DINOGMI), University of Genoa and IRCCS AOU SanMartino-IST, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Mariadella Misericordia, Perugia, Italy
| | - Pierre Payoux
- INSERM; Imagerie cérébrale et handicapsneurologiques UMR 825, Toulouse, France
| | - Federica Ribaldi
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Paolo Maria Rossini
- Area of Neuroscience, Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Policlinic A. Gemelli Foundation Rome, Italy
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Marco Salvatore
- SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | | | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Magda Tsolaki
- 3rd Neurologic Clinic, Medical School, G. Papanikolaou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, The Netherlands
| | - Jens Wiltfang
- LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, Portugal
| | - Jill C. Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | - Régis Bordet
- University of Lille, Inserm, CHU Lille, U1171 - Degenerative and vascular cognitive disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-CNRS 7289, Service de Pharmacologie Clinique, AP-HM, Marseille, France
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging and Alzheimer’s Epidemiology, IRCCS Istituto Centro San Giovanni diDio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
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The Contribution of Genetic Factors to Cognitive Impairment and Dementia: Apolipoprotein E Gene, Gene Interactions, and Polygenic Risk. Int J Mol Sci 2019; 20:ijms20051177. [PMID: 30866553 PMCID: PMC6429136 DOI: 10.3390/ijms20051177] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 02/26/2019] [Indexed: 12/19/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease. Although it has been studied for years, the pathogenesis of AD is still controversial. Genetic factors may play an important role in pathogenesis, with the apolipoprotein E (APOE) gene among the greatest risk factors for AD. In this review, we focus on the influence of genetic factors, including the APOE gene, the interaction between APOE and other genes, and the polygenic risk factors for cognitive function and dementia. The presence of the APOE ε4 allele is associated with increased AD risk and reduced age of AD onset. Accelerated cognitive decline and abnormal internal environment, structure, and function of the brain were also found in ε4 carriers. The effect of the APOE promoter on cognition and the brain was confirmed by some studies, but further investigation is still needed. We also describe the effects of the associations between APOE and other genetic risk factors on cognition and the brain that exhibit a complex gene⁻gene interaction, and we consider the importance of using a polygenic risk score to investigate the association between genetic variance and phenotype.
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Hahn C, Lee CU. A Brief Review of Paradigm Shifts in Prevention of Alzheimer's Disease: From Cognitive Reserve to Precision Medicine. Front Psychiatry 2019; 10:786. [PMID: 31736804 PMCID: PMC6837073 DOI: 10.3389/fpsyt.2019.00786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Accepted: 10/02/2019] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease (AD) and related dementias can be an enormous economic burden for taxpayers, patients, their families, medical systems, and society as a whole. Since disease-modifying treatments have failed, several studies have instead focused on a paradigm shift for preventing and treating AD. A higher cognitive reserve (e.g., greater education, occupational attainment, or more leisure activities) is associated with protection against disease-related cognitive decline. Precision medicine aims to optimize the effectiveness of disease prevention and treatment by considering specific biological components of individuals. We suggest that research into cognitive reserve and precision medicine could be a key to overcoming the limitations of traditional approaches to the prevention and treatment of AD.
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Affiliation(s)
- Changtae Hahn
- Department of Psychiatry, Deajeon Saint Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul Saint Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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Diffusion Tensor Changes According to Age at Onset and Apolipoprotein E Genotype in Alzheimer Disease. Alzheimer Dis Assoc Disord 2017; 30:297-304. [PMID: 27227996 DOI: 10.1097/wad.0000000000000155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Age at onset is one of the most important factors that affects the clinical course in Alzheimer disease (AD), whereas other factors such as apolipoprotein E (apoE) genotype may also play a major role. In this study, we aimed to investigate the effect of age at onset and apoE genotype on white-matter changes in AD using diffusion tensor imaging. About 213 patients with AD and 66 normal individuals underwent diffusion tensor imaging, and apoE genotype was obtained in all AD patients and in 24 normal individuals. When multiple regression analysis was conducted, a younger age at onset was associated with lower fractional anisotropy in both deep-located long-range limbic and association fibers and superficial-located short-range association fibers in the frontal, the temporal, and the parietal lobes, and with a higher mean diffusivity in deep-located fibers and the bilateral medial thalamus. When analyzed separately in apoE e4 carriers and noncarriers, e4 carriers showed an association between a younger age at onset and lower fractional anisotropy, mainly in deep-located fibers, whereas noncarriers showed this association in both deep-located and superficial-located fibers. There was no difference in the spatial distribution between carriers and noncarriers in the association between the age at onset and mean diffusivity. Our results suggest that the topographical distribution of white-matter changes in AD is significantly affected by the interaction between age at onset and apoE genotype.
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Iyappan A, Younesi E, Redolfi A, Vrooman H, Khanna S, Frisoni GB, Hofmann-Apitius M. Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features. J Alzheimers Dis 2017; 59:1153-1169. [PMID: 28731430 PMCID: PMC5611802 DOI: 10.3233/jad-161148] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.
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Affiliation(s)
- Anandhi Iyappan
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany.,Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for Information Technology, Bonn, Germany
| | - Erfan Younesi
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany
| | - Alberto Redolfi
- Laboratory of Epidemiology and Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Henri Vrooman
- Departments of Radiology and Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC University Medical Center, The Netherlands
| | - Shashank Khanna
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany.,Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for Information Technology, Bonn, Germany
| | - Giovanni B Frisoni
- Laboratory of Epidemiology and Neuroimaging, IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and Laboratoire de Neuroimagerie du Vieillissement (LANVIE), University Hospitals and University of Geneva, Geneva, Switzerland
| | - Martin Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Sankt Augustin, Germany.,Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn-Aachen International Center for Information Technology, Bonn, Germany
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Gasca-Salas C, García-Lorenzo D, Garcia-Garcia D, Clavero P, Obeso JA, Lehericy S, Rodríguez-Oroz MC. Parkinson’s disease with mild cognitive impairment: severe cortical thinning antedates dementia. Brain Imaging Behav 2017; 13:180-188. [DOI: 10.1007/s11682-017-9751-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Zajac L, Koo BB, Bauer CM, Killiany R. Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer's Disease. Brain Sci 2017; 7:brainsci7040037. [PMID: 28383490 PMCID: PMC5406694 DOI: 10.3390/brainsci7040037] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Revised: 02/28/2017] [Accepted: 03/31/2017] [Indexed: 01/03/2023] Open
Abstract
Whole-brain networks derived from diffusion tensor imaging (DTI) data require the identification of seed and target regions of interest (ROIs) to assess connectivity patterns. This study investigated how initiating tracts from gray matter (GM) or white matter (WM) seed ROIs impacts (1) structural networks constructed from DTI data from healthy elderly (control) and individuals with Alzheimer’s disease (AD) and (2) between-group comparisons using these networks. DTI datasets were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Deterministic tractography was used to build two whole-brain networks for each subject; one in which tracts were initiated from WM ROIs and another in which they were initiated from GM ROIs. With respect to the first goal, in both groups, WM-seeded networks had approximately 400 more connections and stronger connections (as measured by number of streamlines per connection) than GM-seeded networks, but shared 94% of the connections found in the GM-seed networks. With respect to the second goal, between-group comparisons revealed a stronger subnetwork (as measured by number of streamlines per connection) in controls compared to AD using both WM-seeded and GM-seeded networks. The comparison using WM-seeded networks produced a larger (i.e., a greater number of connections) and more significant subnetwork in controls versus AD. Global, local, and nodal efficiency were greater in controls compared to AD, and between-group comparisons of these measures using WM-seeded networks had larger effect sizes than those using GM-seeded networks. These findings affirm that seed location significantly affects the ability to detect between-group differences in structural networks.
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Affiliation(s)
- Lauren Zajac
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
| | - Bang-Bon Koo
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
| | - Corinna M Bauer
- Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA 02114, USA.
| | - Ron Killiany
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA.
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA.
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Kim J, Pan W. Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations. Genet Epidemiol 2017; 41:259-277. [PMID: 28191669 DOI: 10.1002/gepi.22033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 10/07/2016] [Accepted: 10/31/2016] [Indexed: 12/15/2022]
Abstract
There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n.
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Affiliation(s)
- Junghi Kim
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States of America
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- Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http: //adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf
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18
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The effects of apolipoprotein ε 4 on aging brain in cognitively normal Chinese elderly: a surface-based morphometry study. Int Psychogeriatr 2016; 28:1503-11. [PMID: 27097839 DOI: 10.1017/s1041610216000624] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Default mode network (DMN) has been reported to be susceptible to APOE ε 4 genotype. However, the APOE ε 4-related brain changes in young carriers are different from the ones in elderly carriers. The current study aimed to evaluate the cortical morphometry of DMN subregions in cognitively normal elderly with APOE ε 4. METHOD 11 cognitively normal senior APOE ε 4 carriers and 27 matched healthy controls (HC) participated the neuropsychological tests, genotyping, and magnetic resonance imaging (MRI) scanning. Voxel-based morphometry (VBM) analysis was used to assess the global volumetric changes. Surface-based morphometry (SBM) analysis was performed to measure regional gray matter volume (GMV) and gray matter thickness (GMT). RESULTS Advancing age was associated with decreased GMV of DMN subregions. Compared to HC, APOE ε 4 carriers presented cortical atrophy in right cingulate gyrus (R_CG) (GMV: APOE carriers: 8475.23 ± 1940.73 mm3, HC: 9727.34 ± 1311.57 mm3, t = 2.314, p = 0.026, corrected) and left insular (GMT: APOE ε 4 carriers: 3.83 ± 0.37 mm, HC: 4.05 ± 0.25 mm, t = 2.197, p = 0.033, corrected). CONCLUSIONS Our results highlight the difference between different cortical measures and suggest that the cortical reduction of CG and insular maybe a potential neuroimaging marker for APOE 4 ε senior carriers, even in the context of relatively intact cognition.
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McCarthy CS, Ramprashad A, Thompson C, Botti JA, Coman IL, Kates WR. A comparison of FreeSurfer-generated data with and without manual intervention. Front Neurosci 2015; 9:379. [PMID: 26539075 PMCID: PMC4612506 DOI: 10.3389/fnins.2015.00379] [Citation(s) in RCA: 94] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 09/29/2015] [Indexed: 01/18/2023] Open
Abstract
This paper examined whether FreeSurfer-generated data differed between a fully-automated, unedited pipeline and an edited pipeline that included the application of control points to correct errors in white matter segmentation. In a sample of 30 individuals, we compared the summary statistics of surface area, white matter volumes, and cortical thickness derived from edited and unedited datasets for the 34 regions of interest (ROIs) that FreeSurfer (FS) generates. To determine whether applying control points would alter the detection of significant differences between patient and typical groups, effect sizes between edited and unedited conditions in individuals with the genetic disorder, 22q11.2 deletion syndrome (22q11DS) were compared to neurotypical controls. Analyses were conducted with data that were generated from both a 1.5 tesla and a 3 tesla scanner. For 1.5 tesla data, mean area, volume, and thickness measures did not differ significantly between edited and unedited regions, with the exception of rostral anterior cingulate thickness, lateral orbitofrontal white matter, superior parietal white matter, and precentral gyral thickness. Results were similar for surface area and white matter volumes generated from the 3 tesla scanner. For cortical thickness measures however, seven edited ROI measures, primarily in frontal and temporal regions, differed significantly from their unedited counterparts, and three additional ROI measures approached significance. Mean effect sizes for edited ROIs did not differ from most unedited ROIs for either 1.5 or 3 tesla data. Taken together, these results suggest that although the application of control points may increase the validity of intensity normalization and, ultimately, segmentation, it may not affect the final, extracted metrics that FS generates. Potential exceptions to and limitations of these conclusions are discussed.
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Affiliation(s)
- Christopher S McCarthy
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
| | - Avinash Ramprashad
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
| | - Carlie Thompson
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
| | - Jo-Anna Botti
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
| | - Ioana L Coman
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
| | - Wendy R Kates
- Department of Psychiatry and Behavioral Sciences, Center for Psychiatric Neuroimaging, State University of New York at Upstate Medical University Syracuse, NY, USA
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Chang YL, Fennema-Notestine C, Holland D, McEvoy LK, Stricker NH, Salmon DP, Dale AM, Bondi MW. APOE interacts with age to modify rate of decline in cognitive and brain changes in Alzheimer's disease. Alzheimers Dement 2014; 10:336-48. [PMID: 23896613 PMCID: PMC3815680 DOI: 10.1016/j.jalz.2013.05.1763] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2012] [Revised: 03/29/2013] [Accepted: 05/02/2013] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To determine (1) whether age-standardized cognitive declines and brain morphometric change differ between Young-Old patients with Alzheimer's disease (YOAD) and Very-Old patients with Alzheimer's disease (VOAD), and (2) whether the apolipoprotein E (APOE) genotype modifies these neuropsychological and morphometric changes. METHODS Baseline and 12-month follow-up neuropsychological and morphometric measures were examined for healthy control subjects and patients with AD. The two AD groups were divided further into subgroups on the basis of the presence of at least one APOE ε4 allele. RESULTS The YOAD group showed more severe deficits and steeper declines in cognition than the VOAD group. Moreover, the presence of an APOE ε4 allele had a more deleterious effect on the YOAD group than the VOAD group on cognition and brain structure both cross-sectionally and longitudinally. CONCLUSIONS Results underscore the importance of integrating an individual's age and genetic susceptibility--and their interaction--when examining neuropsychological and neuroimaging changes in the early stages of Alzheimer's disease.
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Affiliation(s)
- Yu-Ling Chang
- Department of Psychology, National Taiwan University, Taipei, Taiwan
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California at San Diego, San Diego, CA, USA; Department of Radiology, University of California at San Diego, San Diego, CA, USA
| | - Dominic Holland
- Department of Neurosciences, University of California at San Diego, San Diego, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California at San Diego, San Diego, CA, USA
| | - Nikki H Stricker
- Veterans Affairs Boston Healthcare System, Boston, MA, USA; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - David P Salmon
- Department of Neurosciences, University of California at San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California at San Diego, San Diego, CA, USA; Department of Neurosciences, University of California at San Diego, San Diego, CA, USA
| | - Mark W Bondi
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California at San Diego, San Diego, CA, USA.
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Cash DM, Ridgway GR, Liang Y, Ryan NS, Kinnunen KM, Yeatman T, Malone IB, Benzinger TLS, Jack CR, Thompson PM, Ghetti BF, Saykin AJ, Masters CL, Ringman JM, Salloway SP, Schofield PR, Sperling RA, Cairns NJ, Marcus DS, Xiong C, Bateman RJ, Morris JC, Rossor MN, Ourselin S, Fox NC. The pattern of atrophy in familial Alzheimer disease: volumetric MRI results from the DIAN study. Neurology 2013; 81:1425-33. [PMID: 24049139 PMCID: PMC3806583 DOI: 10.1212/wnl.0b013e3182a841c6] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2013] [Accepted: 07/15/2013] [Indexed: 01/28/2023] Open
Abstract
OBJECTIVE To assess regional patterns of gray and white matter atrophy in familial Alzheimer disease (FAD) mutation carriers. METHODS A total of 192 participants with volumetric T1-weighted MRI, genotyping, and clinical diagnosis were available from the Dominantly Inherited Alzheimer Network. Of these, 69 were presymptomatic mutation carriers, 50 were symptomatic carriers (31 with Clinical Dementia Rating [CDR] = 0.5, 19 with CDR > 0.5), and 73 were noncarriers from the same families. Voxel-based morphometry was used to identify cross-sectional group differences in gray matter and white matter volume. RESULTS Significant differences in gray matter (p < 0.05, family-wise error-corrected) were observed between noncarriers and mildly symptomatic (CDR = 0.5) carriers in the thalamus and putamen, as well as in the temporal lobe, precuneus, and cingulate gyrus; the same pattern, but with more extensive changes, was seen in those with CDR > 0.5. Significant white matter differences between noncarriers and symptomatic carriers were observed in the cingulum and fornix; these form input and output connections to the medial temporal lobe, cingulate, and precuneus. No differences between noncarriers and presymptomatic carriers survived correction for multiple comparisons, but there was a trend for decreased gray matter in the thalamus for carriers closer to their estimated age at onset. There were no significant increases of gray or white matter in asymptomatic or symptomatic carriers compared to noncarriers. CONCLUSIONS Atrophy in FAD is observed early, both in areas commonly associated with sporadic Alzheimer disease and also in the putamen and thalamus, 2 regions associated with early amyloid deposition in FAD mutation carriers.
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Affiliation(s)
- David M Cash
- From the Dementia Research Centre (D.M.C., Y.L., N.S.R., K.M.K., T.Y., I.B.M., M.N.R., S.O., N.C.F.) and Wellcome Trust Centre for Neuroimaging (G.R.R.), UCL Institute of Neurology, London, UK; Washington University School of Medicine (T.L.S.B., N.J.C., D.S.M., C.X., R.J.B., J.C.M.), St. Louis, MO; Mayo Clinic (C.R.J.), Rochester, MN; Imaging Genetics Center (P.M.T.), Laboratory of Neuroimaging, Department of Neurology & Psychiatry, UCLA School of Medicine, Los Angeles, CA; Indiana University School of Medicine (B.F.G., A.J.S.), Indianapolis; Mental Health Research Institute (C.L.M.), The University Of Melbourne, Victoria, Australia; Mary S. Easton Center for Alzheimer's Disease (J.M.R.), UCLA Department of Neurology, Los Angeles, CA; Butler Hospital (S.P.S.), Providence, RI; Neuroscience Research Australia (P.R.S.), Sydney; and the Center for Alzheimer Research and Treatment (R.A.S.), Brigham and Women's Hospital, Cambridge, MA
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Malone IB, Cash D, Ridgway GR, MacManus DG, Ourselin S, Fox NC, Schott JM. MIRIAD--Public release of a multiple time point Alzheimer's MR imaging dataset. Neuroimage 2013; 70:33-6. [PMID: 23274184 PMCID: PMC3809512 DOI: 10.1016/j.neuroimage.2012.12.044] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2012] [Revised: 12/14/2012] [Accepted: 12/18/2012] [Indexed: 11/18/2022] Open
Abstract
The Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD) dataset is a series of longitudinal volumetric T1 MRI scans of 46 mild-moderate Alzheimer's subjects and 23 controls. It consists of 708 scans conducted by the same radiographer with the same scanner and sequences at intervals of 2, 6, 14, 26, 38 and 52 weeks, 18 and 24 months from baseline, with accompanying information on gender, age and Mini Mental State Examination (MMSE) scores. Details of the cohort and imaging results have been described in peer-reviewed publications, and the data are here made publicly available as a common resource for researchers to develop, validate and compare techniques, particularly for measurement of longitudinal volume change in serially acquired MR.
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Affiliation(s)
- Ian B. Malone
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - David Cash
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Centre for Medical Image Computing, UCL, Gower Street, London, WC1E 6BT, UK
| | - Gerard R. Ridgway
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - David G. MacManus
- NMR Research Unit, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Sebastien Ourselin
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- Centre for Medical Image Computing, UCL, Gower Street, London, WC1E 6BT, UK
| | - Nick C. Fox
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
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Möller C, Vrenken H, Jiskoot L, Versteeg A, Barkhof F, Scheltens P, van der Flier WM. Different patterns of gray matter atrophy in early- and late-onset Alzheimer's disease. Neurobiol Aging 2013; 34:2014-22. [PMID: 23561509 DOI: 10.1016/j.neurobiolaging.2013.02.013] [Citation(s) in RCA: 133] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2012] [Revised: 01/25/2013] [Accepted: 02/17/2013] [Indexed: 12/16/2022]
Abstract
We assessed patterns of gray matter atrophy according to-age-at-onset in a large sample of 215 Alzheimer's disease (AD) patients and 129 control subjects with voxel-based morphometry using 3-Tesla 3D T1-weighted magnetic resonance imaging. Local gray matter amounts were compared between late- and early-onset AD patients and older and younger control subjects, taking into account the effect of apolipoprotein E. Additionally, combined effects of age and diagnosis on volumes of hippocampus and precuneus were assessed. Compared with age-matched control subjects, late-onset AD patients exhibited atrophy of the hippocampus, right temporal lobe, and cerebellum, whereas early-onset AD patients showed gray matter atrophy in hippocampus, temporal lobes, precuneus, cingulate gyrus, and inferior frontal cortex. Direct comparisons between late- and early-onset AD patients revealed more pronounced atrophy of precuneus in early-onset AD patients and more severe atrophy in medial temporal lobe in late-onset AD patients. Age and diagnosis independently affected the hippocampus; moreover, the interaction between age and diagnosis showed that precuneus atrophy was most prominent in early-onset AD patients. Our results suggest that patterns of atrophy might vary in the spectrum of AD.
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Affiliation(s)
- Christiane Möller
- Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands.
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Prabhakaran V, Nair VA, Austin BP, La C, Gallagher TA, Wu Y, McLaren DG, Xu G, Turski P, Rowley H. Current status and future perspectives of magnetic resonance high-field imaging: a summary. Neuroimaging Clin N Am 2012; 22:373-97, xii. [PMID: 22548938 DOI: 10.1016/j.nic.2012.02.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
There are several magnetic resonance (MR) imaging techniques that benefit from high-field MR imaging. This article describes a range of novel techniques that are currently being used clinically or will be used in the future for clinical purposes as they gain popularity. These techniques include functional MR imaging, diffusion tensor imaging, cortical thickness assessment, arterial spin labeling perfusion, white matter hyperintensity lesion assessment, and advanced MR angiography.
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Affiliation(s)
- Vivek Prabhakaran
- Division of Neuroradiology, Department of Radiology, University of Wisconsin, 600 Highland Avenue, Madison, WI 53792-3252, USA.
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Snowden JS, Thompson JC, Stopford CL, Richardson AMT, Gerhard A, Neary D, Mann DMA. The clinical diagnosis of early-onset dementias: diagnostic accuracy and clinicopathological relationships. ACTA ACUST UNITED AC 2011; 134:2478-92. [PMID: 21840888 DOI: 10.1093/brain/awr189] [Citation(s) in RCA: 167] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Accuracy of clinical diagnosis of dementia is increasingly important for therapeutic and scientific investigations. In this study, we examine diagnostic accuracy in a consecutive series of 228 patients referred to a specialist early-onset dementia clinic, whose brains were subsequently examined at post-mortem. Diagnosis was based on structured history, neurological examination and neuropsychological assessment, with emphasis on qualitative as well as quantitative aspects of performance. Neuroimaging provided support for but did not alter the clinical diagnosis. We set out the principles that guided diagnosis: (i) time course of illness; (ii) weighting of physical, behavioural and cognitive symptoms and signs; (iii) 'anterior' versus 'posterior' hemisphere character of cognitive change; and (iv) specificity of deficit, paying attention to the differentiation between syndromes of frontotemporal lobar degeneration and focal forms of Alzheimer's disease. Forty-two per cent of the patients had clinical diagnoses of one of the syndromes of frontotemporal lobar degeneration, the high proportion reflecting the research interests of the group. Forty-six per cent were diagnosed with Alzheimer's disease and the remaining patients, dementia with Lewy bodies, Creutzfeldt-Jakob disease, vascular or unclassified dementia. Frontotemporal lobar degeneration was identified with 100% sensitivity and 97% specificity and Alzheimer's disease with 97% sensitivity and 100% specificity. Patients with other pathologies were accurately identified on clinical grounds. Examination of subsyndromes of frontotemporal lobar degeneration showed a relatively predictable relationship between clinical diagnosis and pathological subtype. Whereas the behavioural disorder of frontotemporal dementia was associated with tau, transactive response DNA binding protein 43 and fused-in-sarcoma pathology, cases of frontotemporal dementia with motoneuron disease, semantic dementia and, with one exception, progressive non-fluent aphasia were associated with transactive response DNA binding protein 43 pathology, distinguished by ubiquitin subtyping (types B, C and A, respectively). Clinical diagnoses of progressive apraxia, corticobasal degeneration and progressive supranuclear palsy were, with one exception, associated with Pick, corticobasal and progressive supranuclear palsy subtypes of tau pathology, respectively. Unanticipated findings included Alzheimer pathology in two patients presenting with the behavioural syndrome of frontotemporal dementia and corticobasal pathology in four others with clinical frontotemporal dementia. Notwithstanding such anomalies, which serve as a reminder that there is not an absolute concordance between clinical phenotype and underlying pathology, the findings show that dementias can be distinguished in life with a high level of accuracy. Moreover, careful clinical phenotyping allows prediction of histopathological subtype of frontotemporal lobar degeneration. The principles guiding diagnosis provide the foundation for future prospective studies.
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Affiliation(s)
- Julie S Snowden
- Cerebral Function Unit, Greater Manchester Neuroscience centre, Salford Royal NHS Foundation Trust, Salford M6 8HD, UK.
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Clarkson MJ, Cardoso MJ, Ridgway GR, Modat M, Leung KK, Rohrer JD, Fox NC, Ourselin S. A comparison of voxel and surface based cortical thickness estimation methods. Neuroimage 2011; 57:856-65. [PMID: 21640841 DOI: 10.1016/j.neuroimage.2011.05.053] [Citation(s) in RCA: 140] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2011] [Revised: 04/19/2011] [Accepted: 05/17/2011] [Indexed: 10/25/2022] Open
Abstract
Cortical thickness estimation performed in-vivo via magnetic resonance imaging is an important technique for the diagnosis and understanding of the progression of neurodegenerative diseases. Currently, two different computational paradigms exist, with methods generally classified as either surface or voxel-based. This paper provides a much needed comparison of the surface-based method FreeSurfer and two voxel-based methods using clinical data. We test the effects of computing regional statistics using two different atlases and demonstrate that this makes a significant difference to the cortical thickness results. We assess reproducibility, and show that FreeSurfer has a regional standard deviation of thickness difference on same day scans that is significantly lower than either a Laplacian or Registration based method and discuss the trade off between reproducibility and segmentation accuracy caused by bending energy constraints. We demonstrate that voxel-based methods can detect similar patterns of group-wise differences as well as FreeSurfer in typical applications such as producing group-wise maps of statistically significant thickness change, but that regional statistics can vary between methods. We use a Support Vector Machine to classify patients against controls and did not find statistically significantly different results with voxel based methods compared to FreeSurfer. Finally we assessed longitudinal performance and concluded that currently FreeSurfer provides the most plausible measure of change over time, with further work required for voxel based methods.
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Affiliation(s)
- Matthew J Clarkson
- Centre for Medical Image Computing, The Engineering Front Building, University College London, London WC1E 6BT, UK.
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van der Flier WM, Pijnenburg YA, Fox NC, Scheltens P. Early-onset versus late-onset Alzheimer's disease: the case of the missing APOE ɛ4 allele. Lancet Neurol 2010; 10:280-8. [PMID: 21185234 DOI: 10.1016/s1474-4422(10)70306-9] [Citation(s) in RCA: 224] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Some patients with early-onset Alzheimer's disease (AD) present with a distinct phenotype. Typically, the first and most salient characteristic of AD is episodic memory impairment. A few patients, however, present with focal cortical, non-memory symptoms, such as difficulties with language, visuospatial, or executive functions. These presentations are associated with specific patterns of atrophy and frequently with a young age at onset. Age is not, however, the only determinant of phenotype; underlying factors, especially genetic factors, seem also to affect phenotype and predispose patients to younger or older age at onset. Importantly, patients with atypical early-onset disease seldom carry the APOE ɛ4 allele, which is the most important risk factor for lowering the age of onset in patients with AD. Additionally, theAPOE ɛ4 genotype seems to predispose patients to vulnerability in the medial temporal areas, which leads to memory loss. Conversely, patients negative for the APOE ɛ4 allele and with early-onset AD are more likely to be predisposed to vulnerability of cerebral networks beyond the medial temporal lobes. Other factors are probably involved in determining the pattern of atrophy, but these are currently unknown.
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Affiliation(s)
- Wiesje M van der Flier
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands
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