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Zhou Z, Wang Q, An X, Chen S, Sun Y, Wang G, Yan G. A novel graph neural network method for Alzheimer's disease classification. Comput Biol Med 2024; 180:108869. [PMID: 39096607 DOI: 10.1016/j.compbiomed.2024.108869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 06/19/2024] [Accepted: 07/07/2024] [Indexed: 08/05/2024]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease. Early diagnosis are very important to timely treatment and delay the progression of the disease. In the past decade, many computer-aided diagnostic (CAD) algorithms have been proposed for classification of AD. In this paper, we propose a novel graph neural network method, termed Brain Graph Attention Network (BGAN) for classification of AD. First, brain graph data are used to model classification of AD as a graph classification task. Second, a local attention layer is designed to capture and aggregate messages of interactions between node neighbors. And, a global attention layer is introduced to obtain the contribution of each node for graph representation. Finally, using the BGAN to implement AD classification. We train and test on two open public databases for AD classification task. Compared to classic models, the experimental results show that our model is superior to six classic models. We demonstrate that BGAN is a powerful classification model for AD. In addition, our model can provide an analysis of brain regions in order to judge which regions are related to AD disease and which regions are related to AD progression.
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Affiliation(s)
- Zhiheng Zhou
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China; School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Qi Wang
- College of Science, China Agricultural University, Beijing, China
| | - Xiaoyu An
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, China
| | - Siwei Chen
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Yongan Sun
- Department of Neurology, Peking University First Hospital, Beijing, China
| | - Guanghui Wang
- School of Mathematics, Shandong University, Jinan, China
| | - Guiying Yan
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China; School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China.
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Pumo A, Legeay S. The dichotomous activities of microglia: A potential driver for phenotypic heterogeneity in Alzheimer's disease. Brain Res 2024; 1832:148817. [PMID: 38395249 DOI: 10.1016/j.brainres.2024.148817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/28/2024] [Accepted: 02/19/2024] [Indexed: 02/25/2024]
Abstract
Alzheimer's disease (AD) is a leading cause of dementia, characterized by two defining neuropathological hallmarks: amyloid plaques composed of Aβ aggregates and neurofibrillary pathology. Recent research suggests that microglia have both beneficial and detrimental effects in the development of AD. A new theory proposes that microglia play a beneficial role in the early stages of the disease but become harmful in later stages. Further investigations are needed to gain a comprehensive understanding of this shift in microglia's function. This transition is likely influenced by specific conditions, including spatial, temporal, and transcriptional factors, which ultimately lead to the deterioration of microglial functionality. Additionally, recent studies have also highlighted the potential influence of microglia diversity on the various manifestations of AD. By deciphering the multiple states of microglia and the phenotypic heterogeneity in AD, significant progress can be made towards personalized medicine and better treatment outcomes for individuals affected by AD.
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Affiliation(s)
- Anna Pumo
- Université d'Angers, Faculté de Santé, Département Pharmacie, 16, Boulevard Daviers, Angers 49045, France.
| | - Samuel Legeay
- Université d'Angers, Faculté de Santé, Département Pharmacie, 16, Boulevard Daviers, Angers 49045, France; Univ Angers, Inserm, CNRS, MINT, SFR ICAT, Angers F-49000, France
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3
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Wu Y, Gao M, Lv L, Yan Y, Gao L, Geng Z, Zhou S, Zhu W, Yu Y, Tian Y, Ji G, Hu P, Wu X, Wang K. Brain functional specialization and cooperation in Alzheimer's disease. Brain Behav 2024; 14:e3550. [PMID: 38841739 PMCID: PMC11154812 DOI: 10.1002/brb3.3550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 04/10/2024] [Accepted: 04/13/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Cerebral specialization and interhemispheric cooperation are two vital features of the human brain. Their dysfunction may be associated with disease progression in patients with Alzheimer's disease (AD), which is featured as progressive cognitive degeneration and asymmetric neuropathology. OBJECTIVE This study aimed to examine and define two inherent properties of hemispheric function in patients with AD by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS Sixty-four clinically diagnosed AD patients and 52 age- and sex-matched cognitively normal subjects were recruited and underwent MRI and clinical evaluation. We calculated and compared brain specialization (autonomy index, AI) and interhemispheric cooperation (connectivity between functionally homotopic voxels, CFH). RESULTS In comparison to healthy controls, patients with AD exhibited enhanced AI in the left middle occipital gyrus. This increase in specialization can be attributed to reduced functional connectivity in the contralateral region, such as the right temporal lobe. The CFH of the bilateral precuneus and prefrontal areas was significantly decreased in AD patients compared to controls. Imaging-cognitive correlation analysis indicated that the CFH of the right prefrontal cortex was marginally positively related to the Montreal Cognitive Assessment score in patients and the Auditory Verbal Learning Test score. Moreover, taking abnormal AI and CFH values as features, support vector machine-based classification achieved good accuracy, sensitivity, specificity, and area under the curve by leave-one-out cross-validation. CONCLUSION This study suggests that individuals with AD have abnormal cerebral specialization and interhemispheric cooperation. This provides new insights for further elucidation of the pathological mechanisms of AD.
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Affiliation(s)
- Yue Wu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Department of Psychology and Sleep Medicinethe Second Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Manman Gao
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Lingling Lv
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Yibing Yan
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Liying Gao
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Zhi Geng
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Shanshan Zhou
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
| | - Wanqiu Zhu
- Department of Radiologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Yongqiang Yu
- Department of Radiologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Yanghua Tian
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
| | - Gong‐Jun Ji
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
| | - Panpan Hu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
| | - Xingqi Wu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Kai Wang
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
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Iaccarino L, Llibre-Guerra JJ, McDade E, Edwards L, Gordon B, Benzinger T, Hassenstab J, Kramer JH, Li Y, Miller BL, Miller Z, Morris JC, Mundada N, Perrin RJ, Rosen HJ, Soleimani-Meigooni D, Strom A, Tsoy E, Wang G, Xiong C, Allegri R, Chrem P, Vazquez S, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Salloway S, Fox NC, Day GS, Gorno-Tempini ML, Boxer AL, La Joie R, Bateman R, Rabinovici GD. Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2024; 6:fcae159. [PMID: 38784820 PMCID: PMC11114609 DOI: 10.1093/braincomms/fcae159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 03/14/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.
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Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jorge J Llibre-Guerra
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason Hassenstab
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Richard J Perrin
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Elena Tsoy
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Silvia Vazquez
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Department of Neuroscience, Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, Indiana, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Stephen Salloway
- Memory & Aging Program, Butler Hospital, Brown University in Providence, RI 02906, USA
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Randall Bateman
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
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Bick A, McKyton A, Glick-Shames H, Rein N, Levin N. Abnormal network connections to early visual cortex in posterior cortical atrophy. J Neurol Sci 2023; 454:120826. [PMID: 37832379 DOI: 10.1016/j.jns.2023.120826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023]
Abstract
INTRODUCTION Posterior Cortical Atrophy (PCA), a visual variant of Alzheimer's disease, initially manifests with higher-order visual disorders and parieto/temporo-occipital atrophy. Recent studies have shown remote functional impairment in both distant brain networks and along the calcarine sulcus (V1). Functional alteration in the calcarine differs along its length, reflecting center to periphery visual space differences. Herein, we aim to connect between these two sets of findings by looking at the retinotopic patterns of functional connectivity between large-scale brain networks and V1, comparing patients with normally sighted subjects. METHODS Resting state functional magnetic resonance imaging (fMRI) and T1 anatomical scans were obtained from 11 PCA patients and 17 age-matched healthy volunteers. Default mode network (DMN) and fronto parietal network (FPN) were defined and differences between the networks in patients and healthy controls were evaluated at the whole brain level, specifically their connectivity to V1. RESULTS Connectivity patterns within the DMN and the FPN were similar between the groups, although differences were found in regions within and beyond the networks. Focusing on V1, in the control group we identified the expected pattern of a distributed connectivity along eccentricity, with foveal regions showing stronger connectivity to the FPN and peripheral regions showing stronger connectivity to the DMN. However, in PCA patients we could not identify a clear difference in connectivity along the eccentricities. CONCLUSION Lost specialization of function along the calcarine in PCA patients may have further implications on large-scale networks or vice versa. This impairment, distant from the core pathology, might explain patients' visual disabilities.
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Affiliation(s)
- Atira Bick
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Ayelet McKyton
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Haya Glick-Shames
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Netaniel Rein
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Netta Levin
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel.
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Valdez-Gaxiola CA, Maciel-Cruz EJ, Hernández-Peña R, Dumois-Petersen S, Rosales-Leycegui F, Gallegos-Arreola MP, Moreno-Ortiz JM, Figuera LE. Potential Modifying Effect of the APOEε4 Allele on Age of Onset and Clinical Manifestations in Patients with Early-Onset Alzheimer's Disease with and without a Pathogenic Variant in PSEN1 in a Sample of the Mexican Population. Int J Mol Sci 2023; 24:15687. [PMID: 37958671 PMCID: PMC10648484 DOI: 10.3390/ijms242115687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/01/2023] [Accepted: 09/23/2023] [Indexed: 11/15/2023] Open
Abstract
In Alzheimer's disease (AD), the age of onset (AoO) exhibits considerable variability, spanning from 40 to 90 years. Specifically, individuals diagnosed with AD and exhibiting symptoms prior to the age of 65 are typically classified as early onset (EOAD) cases. Notably, the apolipoprotein E (APOE) ε4 allele represents the most extensively studied genetic risk factor associated with AD. We clinically characterized and genotyped the APOEε4 allele from 101 individuals with a diagnosis of EOAD, and 69 of them were affected carriers of the autosomal dominant fully penetrant PSEN1 variant c.1292C>A (rs63750083, A431E) (PSEN1+ group), while there were 32 patients in which the genetic cause was unknown (PSEN1- group). We found a correlation between the AoO and the APOEε4 allele; patients carrying at least one APOEε4 allele showed delays, in AoO in patients in the PSEN1+ and PSEN1- groups, of 3.9 (p = 0.001) and 8.6 years (p = 0.012), respectively. The PSEN1+ group presented higher frequencies of gait disorders compared to PSEN1- group, and apraxia was more frequent with PSEN1+/APOE4+ than in the rest of the subgroup. This study shows what appears to be an inverse effect of APOEε4 in EOAD patients, as it delays AoO and modifies clinical manifestations.
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Affiliation(s)
- César A. Valdez-Gaxiola
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
| | - Eric Jonathan Maciel-Cruz
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
| | - Rubiceli Hernández-Peña
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
| | - Sofía Dumois-Petersen
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
| | - Frida Rosales-Leycegui
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Maestría en Ciencias del Comportamiento, Instituto de Neurociencias, Centro Universitario de Ciencias Biológicas y Agropecuarias, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico
| | - Martha Patricia Gallegos-Arreola
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
| | - José Miguel Moreno-Ortiz
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
- Instituto de Genética Humana “Dr. Enrique Corona Rivera”, Departamento de Biología Molecular y Genómica, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico
| | - Luis E. Figuera
- División de Genética, Centro de Investigación Biomédica de Occidente, IMSS, Guadalajara 44340, Jalisco, Mexico; (C.A.V.-G.); (E.J.M.-C.); (R.H.-P.); (S.D.-P.); (F.R.-L.); (M.P.G.-A.)
- Doctorado en Genética Humana, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Jalisco, Mexico;
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Llibre-Guerra JJ, Iaccarino L, Coble D, Edwards L, Li Y, McDade E, Strom A, Gordon B, Mundada N, Schindler SE, Tsoy E, Ma Y, Lu R, Fagan AM, Benzinger TLS, Soleimani-Meigooni D, Aschenbrenner AJ, Miller Z, Wang G, Kramer JH, Hassenstab J, Rosen HJ, Morris JC, Miller BL, Xiong C, Perrin RJ, Allegri R, Chrem P, Surace E, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Fox NC, Day G, Gorno-Tempini ML, Boxer AL, La Joie R, Rabinovici GD, Bateman R. Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2023; 5:fcad280. [PMID: 37942088 PMCID: PMC10629466 DOI: 10.1093/braincomms/fcad280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 10/02/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023] Open
Abstract
Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.
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Affiliation(s)
| | - Leonardo Iaccarino
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Dean Coble
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Amelia Strom
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Elena Tsoy
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yinjiao Ma
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Ruijin Lu
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Tammie L S Benzinger
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - David Soleimani-Meigooni
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | | | - Zachary Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Howard J Rosen
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Bruce L Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
- Department of Pathology and Immunology, Washington University in St Louis, St. Louis, MO 63108, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Ezequiel Surace
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
- Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Gil D Rabinovici
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Randall Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
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8
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Mandelli ML, Lorca‐Puls DL, Lukic S, Montembeault M, Gajardo‐Vidal A, Licata A, Scheffler A, Battistella G, Grasso SM, Bogley R, Ratnasiri BM, La Joie R, Mundada NS, Europa E, Rabinovici G, Miller BL, De Leon J, Henry ML, Miller Z, Gorno‐Tempini ML. Network anatomy in logopenic variant of primary progressive aphasia. Hum Brain Mapp 2023; 44:4390-4406. [PMID: 37306089 PMCID: PMC10318204 DOI: 10.1002/hbm.26388] [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: 12/22/2022] [Revised: 04/21/2023] [Accepted: 05/17/2023] [Indexed: 06/13/2023] Open
Abstract
The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporoparietal junction regions, predominantly follows at least two partially nonoverlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.
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Affiliation(s)
- Maria Luisa Mandelli
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Diego L. Lorca‐Puls
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Sección de Neurología, Departamento de Especialidades, Facultad de MedicinaUniversidad de ConcepciónConcepciónChile
| | - Sladjana Lukic
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Communication Sciences and DisordersAdelphi UniversityGarden CityNew YorkUSA
| | - Maxime Montembeault
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of PsychiatryDouglas Mental Health University Institute, McGill UniversityMontréalCanada
| | - Andrea Gajardo‐Vidal
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Faculty of Health SciencesUniversidad del DesarrolloConcepciónChile
| | - Abigail Licata
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Aaron Scheffler
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Giovanni Battistella
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of OtolaryngologyHead and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical SchoolBostonMassachusettsUSA
| | - Stephanie M. Grasso
- Department of Speech, Language, and Hearing SciencesUniversity of TexasAustinTexasUSA
| | - Rian Bogley
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Buddhika M. Ratnasiri
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Nidhi S. Mundada
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Eduardo Europa
- Department of Communicative Disorders and SciencesSan Jose State UniversitySan JoseCaliforniaUSA
| | - Gil Rabinovici
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jessica De Leon
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Maya L. Henry
- Department of Speech, Language, and Hearing SciencesUniversity of TexasAustinTexasUSA
| | - Zachary Miller
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
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9
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Mak E, Zhang L, Tan CH, Reilhac A, Shim HY, Wen MOQ, Wong ZX, Chong EJY, Xu X, Stephenson M, Venketasubramanian N, Zhou JH, O’Brien JT, Chen CLH. Longitudinal associations between β-amyloid and cortical thickness in mild cognitive impairment. Brain Commun 2023; 5:fcad192. [PMID: 37483530 PMCID: PMC10358322 DOI: 10.1093/braincomms/fcad192] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/25/2023] [Accepted: 07/03/2023] [Indexed: 07/25/2023] Open
Abstract
How beta-amyloid accumulation influences brain atrophy in Alzheimer's disease remains contentious with conflicting findings. We aimed to elucidate the correlations of regional longitudinal atrophy with cross-sectional regional and global amyloid in individuals with mild cognitive impairment and no cognitive impairment. We hypothesized that greater cortical thinning over time correlated with greater amyloid deposition, particularly within Alzheimer's disease characteristic regions in mild cognitive impairment, and weaker or no correlations in those with no cognitive impairment. 45 patients with mild cognitive impairment and 12 controls underwent a cross-sectional [11C]-Pittsburgh Compound B PET and two retrospective longitudinal structural imaging (follow-up: 23.65 ± 2.04 months) to assess global/regional amyloid and regional cortical thickness, respectively. Separate linear mixed models were constructed to evaluate relationships of either global or regional amyloid with regional cortical thinning longitudinally. In patients with mild cognitive impairment, regional amyloid in the right banks of the superior temporal sulcus was associated with longitudinal cortical thinning in the right medial orbitofrontal cortex (P = 0.04 after False Discovery Rate correction). In the mild cognitive impairment group, greater right banks amyloid burden and less cortical thickness in the right medial orbitofrontal cortex showed greater visual and verbal memory decline over time, which was not observed in controls. Global amyloid was not associated with longitudinal cortical thinning in any locations in either group. Our findings indicate an increasing influence of amyloid on neurodegeneration and memory along the preclinical to prodromal spectrum. Future multimodal studies that include additional biomarkers will be well-suited to delineate the interplay between various pathological processes and amyloid and memory decline, as well as clarify their additive or independent effects along the disease deterioration.
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Affiliation(s)
- Elijah Mak
- Correspondence to: Elijah Mak, PhD Department of Psychiatry, University of Cambridge Hills Road, Cambridge, Cambridgeshire, CB20QQ, United Kingdom E-mail:
| | | | - Chin Hong Tan
- Division of Psychology, Nanyang Technological University, Singapore, 637331, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Anthonin Reilhac
- Clinical Imaging Research Centre, the Agency for Science, Technology and Research, and National University of Singapore, Singapore, 117599, Singapore
| | - Hee Youn Shim
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Marcus Ong Qin Wen
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Zi Xuen Wong
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Eddie Jun Yi Chong
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Xin Xu
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- School of Public Health, and the 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 311100, China
| | - Mary Stephenson
- Centre for Translational MR Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117549, Singapore
| | | | - Juan Helen Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Centre for Translational MR Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117549, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 119077, Singapore
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 2QQ, United Kingdom
| | - Christopher Li-Hsian Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
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10
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Pillai JA, Bena J, Maly EF, Leverenz JB. Initial non-amnestic symptoms relate to faster rate of functional and cognitive decline compared to amnestic symptoms in neuropathologically confirmed dementias. Alzheimers Dement 2023; 19:2956-2965. [PMID: 36648159 PMCID: PMC10350479 DOI: 10.1002/alz.12922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/28/2022] [Accepted: 12/12/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION The relationship between initial cognitive symptoms and subsequent rate of clinical decline is important in clinical care and the design of dementia clinical trials. METHODS This retrospective longitudinal, autopsy-confirmed, cohort study among 2426 participants in the National Alzheimer's Coordinating Center database included Alzheimer's disease (AD) pathology, n = 1187; Lewy body pathology (LBP), n = 331; and mixed pathology (AD-LBP), n = 904. The predominant initial cognitive symptom was assessed clinically. Linear mixed models evaluated the longitudinal outcome of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score. RESULTS Non-amnestic initial symptoms had a faster rate of decline than amnestic symptoms in all three groups. Language symptoms had a faster rate of decline in all three groups. Executive symptoms had a faster rate of decline than amnestic in AD and AD-LBP. There was a similar trend for visuospatial symptoms in AD-LBP. DISCUSSION Initial cognitive symptoms, despite varied underlying pathology, are a predictor of longitudinal functional outcomes among dementias. HIGHLIGHTS Initial non-amnestic symptoms had a faster rate of longitudinal cognitive and functional decline on the Clinical Dementia Rating-Sum of Boxes (CDR-SB) scores than amnestic symptoms among Alzheimer's disease, Lewy body pathology, and mixed neuropathology. Given the relative size of CDR-SB changes in Alzheimer's disease clinical trials, clarifying the nature of initial symptoms could be an important variable in ensuring appropriately designed clinical trials.
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Affiliation(s)
- Jagan A Pillai
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH 44195
- Neurological Institute ,Cleveland Clinic, Cleveland, OH 44195
- Department of Neurology, Cleveland Clinic, Cleveland, OH 44195
| | - James Bena
- Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195
| | - Emily F Maly
- Department of Neurology, Cleveland Clinic, Cleveland, OH 44195
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH 44195
- Neurological Institute ,Cleveland Clinic, Cleveland, OH 44195
- Department of Neurology, Cleveland Clinic, Cleveland, OH 44195
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11
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Oliveira FFD. Looking Behind the Curtain: Patient Stratification According to Genetic or Demographic Factors May Yield Unexpected Results in Studies of Neurodegenerative Diseases. J Alzheimers Dis 2023:JAD230561. [PMID: 37393510 DOI: 10.3233/jad-230561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2023]
Abstract
Amyloid-PET studies of neurodegenerative diseases may yield inconclusive findings due to lacking stratification according to genetic or demographic variants. APOEɛ4 alleles are the major variants to increase disease susceptibility and cause earlier onset and more behavioral features in patients with late-onset Alzheimer's disease, but have no linear effects on cognitive or functional decline; thus, sample stratification according to APOEɛ4 carrier status may be the best option. Interactions among APOEɛ4 alleles, sex, and age on amyloid-β deposition may reveal even more innovative findings with sufficiently large samples, suggesting variable genomic effects of cognitive reserve, sex differences, and cerebrovascular risk on neurodegeneration.
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12
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Mandelli ML, Lorca-Puls DL, Lukic S, Montembeault M, Gajardo-Vidal A, Licata A, Scheffler A, Battistella G, Grasso SM, Bogley R, Ratnasiri BM, La Joie R, Mundada NS, Europa E, Rabinovici G, Miller BL, De Leon J, Henry ML, Miller Z, Gorno-Tempini ML. Network anatomy in logopenic variant of primary progressive aphasia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.15.23289065. [PMID: 37292690 PMCID: PMC10246009 DOI: 10.1101/2023.05.15.23289065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills, resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through pre-determined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically-fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporo-parietal junction regions, predominantly follows at least two partially non-overlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.
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13
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Abbate C. The Adult Neurogenesis Theory of Alzheimer's Disease. J Alzheimers Dis 2023:JAD221279. [PMID: 37182879 DOI: 10.3233/jad-221279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Alzheimer's disease starts in neural stem cells (NSCs) in the niches of adult neurogenesis. All primary factors responsible for pathological tau hyperphosphorylation are inherent to adult neurogenesis and migration. However, when amyloid pathology is present, it strongly amplifies tau pathogenesis. Indeed, the progressive accumulation of extracellular amyloid-β deposits in the brain triggers a state of chronic inflammation by microglia. Microglial activation has a significant pro-neurogenic effect that fosters the process of adult neurogenesis and supports neuronal migration. Unfortunately, this "reactive" pro-neurogenic activity ultimately perturbs homeostatic equilibrium in the niches of adult neurogenesis by amplifying tau pathogenesis in AD. This scenario involves NSCs in the subgranular zone of the hippocampal dentate gyrus in late-onset AD (LOAD) and NSCs in the ventricular-subventricular zone along the lateral ventricles in early-onset AD (EOAD), including familial AD (FAD). Neuroblasts carrying the initial seed of tau pathology travel throughout the brain via neuronal migration driven by complex signals and convey the disease from the niches of adult neurogenesis to near (LOAD) or distant (EOAD) brain regions. In these locations, or in close proximity, a focus of degeneration begins to develop. Then, tau pathology spreads from the initial foci to large neuronal networks along neural connections through neuron-to-neuron transmission.
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Affiliation(s)
- Carlo Abbate
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
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14
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Lu J, Zhang Z, Wu P, Liang X, Zhang H, Hong J, Clement C, Yen TC, Ding S, Wang M, Xiao Z, Rominger A, Shi K, Guan Y, Zuo C, Zhao Q. The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer's disease. Neuroimage Clin 2023; 38:103416. [PMID: 37137254 PMCID: PMC10176076 DOI: 10.1016/j.nicl.2023.103416] [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: 02/13/2023] [Revised: 04/13/2023] [Accepted: 04/22/2023] [Indexed: 05/05/2023]
Abstract
PURPOSE Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity. METHODS Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with 18F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with 18F-Florzolotau]. Based on the absolute global tau interhemispheric differences, each cohort was divided into two groups (asymmetric versus symmetric tau distribution). The two groups were cross-sectionally compared in terms of demographic, cognitive characteristics, and pathological burden. The cognitive decline trajectories were analyzed longitudinally. RESULTS Fourteen (23.3%) and 42 (48.3%) patients in the ADNI and SMS cohorts showed an asymmetric tau distribution, respectively. An asymmetric tau distribution was associated with an earlier age at disease onset (proportion of early-onset AD: ADNI/SMS/combined cohorts, p = 0.093/0.026/0.001) and more severe pathological burden (i.e., global tau burden: ADNI/SMS cohorts, p < 0.001/= 0.007). And patients with an asymmetric tau distribution were characterized by a steeper cognitive decline longitudinally (i.e., the annual decline of Mini-Mental Status Examination score: ADNI/SMS/combined cohorts, p = 0.053 / 0.035 / < 0.001). CONCLUSIONS Asymmetry in tau deposition, which may be associated with an earlier age at onset, more severe pathological burden, and a steeper cognitive decline, is potentially an important characteristic of AD heterogeneity.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Zhengwei Zhang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jimin Hong
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Christoph Clement
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | | | - Saineng Ding
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Min Wang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China; Department of Informatics, Technische Universität München, Munich, Germany
| | - Zhenxu Xiao
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland; Department of Informatics, Technische Universität München, Munich, Germany
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Qianhua Zhao
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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15
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Best J, Chapleau M, Rabinovici GD. Posterior cortical atrophy: clinical, neuroimaging, and neuropathological features. Expert Rev Neurother 2023; 23:227-236. [PMID: 36920752 DOI: 10.1080/14737175.2023.2190885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
INTRODUCTION Posterior Cortical Atrophy (PCA) is a neurodegenerative disorder characterized by impairment of higher-order visual processing in the setting of progressive atrophy of the parietal and occipital lobes. The underlying pathology is variable but most commonly Alzheimer's disease. The majority of individuals develop symptoms before 65 years of age; however, delayed diagnosis is common due to misattribution of symptoms to ocular rather than cortical pathology. AREAS COVERED The purpose of this review is to provide readers with an in-depth analysis of Posterior Cortical Atrophy syndrome, including clinical, imaging, pathological, and genetic features, management, and treatments. EXPERT OPINION Most patients present initially with a relatively pure visuoperceptual-visuospatial syndrome, though other cognitive domains become affected over time. Structural neuroimaging demonstrates parieto-occipital or temporo-occipital predominant atrophy. Cerebrospinal fluid Alzheimer's disease biomarkers, or amyloid/tau PET imaging can help evaluate for underlying Alzheimer's disease, which is the most common underlying neuropathology. The cornerstone of management is focused on nonpharmacologic measures. Early etiologic diagnosis is important with the arrival of disease-modifying therapies, especially for Alzheimer's disease.
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Affiliation(s)
- John Best
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA.,Departments of Neurology, Radiology & Biomedical Imaging, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
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16
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Corriveau-Lecavalier N, Gunter JL, Kamykowski M, Dicks E, Botha H, Kremers WK, Graff-Radford J, Wiepert DA, Schwarz CG, Yacoub E, Knopman DS, Boeve BF, Ugurbil K, Petersen RC, Jack CR, Terpstra MJ, Jones DT. Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease. Brain Commun 2023; 5:fcad058. [PMID: 37013176 PMCID: PMC10066575 DOI: 10.1093/braincomms/fcad058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 12/15/2022] [Accepted: 03/07/2023] [Indexed: 03/09/2023] Open
Abstract
From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.
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Affiliation(s)
| | | | - Michael Kamykowski
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Essa Yacoub
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kamil Ugurbil
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa J Terpstra
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Radiology, University of Missouri, Columbia, MO 65211, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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17
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Donadio V, Sturchio A, Rizzo G, Abu Rumeileh S, Liguori R, Espay AJ. Pathology vs pathogenesis: Rationale and pitfalls in the clinicopathology model of neurodegeneration. HANDBOOK OF CLINICAL NEUROLOGY 2023; 192:35-55. [PMID: 36796947 DOI: 10.1016/b978-0-323-85538-9.00001-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
In neurodegenerative disorders, the term pathology is often implicitly referred to as pathogenesis. Pathology has been conceived as a window into the pathogenesis of neurodegenerative disorders. This clinicopathologic framework posits that what can be identified and quantified in postmortem brain tissue can explain both premortem clinical manifestations and the cause of death, a forensic approach to understanding neurodegeneration. As the century-old clinicopathology framework has yielded little correlation between pathology and clinical features or neuronal loss, the relationship between proteins and degeneration is ripe for revisitation. There are indeed two synchronous consequences of protein aggregation in neurodegeneration: the loss of the soluble/normal proteins on one; the accrual of the insoluble/abnormal fraction of these proteins on the other. The omission of the first part in the protein aggregation process is an artifact of the early autopsy studies: soluble, normal proteins have disappeared, with only the remaining insoluble fraction amenable to quantification. We here review the collective evidence from human data suggesting that protein aggregates, known collectively as pathology, are the consequence of many biological, toxic, and infectious exposures, but may not explain alone the cause or pathogenesis of neurodegenerative disorders.
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Affiliation(s)
- Vincenzo Donadio
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy.
| | - Andrea Sturchio
- Department of Clinical Neuroscience, Neuro Svenningsson, Karolinska Institutet, Stockholm, Sweden; James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, United States
| | - Giovanni Rizzo
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy
| | - Samir Abu Rumeileh
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Rocco Liguori
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy
| | - Alberto J Espay
- James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, United States
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18
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Wang L, Hu Z, Chen H, Sheng X, Qin R, Shao P, Yang Z, Yao W, Zhao H, Xu Y, Bai F. Applying Retinal Vascular Structures Characteristics Coupling with Cortical Visual System in Alzheimer's Disease Spectrum Patients. Brain Sci 2023; 13:brainsci13020339. [PMID: 36831883 PMCID: PMC9954049 DOI: 10.3390/brainsci13020339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/08/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
Cortical visual system dysfunction is closely related to the progression of Alzheimer's Disease (AD), while retinal vascular structures play an important role in the integrity of the function of the visual network and are a potential biomarker of AD. This study explored the association between the cortical visual system and retinal vascular structures in AD-spectrum patients, and it established a screening tool to detect preclinical AD based on these parameters identified in a retinal examination. A total of 42 subjects were enrolled and were distributed into two groups: 22 patients with cognitive impairment and 20 healthy controls. All participants underwent neuropsychological tests, optical coherence tomography angiography and resting-state fMRI imaging. Seed-based functional connectivity analysis was used to construct the cortical visual network. The association of functional connectivity of the cortical visual system and retinal vascular structures was further explored in these subjects. This study found that the cognitive impairment group displayed prominently decreased functional connectivity of the cortical visual system mainly involving the right inferior temporal gyrus, left supramarginal gyrus and right postcentral gyrus. Meanwhile, we observed that retinal vascular structure characteristics deteriorated with the decline in functional connectivity in the cortical visual system. Our study provided novel insights into the aberrant cortical visual system in patients with cognitive impairment that strongly emphasized the critical role of retinal vascular structure characteristics, which could be used as potential biomarkers for diagnosing and monitoring the progression of AD.
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Affiliation(s)
- Lianlian Wang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing 210008, China
| | - Zheqi Hu
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Xiaoning Sheng
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Pengfei Shao
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Zhiyuan Yang
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Weina Yao
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing 210008, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital of the Affiliated Hospital of Nanjing University Medical School, the State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing 210008, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing 210008, China
- Geriatric Medicine Center, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
- Correspondence: ; Tel.: +86-25-83105960
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19
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Yong KXX, Graff-Radford J, Ahmed S, Chapleau M, Ossenkoppele R, Putcha D, Rabinovici GD, Suarez-Gonzalez A, Schott JM, Crutch S, Harding E. Diagnosis and Management of Posterior Cortical Atrophy. Curr Treat Options Neurol 2023; 25:23-43. [PMID: 36820004 PMCID: PMC9935654 DOI: 10.1007/s11940-022-00745-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/10/2023]
Abstract
Purpose of review The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps. Recent findings Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer's disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies. Summary PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic - pharmacological and non-pharmacological - and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile - visual-spatial - rather than memory-led, predominantly young onset - and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.
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Affiliation(s)
- Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | | | - Samrah Ahmed
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire UK
| | - Marianne Chapleau
- Memory and Aging Center, University of California San Francisco, San Francisco, CA USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
| | - Gil D. Rabinovici
- Department of Neurology, Radiology, and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Sebastian Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Emma Harding
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
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20
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Katsumi Y, Putcha D, Eckbo R, Wong B, Quimby M, McGinnis S, Touroutoglou A, Dickerson BC. Anterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy. Brain 2023; 146:295-306. [PMID: 36237170 DOI: 10.1093/brain/awac245] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/16/2022] [Accepted: 06/21/2022] [Indexed: 01/11/2023] Open
Abstract
Posterior cortical atrophy (PCA), usually an atypical clinical syndrome of Alzheimer's disease, has well-characterized patterns of cortical atrophy and tau deposition that are distinct from typical amnestic presentations of Alzheimer's disease. However, the mechanisms underlying the cortical spread of tau in PCA remain unclear. Here, in a sample of 17 biomarker-confirmed (A+/T+/N+) individuals with PCA, we sought to identify functional networks with heightened vulnerability to tau pathology by examining the cortical distribution of elevated tau as measured by 18F-flortaucipir (FTP) PET. We then assessed the relationship between network-specific FTP uptake and visuospatial cognitive task performance. As predicted, we found consistent and prominent localization of tau pathology in the dorsal attention network and visual network of the cerebral cortex. Elevated FTP uptake within the dorsal attention network (particularly the ratio of FTP uptake between the anterior and posterior nodes) was associated with poorer visuospatial attention in PCA; associations were also identified in other functional networks, although to a weaker degree. Furthermore, using functional MRI data collected from each patient at wakeful rest, we found that a greater anterior-to-posterior ratio in FTP uptake was associated with stronger intrinsic functional connectivity between anterior and posterior nodes of the dorsal attention network. Taken together, we conclude that our cross-sectional marker of anterior-to-posterior FTP ratio could indicate tau propagation from posterior to anterior dorsal attention network nodes, and that this anterior progression occurs in relation to intrinsic functional connectivity within this network critical for visuospatial attention. Our findings help to clarify the spatiotemporal pattern of tau propagation in relation to visuospatial cognitive decline and highlight the key role of the dorsal attention network in the disease progression of PCA.
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Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott McGinnis
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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21
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Chen TB, Lee WJ, Chen JP, Chang SY, Lin CF, Chen HC. Imaging markers of cerebral amyloid angiopathy and hypertensive arteriopathy differentiate Alzheimer disease subtypes synergistically. Alzheimers Res Ther 2022; 14:141. [PMID: 36180874 PMCID: PMC9524061 DOI: 10.1186/s13195-022-01083-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022]
Abstract
Background Both cerebral amyloid angiopathy (CAA) and hypertensive arteriopathy (HA) are related to cognitive impairment and dementia. This study aimed to clarify CAA- and HA-related small vessel disease (SVD) imaging marker associations with cognitive dysfunction and Alzheimer disease (AD) subtypes. Methods A sample of 137 subjects with clinically diagnosed late-onset AD identified from the dementia registry of a single center from January 2017 to October 2021 were enrolled. Semi-quantitative imaging changes (visual rating scale grading) suggestive of SVD were analyzed singularly and compositely, and their correlations with cognitive domains and AD subtypes were examined. Results Patients with typical and limbic-predominant AD subtypes had worse cognitive performance and higher dementia severity than minimal-atrophy subtype patients. Deep white matter hyperintensity (WMH) presence correlated inversely with short-term memory (STM) performance. The three composite SVD scores correlated with different cognitive domains and had distinct associations with AD subtypes. After adjusting for relevant demographic factors, multivariate logistic regression (using minimal-atrophy subtype as the reference condition) revealed the following: associations of the typical subtype with periventricular WMH [odds ratio (OR) 2.62; 95% confidence interval (CI), 1.23–5.57, p = 0.012], global SVD score (OR 1.67; 95%CI, 1.11–2.52, p = 0.009), and HA-SVD score (OR 1.93; 95%CI, 1.10–3.52, p = 0.034); associations of limbic-predominant subtype with HA-SVD score (OR 2.57; 95%CI, 1.23–5.37, p = 0.012) and most global and domain-specific cognitive scores; and an association of hippocampal-sparing subtype with HA-SVD score (OR 3.30; 95%CI, 1.58–6.85, p = 0.001). Conclusion Composite SVD imaging markers reflect overall CAA and/or HA severity and may have differential associations with cognitive domains and AD subtypes. Our finding supports the possibility that the clinical AD subtypes may reflect differing burdens of underlying CAA and HA microangiopathologies. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01083-8.
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22
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Vipin A, Koh CL, Wong BYX, Zailan FZ, Tan JY, Soo SA, Satish V, Kumar D, Wang BZ, Ng ASL, Chiew HJ, Ng KP, Kandiah N. Amyloid-Tau-Neurodegeneration Profiles and Longitudinal Cognition in Sporadic Young-Onset Dementia. J Alzheimers Dis 2022; 90:543-551. [DOI: 10.3233/jad-220448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We examined amyloid-tau-neurodegeneration biomarker effects on cognition in a Southeast-Asian cohort of 84 sporadic young-onset dementia (YOD; age-at-onset <65 years) patients. They were stratified into A+N+, A– N+, and A– N– profiles via cerebrospinal fluid amyloid-β1–42 (A), phosphorylated-tau (T), MRI medial temporal atrophy (neurodegeneration– N), and confluent white matter hyperintensities cerebrovascular disease (CVD). A, T, and CVD effects on longitudinal Mini-Mental State Examination (MMSE) were evaluated. A+N+ patients demonstrated steeper MMSE decline than A– N+ (β = 1.53; p = 0.036; CI 0.15:2.92) and A– N– (β = 4.68; p = 0.001; CI 1.98:7.38) over a mean follow-up of 1.24 years. Within A– N+, T– CVD+ patients showed greater MMSE decline compared to T+CVD– patients (β = – 2.37; p = 0.030; CI – 4.41:– 0.39). A+ results in significant cognitive decline, while CVD influences longitudinal cognition in the A– sub-group.
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Affiliation(s)
- Ashwati Vipin
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
| | - Chen Ling Koh
- National Neuroscience Institute, Singapore, Singapore
| | | | - Fatin Zahra Zailan
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
| | - Jayne Yi Tan
- National Neuroscience Institute, Singapore, Singapore
| | - See Ann Soo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
| | - Vaynii Satish
- National Neuroscience Institute, Singapore, Singapore
| | - Dilip Kumar
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
| | | | - Adeline Su Lyn Ng
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Hui Jin Chiew
- National Neuroscience Institute, Singapore, Singapore
| | - Kok Pin Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Nagaendran Kandiah
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore
- National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
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23
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Kim SE, Kim HJ, Jang H, Weiner MW, DeCarli C, Na DL, Seo SW. Interaction between Alzheimer's Disease and Cerebral Small Vessel Disease: A Review Focused on Neuroimaging Markers. Int J Mol Sci 2022; 23:10490. [PMID: 36142419 PMCID: PMC9499680 DOI: 10.3390/ijms231810490] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/07/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan 48108, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, CA 94121, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA 95616, USA
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06355, Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul 06351, Korea
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24
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Fray S, Achouri-Rassas A, Belal S, Messaoud T. Missing apolipoprotein E ɛ4 allele associated with nonamnestic Alzheimer’s disease in a Tunisian population. J Genet 2022. [DOI: 10.1007/s12041-022-01384-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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25
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Therriault J, Pascoal TA, Savard M, Mathotaarachchi S, Benedet AL, Chamoun M, Tissot C, Lussier FZ, Rahmouni N, Stevenson J, Qureshi MNI, Kang MS, Thomas É, Vitali P, Soucy JP, Massarweh G, Saha-Chaudhuri P, Gauthier S, Rosa-Neto P. Intrinsic connectivity of the human brain provides scaffold for tau aggregation in clinical variants of Alzheimer's disease. Sci Transl Med 2022; 14:eabc8693. [PMID: 36001678 DOI: 10.1126/scitranslmed.abc8693] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) phenotypes might result from differences in selective vulnerability. Evidence from preclinical models suggests that tau pathology has cell-to-cell propagation properties. Therefore, here, we tested the cell-to-cell propagation framework in the amnestic, visuospatial, language, and behavioral/dysexecutive phenotypes of AD. We report that each AD phenotype is associated with a distinct network-specific pattern of tau aggregation, where tau aggregation is concentrated in brain network hubs. In all AD phenotypes, regional tau load could be predicted by connectivity patterns of the human brain. Furthermore, regions with greater connectivity displayed similar rates of longitudinal tau accumulation in an independent cohort. Connectivity-based tau deposition was not restricted to a specific vulnerable network but was rather a general property of brain organization, linking selective vulnerability and transneuronal spreading models of neurodegeneration. Together, this study indicates that intrinsic brain connectivity provides a framework for tau aggregation across diverse phenotypic manifestations of AD.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Mélissa Savard
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada
| | - Andréa L Benedet
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Émilie Thomas
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Jean-Paul Soucy
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Gassan Massarweh
- Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada.,Department of Radiochemistry, McGill University, Montreal, Quebec H3A 2B4, Canada
| | | | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec H3A 1G1, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada.,Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec H3A 1G1, Canada
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26
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De Anda-Duran I, Woltz SG, Bell CN, Bazzano LA. Hypertension and cognitive function: a review of life-course factors and disparities. Curr Opin Cardiol 2022; 37:326-333. [PMID: 35731677 PMCID: PMC9354652 DOI: 10.1097/hco.0000000000000975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF REVIEW Dementia is a life-course condition with modifiable risk factors many from cardiovascular (CV) origin, and disproportionally affects some race/ethnic groups and underserved communities in the USA. Hypertension (HTN) is the most common preventable and treatable condition that increases the risk for dementia and exacerbates dementia pathology. Epidemiological studies beginning in midlife provide strong evidence for this association. This study provides an overview of the differences in the associations across the lifespan, and the role of social determinants of health (SDoH). RECENT FINDINGS Clinical trials support HTN management in midlife as an avenue to lower the risk for late-life cognitive decline. However, the association between HTN and cognition differs over the life course. SDoH including higher education modify the association between HTN and cognition which may differ by race and ethnicity. The role of blood pressure (BP) variability, interactions among CV risk factors, and cognitive assessment modalities may provide information to better understand the relationship between HTN and cognition. SUMMARY Adopting a life-course approach that considers SDoH, may help develop tailored interventions to manage HTN and prevent dementia syndromes. Where clinical trials to assess BP management from childhood to late-life are not feasible, observational studies remain the best available evidence.
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Affiliation(s)
- Ileana De Anda-Duran
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Sara G. Woltz
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Caryn N. Bell
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Lydia A. Bazzano
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
- Tulane University School of Medicine, New Orleans, LA
- Ochsner Clinic Foundation, New Orleans, LA
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27
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Correlación entre el metabolismo de la glucosa cerebral (18F-FDG) y el flujo sanguíneo cerebral con marcadores de amiloide (18F-florbetapir) en práctica clínica: evidencias preliminares. Rev Esp Med Nucl Imagen Mol 2022. [DOI: 10.1016/j.remn.2021.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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28
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Brodeur C, Belley É, Deschênes LM, Enriquez-Rosas A, Hubert M, Guimond A, Bilodeau J, Soucy JP, Macoir J. Primary and Secondary Progressive Aphasia in Posterior Cortical Atrophy. Life (Basel) 2022; 12:life12050662. [PMID: 35629330 PMCID: PMC9142989 DOI: 10.3390/life12050662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/20/2022] [Accepted: 04/25/2022] [Indexed: 12/26/2022] Open
Abstract
Background: Posterior cortical atrophy (PCA) is a clinico-radiological syndrome characterized by a progressive decline in visuospatial/visuoperceptual processing. PCA is accompanied by the impairment of other cognitive functions, including language abilities. Methods: The present study focused on three patients presenting with language complaints and a clinical profile that was compatible with PCA. In addition to neurological and neuroimaging examinations, they were assessed with comprehensive batteries of neuropsychological and neurolinguistic tests. Results: The general medical profile of the three patients is consistent with PCA, although they presented with confounding factors, making diagnosis less clear. The cognitive profile of the three patients was marked by Balint and Gerstmann’s syndromes as well as impairments affecting executive functions, short-term and working memory, visuospatial and visuoperceptual abilities, and sensorimotor execution abilities. Their language ability was characterized by word-finding difficulties and impairments of sentence comprehension, sentence repetition, verbal fluency, narrative speech, reading, and writing. Conclusions: This study confirmed that PCA is marked by visuospatial and visuoperceptual deficits and reported evidence of primary and secondary language impairments in the three patients. The similarities of some of their language impairments with those found in the logopenic variant of primary progressive aphasia is discussed from neurolinguistic and neuroanatomical points of view.
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Affiliation(s)
- Catherine Brodeur
- Institut Universitaire de Gériatrie de Montréal, Montreal, QC H3W 1W5, Canada; (C.B.); (A.E.-R.); (M.H.); (A.G.); (J.B.)
- Université de Montréal, Montreal, QC H3T 1J4, Canada;
- Centre de Recherche de l’IUGM, Montreal, QC H3W 1W6, Canada
| | - Émilie Belley
- Département de Réadaptation, Faculté de Médecine, Université Laval, Quebec, QC G1V 0A6, Canada; (É.B.); (L.-M.D.)
| | - Lisa-Marie Deschênes
- Département de Réadaptation, Faculté de Médecine, Université Laval, Quebec, QC G1V 0A6, Canada; (É.B.); (L.-M.D.)
| | - Adriana Enriquez-Rosas
- Institut Universitaire de Gériatrie de Montréal, Montreal, QC H3W 1W5, Canada; (C.B.); (A.E.-R.); (M.H.); (A.G.); (J.B.)
| | - Michelyne Hubert
- Institut Universitaire de Gériatrie de Montréal, Montreal, QC H3W 1W5, Canada; (C.B.); (A.E.-R.); (M.H.); (A.G.); (J.B.)
| | - Anik Guimond
- Institut Universitaire de Gériatrie de Montréal, Montreal, QC H3W 1W5, Canada; (C.B.); (A.E.-R.); (M.H.); (A.G.); (J.B.)
| | - Josée Bilodeau
- Institut Universitaire de Gériatrie de Montréal, Montreal, QC H3W 1W5, Canada; (C.B.); (A.E.-R.); (M.H.); (A.G.); (J.B.)
| | - Jean-Paul Soucy
- Université de Montréal, Montreal, QC H3T 1J4, Canada;
- McConnell Brain Imaging Centre, McGill University, Montreal, QC H3A 2B4, Canada
- Concordia University, Montreal, QC H4B 1R6, Canada
| | - Joël Macoir
- Département de Réadaptation, Faculté de Médecine, Université Laval, Quebec, QC G1V 0A6, Canada; (É.B.); (L.-M.D.)
- Centre de Recherche CERVO (CERVO Brain Research Centre), Quebec, QC G1J 2G3, Canada
- Correspondence: ; Tel.: +1-418-656-2131 (ext. 412190)
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29
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Giacomucci G, Mazzeo S, Padiglioni S, Bagnoli S, Belloni L, Ferrari C, Bracco L, Nacmias B, Sorbi S, Bessi V. Gender differences in cognitive reserve: implication for subjective cognitive decline in women. Neurol Sci 2022; 43:2499-2508. [PMID: 34625855 PMCID: PMC8918152 DOI: 10.1007/s10072-021-05644-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 09/29/2021] [Indexed: 01/02/2023]
Abstract
BACKGROUND Subjective Cognitive Decline (SCD) is a self-experienced decline in cognitive capacity with normal performance on standardized cognitive tests, showing to increase risk of Alzheimer's Disease (AD). Cognitive reserve seems to influence the progression from SCD to Mild Cognitive Impairment (MCI) and to AD. The aim of our study was to investigate gender differences in cognitive reserve evaluating how sex might modulate the role of cognitive reserve on SCD. METHODS We included 381 SCD patients who underwent clinical evaluation, neuropsychological assessment, evaluation of premorbid intelligence by the Test di Intelligenza Breve (TIB), cognitive complaints by the Memory Assessment Clinics Questionnaire (MAC-Q), and apolipoprotein E (APOE) genotyping. RESULTS The proportion between women and men was significantly different (68.7% [95% CI 63.9-73.4 vs 31.4%, 95% CI 26.6-36.0]). Women were younger than men at onset of SCD and at the baseline visit (p = 0.021), had lower years of education (p = 0.007), lower TIB scores (p < 0.001), and higher MAC-Q scores (p = 0.012). TIB was directly associated with age at onset of SCD in both women and men, while years of education was inversely associated with age at onset only in women. Multivariate analysis showed that sex influences TIB independently from years of education. TIB was directly associated with MAC-Q in men. CONCLUSIONS Sex interacts with premorbid intelligence and education level in influencing the age at onset and the severity of SCD. As the effect of education was different between men and women, we speculated that education might act as a minor contributor of cognitive reserve in women.
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Affiliation(s)
- Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, Florence, Italy
- Unit Clinic of Organizations Careggi University Hospital, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Laura Belloni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, Florence, Italy
- Unit Clinic of Organizations Careggi University Hospital, Florence, Italy
| | - Camilla Ferrari
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Laura Bracco
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy.
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Isella V, Crivellaro C, Formenti A, Musarra M, Pacella S, Morzenti S, Ferri F, Mapelli C, Gallivanone F, Guerra L, Appollonio I, Ferrarese C. Validity of cingulate–precuneus–temporo-parietal hypometabolism for single-subject diagnosis of biomarker-proven atypical variants of Alzheimer’s Disease. J Neurol 2022; 269:4440-4451. [PMID: 35347453 PMCID: PMC9293827 DOI: 10.1007/s00415-022-11086-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 11/14/2022]
Abstract
The aim of our study was to establish empirically to what extent reduced glucose uptake in the precuneus, posterior cingulate and/or temporo-parietal cortex (PCTP), which is thought to indicate brain amyloidosis in patients with dementia or MCI due to Alzheimer’s Disease (AD), permits to distinguish amyloid-positive from amyloid-negative patients with non-classical AD phenotypes at the single-case level. We enrolled 127 neurodegenerative patients with cognitive impairment and a positive (n. 63) or negative (n. 64) amyloid marker (cerebrospinal fluid or amy-PET). Three rating methods of FDG-PET scan were applied: purely qualitative visual interpretation of uptake images (VIUI), and visual reading assisted by a semi-automated and semi-quantitative tool: INLAB, provided by the Italian National Research Council, or Cortex ID Suite, marketed by GE Healthcare. Fourteen scans (11.0%) patients remained unclassified by VIUI or INLAB procedures, therefore, validity values were computed on the remaining 113 cases. The three rating approaches showed good total accuracy (77–78%), good to optimal sensitivity (81–93%), but poorer specificity (62–75%). VIUI showed the highest sensitivity and the lowest specificity, and also the highest proportion of unclassified cases. Cases with asymmetric temporo-parietal hypometabolism and a progressive aphasia or corticobasal clinical profile, in particular, tended to be rated as AD-like, even if biomarkers indicated non-amyloid pathology. Our findings provide formal support to the value of PCTP hypometabolism for single-level diagnosis of amyloid pathophysiology in atypical AD, but also highlight the risk of qualitative assessment to misclassify patients with non-AD PPA or CBS underpinned by asymmetric temporo-parietal hypometabolism.
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31
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Vogel JW, Tosun D. Multiple Cortical to Striatal Accumulation Trajectories of β-Amyloid: Do All Roads Lead to Rome? Neurology 2022; 98:695-696. [PMID: 35338076 DOI: 10.1212/wnl.0000000000200191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Jacob W Vogel
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.,Veterans Affairs San Francisco, CA, USA
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32
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Gan J, Wang XD, Shi Z, Yuan J, Zhang M, Liu S, Wang F, You Y, Jia P, Feng L, Xu J, Zhang J, Hu W, Chen Z, Ji Y. The Impact of Rotating Night Shift Work and Daytime Recharge on Cognitive Performance Among Retired Nurses. Front Aging Neurosci 2022; 13:827772. [PMID: 35145395 PMCID: PMC8821912 DOI: 10.3389/fnagi.2021.827772] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
IntroductionThe exact relationship between long-term shift work (SW) and cognitive impairment (CI) has been poorly understood. The effects of the long-term rotating night SW (RNSW) combining daytime recharge (DTR) on cognitive function were investigated.MethodsA total 920 retired nurses and 656 retired female teachers aged ≥50 years were analyzed. Participants who worked at least once per week for 8 hat night for more than 1 year were defined as the SW group, and those without a regular nighttime shift were defined as the control group. The associations among duration, frequency, and DTR of RNSW, and neuropsychological assessments were ascertained by regression models.ResultsParticipants with RNSW had a significantly higher proportion of mild CI (MCI), both amnestic MCI (aMCI) (14.4% in 11–20 years, p < 0.05, and 17.8% in > 20 years, p < 0.001) and non-amnestic MCI (naMCI) (8.1% in 11–20 years, p < 0.05), as well as dementia (1.5% in 1–10 years, and 11.7% in > 20 years, p < 0.05) compared to controls (8.4% with aMCI, 4.4% with naMCI, and 7.0% with dementia, respectively). There were significant negative relationships between general times of night SW and scores of Mini-Mental State Examination (MMSE) (R squared = 0.01, p = 0.0014) and Montreal Cognitive Assessment (MoCA) (R squared = 0.01, p = 0.0054). Participants with ≥1 h of DTR and ≥ 11 years of RNSW were about 2-fold more likely to experience MCI compared with the subjects in the control group, especially with 3–5 h (odds ratio [OR]: 2.35; 95% confidence interval: 1.49–3.68, p < 0.001).ConclusionThe long-term RNSW was associated with a higher risk of CI, especially aMCI and dementia, and the problem cannot be improved by DTR.
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Affiliation(s)
- Jinghuan Gan
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiao-Dan Wang
- Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Department of Neurology, Tianjin Huanhu Hospital, Tianjin Dementia Institute, Tianjin, China
| | - Zhihong Shi
- Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Department of Neurology, Tianjin Huanhu Hospital, Tianjin Dementia Institute, Tianjin, China
| | - Junliang Yuan
- NHC Key Laboratory of Mental Health (Peking University), Department of Neurology, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
| | - Meiyun Zhang
- Department of Neurology, Tianjin People’s Hospital, Tianjin, China
| | - Shuai Liu
- Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Department of Neurology, Tianjin Huanhu Hospital, Tianjin Dementia Institute, Tianjin, China
| | - Fei Wang
- Department of Neurology, Yuncheng Central Hospital of Shanxi Province, Yuncheng, China
| | - Yong You
- Department of Neurology, Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Peifei Jia
- Department of Neurology, The Second Affiliated Hospital of Baotou Medical College, Baotou, China
| | - Lisha Feng
- Department of Encephalopathy, Research Institute of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Junying Xu
- Department of Neurology, Tianjin Baodi People’s Hospital, Tianjin, China
| | - Jinhong Zhang
- Department of Neurology, Cangzhou People’s Hospital, Cangzhou, China
| | - Wenzheng Hu
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhichao Chen
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yong Ji
- Department of Neurology, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Tianjin Key Laboratory of Cerebrovascular and of Neurodegenerative Diseases, Department of Neurology, Tianjin Huanhu Hospital, Tianjin Dementia Institute, Tianjin, China
- *Correspondence: Yong Ji,
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Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer’s Disease. Brain Sci 2022; 12:brainsci12020146. [PMID: 35203910 PMCID: PMC8869882 DOI: 10.3390/brainsci12020146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/17/2022] [Accepted: 01/18/2022] [Indexed: 11/17/2022] Open
Abstract
Alzheimer’s disease (AD) does not present uniform symptoms or a uniform rate of progression in all cases. The classification of subtypes can be based on clinical symptoms or patterns of pathological brain alterations. Imaging techniques may allow for the identification of AD subtypes and their differentiation from other neurodegenerative diseases already at an early stage. In this review, the strengths and weaknesses of current clinical imaging methods are described. These include positron emission tomography (PET) to image cerebral glucose metabolism and pathological amyloid or tau deposits. Magnetic resonance imaging (MRI) is more widely available than PET. It provides information on structural or functional changes in brain networks and their relation to AD subtypes. Amyloid PET provides a very early marker of AD but does not distinguish between AD subtypes. Regional patterns of pathology related to AD subtypes are observed with tau and glucose PET, and eventually as atrophy patterns on MRI. Structural and functional network changes occur early in AD but have not yet provided diagnostic specificity.
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Coomans EM, Tomassen J, Ossenkoppele R, Golla SSV, den Hollander M, Collij LE, Weltings E, van der Landen S, Wolters EE, Windhorst AD, Barkhof F, de Geus EJ, Scheltens P, Visser PJ, van Berckel BNM, den Braber A. Genetically identical twins show comparable tau PET load and spatial distribution. Brain 2022; 145:3571-3581. [PMID: 35022652 PMCID: PMC9586544 DOI: 10.1093/brain/awac004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/05/2021] [Accepted: 11/26/2021] [Indexed: 11/13/2022] Open
Abstract
Tau accumulation starts during the preclinical phase of Alzheimer’s disease and is closely associated with cognitive decline. For preventive purposes, it is important to identify factors associated with tau accumulation and spread. Studying genetically identical twin-pairs may give insight into genetic and environmental contributions to tau pathology, as similarities in identical twin-pairs largely result from genetic factors, while differences in identical twin-pairs can largely be attributed to non-shared, environmental factors. This study aimed to examine similarities and dissimilarities in a cohort of genetically identical older twin-pairs in (i) tau load; and (ii) spatial distribution of tau, measured with 18F-flortaucipir PET. We selected 78 genetically identical twins (39 pairs; average age 73 ± 6 years), enriched for amyloid-β pathology and APOE ε4 carriership, who underwent dynamic 18F-flortaucipir PET. We extracted binding potentials (BPND) in entorhinal, temporal, widespread neocortical and global regions, and examined within-pair similarities in BPND using age and sex corrected intra-class correlations. Furthermore, we tested whether twin-pairs showed a more similar spatial 18F-flortaucipir distribution compared to non-twin pairs, and whether the participant’s co-twin could be identified solely based on the spatial 18F-flortaucipir distribution. Last, we explored whether environmental (e.g. physical activity, obesity) factors could explain observed differences in twins of a pair in 18F-flortaucipir BPND. On visual inspection, Alzheimer’s disease-like 18F-flortaucipir PET patterns were observed, and although we mainly identified similarities in twin-pairs, some pairs showed strong dissimilarities. 18F-flortaucipir BPND was correlated in twins in the entorhinal (r = 0.40; P = 0.01), neocortical (r = 0.59; P < 0.01) and global (r = 0.56; P < 0.01) regions, but not in the temporal region (r = 0.20; P = 0.10). The 18F-flortaucipir distribution pattern was significantly more similar between twins of the same pair [mean r = 0.27; standard deviation (SD) = 0.09] than between non-twin pairings of participants (mean r = 0.01; SD = 0.10) (P < 0.01), also after correcting for proxies of off-target binding. Based on the spatial 18F-flortaucipir distribution, we could identify with an accuracy of 86% which twins belonged to the same pair. Finally, within-pair differences in 18F-flortaucipir BPND were associated with within-pair differences in depressive symptoms (0.37 < β < 0.56), physical activity (−0.41 < β < −0.42) and social activity (−0.32 < β < −0.36) (all P < 0.05). Overall, identical twin-pairs were comparable in tau load and spatial distribution, highlighting the important role of genetic factors in the accumulation and spreading of tau pathology. Considering also the presence of dissimilarities in tau pathology in identical twin-pairs, our results additionally support a role for (potentially modifiable) environmental factors in the onset of Alzheimer’s disease pathological processes, which may be of interest for future prevention strategies.
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Affiliation(s)
- Emma M. Coomans
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Sandeep S. V. Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marijke den Hollander
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Lyduine E. Collij
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma Weltings
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sophie van der Landen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma E. Wolters
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Albert D. Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- UCL Institute of Neurology, London, UK
| | - Eco J.C. de Geus
- Department of Biological Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm Sweden
| | - Bart N. M. van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Biological Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Differential associations between neocortical tau pathology and blood flow with cognitive deficits in early-onset vs late-onset Alzheimer's disease. Eur J Nucl Med Mol Imaging 2022; 49:1951-1963. [PMID: 34997294 PMCID: PMC9016024 DOI: 10.1007/s00259-021-05669-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/20/2021] [Indexed: 12/23/2022]
Abstract
Purpose Early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD. Methods Seventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n = 35, age-at-PET = 59 ± 5, MMSE = 23 ± 4; LOAD: n = 44, age-at-PET = 71 ± 5, MMSE = 23 ± 4) underwent a 130-min dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital, and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language, and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition. Results Both region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipitoparietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND − 0.76 ≤ stβ ≤ − 0.48 vs LOAD − 0.18 ≤ stβ ≤ − 0.02; EOAD R1 0.37 ≤ stβ ≤ 0.84 vs LOAD − 0.25 ≤ stβ ≤ 0.16). Conclusions Compared to LOAD, the degree of lateral temporal and occipitoparietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05669-6.
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Migliaccio R, Cacciamani F. The temporal lobe in typical and atypical Alzheimer disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 187:449-466. [PMID: 35964987 DOI: 10.1016/b978-0-12-823493-8.00004-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Alzheimer disease (AD) is defined neuropathologically by abnormal extra-cellular β-amyloid plaques combined with intraneuronal tau aggregation. Patients sharing the same neuropathological features but presenting different clinical manifestations and evolutions have led to the notion of AD spectrum. This spectrum encompasses typical and atypical forms of AD. For all of them, specific parts of the temporal lobes, as well as their structural and functional connections with other brain regions, are affected. In typical amnestic late-onset Alzheimer's disease (>65 years old; LOAD), tau pathology gradually spreads to the brain from the medial temporal lobe (MTL). MTL is an inhomogeneous structure consisting of several subregions densely connected to each other and to other cortical and subcortical brain regions. These regions play a crucial role in the storage of information in episodic memory. In less common early-onset AD (<65 years old; EOAD), a large proportion of patients presents atypical clinical manifestations, in which memory impairment is not inaugural and predominant. Instead, these patients have predominant and/or isolated deficits in language, visuospatial, motor, or executive/behavioral functions. In atypical variants, brain damage is mainly centered on the posterior regions, with relative sparing of the MTL. However, the temporal lobe also appears to be variably and specifically damaged in some subtypes of EOAD. For example, the left superior temporal gyrus is the core of brain damage in the language variant, as well as the ventral regions of the temporal lobe play an important role in the clinic of the visual variant.
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Affiliation(s)
- Raffaella Migliaccio
- Paris Brain Institute, INSERM U1127, Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurology, Institut de la mémoire et de la maladie d'Alzheimer, Hôpital de la Pitié-Salpêtrière, Paris, France.
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McGinnis SM, Stern AM, Woods JK, Torre M, Feany MB, Miller MB, Silbersweig DA, Gale SA, Daffner KR. Case Study 1: A 55-Year-Old Woman With Progressive Cognitive, Perceptual, and Motor Impairments. J Neuropsychiatry Clin Neurosci 2022; 34:8-15. [PMID: 34763525 PMCID: PMC8813898 DOI: 10.1176/appi.neuropsych.21040114] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Scott M. McGinnis
- Department of Neurology, Division of Cognitive and Behavioral Neurology, Center for Brain/Mind Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Andrew M. Stern
- Department of Neurology, Division of Cognitive and Behavioral Neurology, Center for Brain/Mind Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Jared K. Woods
- Department of Pathology, Division of Neuropathology, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Matthew Torre
- Department of Pathology, Division of Neuropathology, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Mel B. Feany
- Department of Pathology, Division of Neuropathology, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Michael B. Miller
- Department of Pathology, Division of Neuropathology, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - David A. Silbersweig
- Department of Psychiatry, Center for Brain/Mind Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Seth A. Gale
- Department of Neurology, Division of Cognitive and Behavioral Neurology, Center for Brain/Mind Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston
| | - Kirk R. Daffner
- Department of Neurology, Division of Cognitive and Behavioral Neurology, Center for Brain/Mind Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston
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38
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Jellinger KA. Recent update on the heterogeneity of the Alzheimer’s disease spectrum. J Neural Transm (Vienna) 2021; 129:1-24. [DOI: 10.1007/s00702-021-02449-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/25/2021] [Indexed: 02/03/2023]
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Iaccarino L, La Joie R, Koeppe R, Siegel BA, Hillner BE, Gatsonis C, Whitmer RA, Carrillo MC, Apgar C, Camacho MR, Nosheny R, Rabinovici GD. rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data. Neuroimage 2021; 246:118775. [PMID: 34890793 DOI: 10.1016/j.neuroimage.2021.118775] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/12/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022] Open
Abstract
The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia-Evidence for Amyloid Scanning - Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7-0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87-0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.
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Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - Barry A Siegel
- Edward Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO, United States
| | - Bruce E Hillner
- Department of Medicine, Virginia Commonwealth University, Richmond, VA, United States
| | - Constantine Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, United States; Department of Biostatistics, Brown University School of Public Health, Providence, RI, United States
| | - Rachel A Whitmer
- Division of Research, Kaiser Permanente, Oakland, CA, United States; Department of Public Health Sciences, University of California Davis, Davis, CA, United States
| | - Maria C Carrillo
- Medical and Scientific Relations Division, Alzheimer's Association, Chicago, IL, United States
| | - Charles Apgar
- American College of Radiology, Reston, VA, United States
| | - Monica R Camacho
- San Francisco VA Medical Center, San Francisco, CA, United States; Northern California Institute for Research and Education (NCIRE), San Francisco, CA, United States
| | - Rachel Nosheny
- San Francisco VA Medical Center, San Francisco, CA, United States; Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.
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Pini L, Wennberg AM, Salvalaggio A, Vallesi A, Pievani M, Corbetta M. Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease. Ageing Res Rev 2021; 72:101482. [PMID: 34606986 DOI: 10.1016/j.arr.2021.101482] [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] [Received: 05/27/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
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Vipin A, Satish V, Saffari SE, Koh W, Lim L, Silva E, Nyu MM, Choong TM, Chua E, Lim L, Ng ASL, Chiew HJ, Ng KP, Kandiah N. Dementia in Southeast Asia: influence of onset-type, education, and cerebrovascular disease. Alzheimers Res Ther 2021; 13:195. [PMID: 34847922 PMCID: PMC8630908 DOI: 10.1186/s13195-021-00936-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/16/2021] [Indexed: 11/10/2022]
Abstract
Abstract
Background
Southeast Asia represents 10% of the global population, yet little is known about regional clinical characteristics of dementia and risk factors for dementia progression. This study aims to describe the clinico-demographic profiles of dementia in Southeast Asia and investigate the association of onset-type, education, and cerebrovascular disease (CVD) on dementia progression in a real-world clinic setting.
Methods
In this longitudinal study, participants were consecutive series of 1606 patients with dementia from 2010 to 2019 from a tertiary memory clinic from Singapore. The frequency of dementia subtypes stratified into young-onset (YOD; <65 years age-at-onset) and late-onset dementia (LOD; ≥65 years age-at-onset) was studied. Association of onset-type (YOD or LOD), years of lifespan education, and CVD on the trajectory of cognition was evaluated using linear mixed models. The time to significant cognitive decline was investigated using Kaplan-Meier analysis.
Results
Dementia of the Alzheimer’s type (DAT) was the most common diagnosis (59.8%), followed by vascular dementia (14.9%) and frontotemporal dementia (11.1%). YOD patients accounted for 28.5% of all dementia patients. Patients with higher lifespan education had a steeper decline in global cognition (p<0.001), with this finding being more pronounced in YOD (p=0.0006). Older patients with a moderate-to-severe burden of CVD demonstrated a trend for a faster decline in global cognition compared to those with a mild burden.
Conclusions
There is a high frequency of YOD with DAT being most common in our Southeast Asian memory clinic cohort. YOD patients with higher lifespan education and LOD patients with moderate-to-severe CVD experience a steep decline in cognition.
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Sun W, Zhang M, Zhang Y, Li B, Li Y. Brain Intrinsic Functional Activity in Relation to Metabolic Changes in Alzheimer's Disease: A Simultaneous PET/fMRI study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:3467-3470. [PMID: 34891986 DOI: 10.1109/embc46164.2021.9630966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Previous studies have shown that the intrinsic brain functional activity significantly reduced in a variety of regions of Alzheimer's disease (AD) patients. However, the associated underlying metabolic mechanism remains not clear. Brain activity is primarily driven by the dynamic activity of neurons and their interconnections, which are regulated by synapses and are closely related to glucose uptakes. Simultaneous FDG-PET/fMRI imaging provides a unique opportunity to measure the concurrent brain functional activity and cerebral glucose metabolism information. In this study, using simultaneous resting-state PET/fMRI imaging, we investigated the concurrent global intrinsic activity and metabolic signal changes in AD patients. Twenty-two controls and nineteen AD patients were included. We compared the whole-brain amplitude of low frequency fluctuations (ALFF) measured using fMRI imaging and glucose uptake maps acquired from PET imaging between the two groups. Both maps showed significant reductions in the precuneus and left inferior parietal lobule (IPL) in AD compared to the control groups. Moreover, the ALFF within the precuneus and left IPL were significantly correlated with the colocalized glucose metabolism. The ALFF in the left IPL was significantly correlated with patient cognitive performance evaluated using MMSE or MoCA. Our findings provide useful insights into the understanding of brain intrinsic functional-metabolic activity and its role in AD pathology.
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Huang Y, Li L, Jiang J. Radiogenomics of Alzheimer's disease: exploring gene related metabolic imaging markers. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:5772-5775. [PMID: 34892431 DOI: 10.1109/embc46164.2021.9630690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and considerably determined by genetic factors. Fluorodeoxyglucose positron emission tomography (FDG-PET) can reflect the functional state of glucose metabolism in the brain, and radiomic features of FDG-PET were considered as important imaging markers in AD. However, radiomic features are not highly interpretable, especially lack of explanation of underlying biological and molecular mechanisms. Therefore, this study used radiogenomics analysis to explore prognostic metabolic imaging markers by associating radiomics features and genetic data. In the study, we used the FDG-PET images and genotype data of 389 subjects (Cohort B) enrolled in the ADNI, including 109 AD, 134 healthy controls (HCs), 72 MCI non-converters (MCI-nc) and 74 MCI converters (MCI-c). Firstly, we performed a Genome-wide association study (GWAS) on the genotype data of 998 subjects (Cohort A), including 632 AD and 366 HCs after quality control (QC) steps to identify susceptibility loci as the gene features. Secondly, radiomics features were extracted from the preprocessed PET images. Thirdly, two-sample t-test, rank sum test and F-score were regarded as the feature selection step to select effective radiomic features. Fourthly, a support vector machine (SVM) was used to test the ability of the radiomic features to classify HCs, MCI and AD patients. Finally, we performed the Spearman correlation analysis on the genetic data and radiomic features. As a result, we identified rs429358 and rs2075650 as genome-wide significant signals. The radiomic approach achieved good classification abilities. Two prognostic FDG-PET radiomic features in the amygdala were proven to be correlated with the genetic data.
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Whitwell JL, Tosakulwong N, Weigand SD, Graff-Radford J, Ertekin-Taner N, Machulda MM, Duffy JR, Schwarz CG, Senjem ML, Jack CR, Lowe VJ, Josephs KA. Relationship of APOE, age at onset, amyloid and clinical phenotype in Alzheimer disease. Neurobiol Aging 2021; 108:90-98. [PMID: 34551374 DOI: 10.1016/j.neurobiolaging.2021.08.012] [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] [Received: 02/08/2021] [Revised: 08/13/2021] [Accepted: 08/18/2021] [Indexed: 11/26/2022]
Abstract
The apolipoprotein E (APOE) ε4 allele is the most well-established risk factor for Alzheimer's disease (AD), although its relationship to age at onset and clinical phenotype is unclear. We aimed to assess relationships between APOE genotype and age at onset, amyloid-beta (Aβ) deposition and typical versus atypical clinical presentations in AD. Frequency of APOE ε4 carriers by age at onset was assessed in 447 AD patients, 138 atypical AD patients recruited by the Neurodegenerative Research Group at Mayo Clinic, and 309 with typical AD from ADNI. APOE ε4 frequency increased with age at onset in atypical AD but showed a bell-shaped curve in typical AD where highest frequencies were observed between 65 and 70 years. Typical AD showed higher APOE ε4 frequencies than atypical AD only between the ages of 57 and 69 years. Global Aβ standard uptake value ratios did not differ according to APOE e4 status in either group. APOE genotype varies by both age at onset and clinical phenotype in AD, highlighting the heterogeneous nature of AD.
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Affiliation(s)
| | | | - Stephen D Weigand
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Mary M Machulda
- Department of Psychology and Psychiatry, Mayo Clinic, Rochester, MN, USA
| | - Joseph R Duffy
- Department of Neurology, 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
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Clinical Implications of Amyloid-Beta Accumulation in Occipital Lobes in Alzheimer's Continuum. Brain Sci 2021; 11:brainsci11091232. [PMID: 34573252 PMCID: PMC8470691 DOI: 10.3390/brainsci11091232] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/18/2021] [Accepted: 08/16/2021] [Indexed: 11/16/2022] Open
Abstract
A substantial amount of amyloid-beta (Aβ) accumulates in the occipital cortices; however, it draws less attention. We investigated the clinical implications of Aβ accumulation in the occipital lobes in the Alzheimer’s disease (AD) continuum. [18F]-Florbetaben amyloid PET scans were performed in a total of 121 AD or amnestic mild cognitive impairment (aMCI) patients. Of the 121 patients, 74 Aβ positive patients were divided into occipital Aβ positive (OCC+) and occipital Aβ negative (OCC−) groups based on Aβ accumulation in the bilateral occipital lobes. The OCC+ group (41/74, 55.4%) was younger and had a younger age at onset than the OCC− group. The OCC+ group also had an increased standard uptake value ratio in the occipital lobes and greater cortical thinning in relevant areas. The OCC+ group had a higher global deterioration scale, lower performance for the copy, immediate recall, delayed recall, and recognition in Rey–Osterrieth Complex Figure tests than the OCC- group, although both groups had similar disease durations. AD or aMCI patients in the OCC+ group exhibited features noted in early onset AD with relevant neuropsychological and image findings. Occipital Aβ positivity in amyloid PET scans need to be considered as an underestimated marker of early onset AD continuum.
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Bergeron D, Beauregard JM, Soucy JP, Verret L, Poulin S, Matias-Guiu JA, Cabrera-Martín MN, Bouchard RW, Laforce R. Posterior Cingulate Cortex Hypometabolism in Non-Amnestic Variants of Alzheimer's Disease. J Alzheimers Dis 2021; 77:1569-1577. [PMID: 32925054 DOI: 10.3233/jad-200567] [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: 11/15/2022]
Abstract
BACKGROUND Hypometabolism of the posterior cingulate cortex (PCC) is an important diagnostic feature of late-onset, amnestic Alzheimer's disease (AD) measured with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). However, it is unclear whether PCC hypometabolism has diagnostic value in young-onset, non-amnestic variants of AD, which exhibit less pathology in the hippocampus and default mode network. OBJECTIVE Evaluate the prevalence and diagnostic value of PCC hypometabolism in non-amnestic variants of AD. METHODS We retrospectively identified 60 patients with young-onset, atypical dementia who have undergone a detailed clinical evaluation, FDG-PET, and an amyloid biomarker (amyloid-PET or cerebrospinal fluid analysis). We quantitatively analyzed regional hypometabolism in 70 regions of interest (ROI) using the MIMneuro® software. RESULTS Based on a cut-off of z-score < -1.5 for significant PCC hypometabolism, the prevalence of PCC hypometabolism in non-amnestic variants of AD was 65% compared to 28% in clinical variants of frontotemporal dementia (FTD). The ROI with the maximal hypometabolism was the dominant middle temporal gyrus in the language variant of AD (mean z score -2.28), middle occipital gyrus in PCA (-3.24), middle temporal gyrus in frontal AD (-2.70), and angular gyrus in corticobasal syndrome due to AD (-2.31). The PCC was not among the 10 most discriminant regions between non-amnestic variants of AD versus clinical variants of FTD. CONCLUSION We conclude that PCC hypometabolism is not a discriminant feature to distinguish non-amnestic variants of AD from clinical variants of FTD-and should be interpreted with caution in patients with young-onset, non-amnestic dementia.
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Affiliation(s)
- David Bergeron
- Clinique Interdisciplinaire de Mémoire (CIME) du CHU de Québec, Québec, Canada
| | | | - Jean-Paul Soucy
- Department of Nuclear Medicine, Montreal Neurological Institute (MNI), Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Louis Verret
- Clinique Interdisciplinaire de Mémoire (CIME) du CHU de Québec, Québec, Canada
| | - Stéphane Poulin
- Clinique Interdisciplinaire de Mémoire (CIME) du CHU de Québec, Québec, Canada
| | - Jordi A Matias-Guiu
- Department of Neurology, San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Department of Neurology, San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Madrid, Spain
| | - Rémi W Bouchard
- Department of Neurology, San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Madrid, Spain
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire (CIME) du CHU de Québec, Québec, Canada
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47
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Strom A, Iaccarino L, Edwards L, Lesman-Segev OH, Soleimani-Meigooni DN, Pham J, Baker SL, Landau S, Jagust WJ, Miller BL, Rosen HJ, Gorno-Tempini ML, Rabinovici GD, La Joie R. Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease. Brain 2021; 145:713-728. [PMID: 34373896 PMCID: PMC9014741 DOI: 10.1093/brain/awab294] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 07/09/2021] [Accepted: 07/21/2021] [Indexed: 11/14/2022] Open
Abstract
Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.
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Affiliation(s)
- Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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Kim H, Chung JY. Pathobiolgy and Management of Alzheimer's Disease. Chonnam Med J 2021; 57:108-117. [PMID: 34123738 PMCID: PMC8167446 DOI: 10.4068/cmj.2021.57.2.108] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 01/02/2023] Open
Abstract
Amyloid and tau protein abnormalities have been identified as the main causes of Alzheimer's disease but exact mechanisms remain to be revealed. Especially, amyloid beta and tau protein coupling and neuroinflammatory and neurovascular contributions to Alzheimer disease are quite mysterious. Many animal models and basic biological research are trying to solve these puzzles. Known as aging processes, autophagy, mitochondrial degeneration with generation of reactive oxygen species, and age-related epigenetic modifications are also known to be associated with development of Alzheimer's disease. Environmental factors such as bacterial and viral infections, heavy metal ions, diet, sleep, stress, and gut microbiota are also risk factors of Alzheimer's disease. Future development of preventive and therapeutic modalities may be dependent on the pathobiology of Alzheimer's disease.
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Affiliation(s)
- Hoowon Kim
- Department of Neurology, Chosun University Hospital, Gwangju, Korea
| | - Ji Yeon Chung
- Department of Neurology, Chosun University Hospital, Gwangju, Korea
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49
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Groot C, Risacher SL, Chen JQA, Dicks E, Saykin AJ, Mac Donald CL, Mez J, Trittschuh EH, Mukherjee S, Barkhof F, Scheltens P, van der Flier WM, Ossenkoppele R, Crane PK. Differential trajectories of hypometabolism across cognitively-defined Alzheimer's disease subgroups. NEUROIMAGE-CLINICAL 2021; 31:102725. [PMID: 34153688 PMCID: PMC8238088 DOI: 10.1016/j.nicl.2021.102725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 05/28/2021] [Accepted: 06/08/2021] [Indexed: 11/26/2022]
Abstract
Cognitive-subgroups can be identified among individuals
with AD dementia. Subgroup-specific patterns and longitudinal trajectories of
hypometabolism observed. Regional hypometabolism matched respective cognitive
profiles of subgroups. Cognitive-classification yields biologically distinct
subgroups.
Disentangling biologically distinct subgroups of Alzheimer’s
disease (AD) may facilitate a deeper understanding of the neurobiology underlying
clinical heterogeneity. We employed longitudinal [18F]FDG-PET
standardized uptake value ratios (SUVRs) to map hypometabolism across
cognitively-defined AD subgroups. Participants were 384 amyloid-positive individuals
with an AD dementia diagnosis from ADNI who had a total of 1028 FDG-scans (mean time
between first and last scan: 1.6 ± 1.8 years). These participants were categorized
into subgroups on the basis of substantial impairment at time of dementia diagnosis
in a specific cognitive domain relative to the average across domains. This approach
resulted in groups of AD-Memory (n = 135), AD-Executive (n = 8), AD-Language
(n = 22), AD-Visuospatial (n = 44), AD-Multiple Domains (n = 15) and AD-No Domains
(for whom no domain showed substantial relative impairment; n = 160). Voxelwise
contrasts against controls revealed that all AD-subgroups showed progressive
hypometabolism compared to controls across temporoparietal regions at time of AD
diagnosis. Voxelwise and regions-of-interest (ROI)-based linear mixed model analyses
revealed there were also subgroup-specific hypometabolism patterns and trajectories.
The AD-Memory group had more pronounced hypometabolism compared to all other groups
in the medial temporal lobe and posterior cingulate, and faster decline in metabolism
in the medial temporal lobe compared to AD-Visuospatial. The AD-Language group had
pronounced lateral temporal hypometabolism compared to all other groups, and the
pattern of metabolism was also more asymmetrical (left < right) than all other
groups. The AD-Visuospatial group had faster decline in metabolism in parietal
regions compared to all other groups, as well as faster decline in the precuneus
compared to AD-Memory and AD-No Domains. Taken together, in addition to a common
pattern, cognitively-defined subgroups of people with AD dementia show
subgroup-specific hypometabolism patterns, as well as differences in trajectories of
metabolism over time. These findings provide support to the notion that
cognitively-defined subgroups are biologically distinct.
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Affiliation(s)
- Colin Groot
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | | | - J Q Alida Chen
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Ellen Dicks
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Andrew J Saykin
- Indiana University School of Medicine, Indianapolis, IN, USA.
| | | | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Alzheimer's Disease Center, Boston University School of Medicine, MA, USA.
| | - Emily H Trittschuh
- Psychiatry & Behavioral Science, University of Washington, Seattle, WA, USA; Veterans Affairs Puget Sound Health Care System, Geriatric Research, Education, & Clinical Center, Seattle, WA, USA
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; University College London, Institutes of Neurology & Healthcare Engineering, London, United Kingdom.
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Rik Ossenkoppele
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Lund University, Clinical Memory Research Unit, Lund, Sweden.
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
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50
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Jellinger KA. Pathobiological Subtypes of Alzheimer Disease. Dement Geriatr Cogn Disord 2021; 49:321-333. [PMID: 33429401 DOI: 10.1159/000508625] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 05/11/2020] [Indexed: 11/19/2022] Open
Abstract
Alzheimer disease (AD), the most common form of dementia, is a heterogenous disorder with various pathobiological subtypes. In addition to the 4 major subtypes based on the distribution of tau pathology and brain atrophy (typical, limbic predominant, hippocampal sparing, and minimal atrophy [MA]), several other clinical variants showing distinct regional patterns of tau burden have been identified: nonamnestic, corticobasal syndromal, primary progressive aphasia, posterior cortical atrophy, behavioral/dysexecutive, and mild dementia variants. Among the subtypes, differences were found in age at onset, sex distribution, cognitive status, disease duration, APOE genotype, and biomarker levels. The patterns of key network destructions parallel the tau and atrophy patterns of the AD subgroups essentially. Interruption of key networks, in particular the default-mode network that is responsible for cognitive decline, is consistent in hetero-genous AD groups. AD pathology is often associated with co-pathologies: cerebrovascular lesions, Lewy pathology, and TDP-43 proteinopathies. These mixed pathologies essentially influence the clinical picture of AD and may accel-erate disease progression. Unraveling the heterogeneity among the AD spectrum entities is important for opening a window to pathogenic mechanisms affecting the brain and enabling precision medicine approaches as a basis for developing preventive and ultimately successful disease-modifying therapies for AD.
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