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Li C, Wang S, Xia Y, Shi F, Tang L, Yang Q, Feng J, Li C. Risk factors and predictive models in the progression from MCI to Alzheimer's disease. Neuroscience 2025; 565:312-319. [PMID: 39645072 DOI: 10.1016/j.neuroscience.2024.11.056] [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: 09/23/2024] [Revised: 11/17/2024] [Accepted: 11/22/2024] [Indexed: 12/09/2024]
Abstract
BACKGROUND The conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD) is related to various factors. The causal relationships among these factors remain unclear. This study aims to investigate pathways of the progression by using causal analysis and build a predictive model with high accuracy. METHODS 162 MCI patients were recruited from the Alzheimer's Disease Neuroimaging Initiative database. 68 patients progressed to AD. 94 patients did not convert to AD. We captured standard T1-weighted images, processed them for feature extraction, and selected relevant features using mRMR and LASSO to calculate cortical and nuclear scores. The computational causal structure discovery and regression analyses were adopted to analyze the intricate relationships among APOE ε4 alleles, P-tau, Aβ1-42, cortical and nuclear scores. The individualized prediction nomogram was constructed. RESULTS Our results indicated that APOE ε4 alleles was the promoter that caused MCI to transform into AD. Three independent pathways were identified, including P-tau, Aβ1-42, and cortical atrophy. P-tau was the cause of nuclear atrophy. The APOE ε4 alleles, P-tau, Aβ1-42, cortical and nuclear scores all had good predictive value for the MCI conversion. The predictive accuracy of the combined model was the highest, with an AUC of 0.918 in the training cohort and 0.908 in the testing cohort. A multi-predictor nomogram was established. CONCLUSION Our study elucidated the initiating factors and three independent pathways involved in the conversion of MCI to AD. The predictive value of each factor was clarified and a multi-predictor nomogram was established with high accuracy.
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Affiliation(s)
- Chang Li
- Bioengineering College of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, 400030 China
| | - Shike Wang
- Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400030 China
| | - Yuwei Xia
- Shanghai United Imaging Intelligence, Shanghai, 200082 China
| | - Feng Shi
- Shanghai United Imaging Intelligence, Shanghai, 200082 China
| | - Lin Tang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, 400030 China
| | - Qingning Yang
- Bioengineering College of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, 400030 China
| | - Junbang Feng
- Bioengineering College of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, 400030 China.
| | - Chuanming Li
- Bioengineering College of Chongqing University, Chongqing University Central Hospital (Chongqing Emergency Medical Center), Chongqing, 400030 China.
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Asken BM, Brett BL, Barr WB, Banks S, Wethe JV, Dams-O'Connor K, Stern RA, Alosco ML. Chronic traumatic encephalopathy: State-of-the-science update and narrative review. Clin Neuropsychol 2025:1-25. [PMID: 39834035 DOI: 10.1080/13854046.2025.2454047] [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: 08/07/2024] [Accepted: 01/10/2025] [Indexed: 01/22/2025]
Abstract
OBJECTIVE The long-recognized association of brain injury with increased risk of dementia has undergone significant refinement and more detailed study in recent decades. Chronic traumatic encephalopathy (CTE) is a specific neurodegenerative tauopathy related to prior exposure to repetitive head impacts (RHI). We aim to contextualize CTE within a historical perspective and among emerging data which highlights the scientific and conceptual evolution of CTE-related research in parallel with the broader field of neurodegenerative disease and dementia. METHODS We provide a narrative state-of-the-science update on CTE neuropathology, clinical manifestations, biomarkers, different types and patterns of head impact exposure relevant for CTE, and the complicated influence of neurodegenerative co-pathology on symptoms. CONCLUSIONS Now almost 20 years since the initial case report of CTE in a former American football player, the field of CTE continues evolving with increasing clarity but also several ongoing controversies. Our understanding of CTE neuropathology outpaces that of disease-specific clinical correlates or the development of in-vivo biomarkers. Diagnostic criteria for symptoms attributable to CTE are still being validated, but leveraging increasingly available biomarkers for other conditions like Alzheimer's disease may be helpful for informing the CTE differential diagnosis. As diagnostic refinement efforts advance, clinicians should provide care and/or referrals to providers best suited to treat an individual patient's clinical symptoms, many of which have evidence-based behavioral treatment options that are etiologically agnostic. Several ongoing research initiatives and the gradual accrual of gold standard clinico-pathological data will pay dividends for advancing the many existing gaps in the field of CTE.
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Affiliation(s)
- Breton M Asken
- Department of Clinical and Health Psychology, University of Florida, 1Florida Alzheimer's Disease Research Center, Gainesville, FL, USA
| | - Benjamin L Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WS, USA
| | - William B Barr
- Department of Neurology, New York University Langone Health Medical Center, New York, NY, USA
| | - Sarah Banks
- Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Jennifer V Wethe
- Departments of Psychiatry and Psychology, Mayo Clinic, Phoenix, AZ, USA
| | - Kristen Dams-O'Connor
- Departments of Rehabilitation Medicine and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert A Stern
- Departments of Neurology, Neurosurgery, and Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston University CTE and Alzheimer's Disease Research Centers, Boston, MA, USA
| | - Michael L Alosco
- Departments of Neurology and Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston University CTE and Alzheimer's Disease Research Centers, Boston, MA, USA
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Ferraro PM, Filippi L, Ponzano M, Signori A, Orso B, Massa F, Arnaldi D, Caneva S, Argenti L, Losa M, Lombardo L, Mattioli P, Costagli M, Gualco L, Pulze M, Plantone D, Brugnolo A, Girtler N, Diociasi A, Garbarino S, Villani F, Sormani MP, Uccelli A, Roccatagliata L, Pardini M. Clinical and biological underpinnings of longitudinal atrophy pattern progression in Alzheimer's disease. J Alzheimers Dis 2025; 103:243-255. [PMID: 39587787 DOI: 10.1177/13872877241299843] [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] [Indexed: 11/27/2024]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) has recently enabled to identify four distinct Alzheimer's disease (AD) subtypes: hippocampal sparing (HpSp), typical AD (tAD), limbic predominant (Lp), and minimal atrophy (MinAtr). To date, however, the natural history of these subtypes, especially regarding the presence of subjects switching to other MRI patterns and their clinical and biological differences, remains poorly understood. OBJECTIVE To investigate the clinical and biological underpinnings of longitudinal atrophy pattern progression in AD. METHODS 251 AD patients (16 with significant memory concern, 66 with early mild cognitive impairment (MCI), 125 with late MCI, and 44 with AD dementia) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were assigned to their baseline MRI atrophy subtype using Freesurfer-derived cortical:hippocampal volumes ratio. Switching to other MRI patterns was investigated on longitudinal scans, and patients were accordingly classified as "switching" and "stable". Logistic regression models were applied to identify predictors of switching to other MRI patterns. RESULTS 40% of Lp, 26% of HpSp, and 35% of MinAtr cases switched to other MRI patterns, with tAD representing the destination subtype of all switching HpSp and Lp, and the majority of MinAtr. At baseline significant clinical, cognitive and biomarkers differences were observed across the four subtypes. Only clinical and cognitive variables, however, were significantly associated with switch to other MRI patterns. CONCLUSIONS Our results suggest convergent directions of disease progression across atypical and typical AD forms, at least in a subset of AD subjects, and highlight the importance of deep-phenotyping approaches to understand AD heterogeneity.
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Affiliation(s)
| | - Laura Filippi
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Marta Ponzano
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Alessio Signori
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Beatrice Orso
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Federico Massa
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Dario Arnaldi
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Stefano Caneva
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Lucia Argenti
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Mattia Losa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Lorenzo Lombardo
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Pietro Mattioli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Mauro Costagli
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | | | - Martina Pulze
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Domenico Plantone
- Centre for Precision and Translational Medicine, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Andrea Brugnolo
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Nicola Girtler
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Andrea Diociasi
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | | | | | - Maria Pia Sormani
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Antonio Uccelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Luca Roccatagliata
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Matteo Pardini
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
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Wheatley SH, Mohanty R, Poulakis K, Levin F, Muehlboeck JS, Nordberg A, Grothe MJ, Ferreira D, Westman E. Divergent neurodegenerative patterns: Comparison of [ 18F] fluorodeoxyglucose-PET- and MRI-based Alzheimer's disease subtypes. Brain Commun 2024; 6:fcae426. [PMID: 39703327 PMCID: PMC11656166 DOI: 10.1093/braincomms/fcae426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 09/23/2024] [Accepted: 11/21/2024] [Indexed: 12/21/2024] Open
Abstract
[18F] fluorodeoxyglucose (FDG)-PET and MRI are key imaging markers for neurodegeneration in Alzheimer's disease. It has been well established that parieto-temporal hypometabolism on FDG-PET is closely associated with medial temporal atrophy on MRI in Alzheimer's disease. Substantial biological heterogeneity, expressed as distinct subtypes of hypometabolism or atrophy patterns, has been previously described in Alzheimer's disease using data-driven and hypothesis-driven methods. However, the link between these two imaging modalities has not yet been explored in the context of Alzheimer's disease subtypes. To investigate this link, the current study utilized FDG-PET and MRI scans from 180 amyloid-beta positive Alzheimer's disease dementia patients, 339 amyloid-beta positive mild cognitive impairment and 176 amyloid-beta negative cognitively normal controls from the Alzheimer's Disease Neuroimaging Initiative. Random forest hierarchical clustering, a data-driven model for identifying subtypes, was implemented in the two modalities: one with standard uptake value ratios and the other with grey matter volumes. Five hypometabolism- and atrophy-based subtypes were identified, exhibiting both cortical-predominant and limbic-predominant patterns although with differing percentages and clinical presentations. Three cortical-predominant hypometabolism subtypes found were Cortical Predominant (32%), Cortical Predominant+ (11%) and Cortical Predominant posterior (8%), and two limbic-predominant hypometabolism subtypes found were Limbic Predominant (36%) and Limbic Predominant frontal (13%). In addition, little atrophy (minimal) and widespread (diffuse) neurodegeneration subtypes were observed from the MRI data. The five atrophy subtypes found were Cortical Predominant (19%), Limbic Predominant (27%), Diffuse (29%), Diffuse+ (6%) and Minimal (19%). Inter-modality comparisons showed that all FDG-PET subtypes displayed medial temporal atrophy, whereas the distinct MRI subtypes showed topographically similar hypometabolic patterns. Further, allocations of FDG-PET and MRI subtypes were not consistent when compared at an individual level. Additional analysis comparing the data-driven clustering model with prior hypothesis-driven methods showed only partial agreement between these subtyping methods. FDG-PET subtypes had greater differences between limbic-predominant and cortical-predominant patterns, and MRI subtypes had greater differences in severity of atrophy. In conclusion, this study highlighted that Alzheimer's disease subtypes identified using both FDG-PET and MRI capture distinct pathways showing cortical versus limbic predominance of neurodegeneration. However, the subtypes do not share a bidirectional relationship between modalities and are thus not interchangeable.
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Affiliation(s)
- Sophia H Wheatley
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Rosaleena Mohanty
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Konstantinos Poulakis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Fedor Levin
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), 18147 Rostock, Germany
| | - J Sebastian Muehlboeck
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Michel J Grothe
- Reina Sofia Alzheimer Centre, CIEN Foundation, ISCIII, 28031 Madrid, Spain
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, 35016 Las Palmas, España
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, 171 77 Stockholm, Sweden
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Boccalini C, Caminiti SP, Chiti A, Frisoni GB, Garibotto V, Perani D. The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes. Ann Clin Transl Neurol 2024; 11:1236-1249. [PMID: 38553802 PMCID: PMC11093253 DOI: 10.1002/acn3.52039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 02/21/2024] [Accepted: 02/26/2024] [Indexed: 05/15/2024] Open
Abstract
OBJECTIVES Mild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, including brain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up. METHODS We included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data. RESULTS The algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline. INTERPRETATION aMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.
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Affiliation(s)
- Cecilia Boccalini
- Vita‐Salute San Raffaele UniversityMilanItaly
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Silvia Paola Caminiti
- Vita‐Salute San Raffaele UniversityMilanItaly
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Arturo Chiti
- Vita‐Salute San Raffaele UniversityMilanItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicGeneva University HospitalsGenevaSwitzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Division of Nuclear Medicine and Molecular ImagingGeneva University HospitalsGenevaSwitzerland
- CIBM Center for Biomedical ImagingGenevaSwitzerland
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
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Mohanty R, Ferreira D, Westman E. Multi-pathological contributions toward atrophy patterns in the Alzheimer's disease continuum. Front Neurosci 2024; 18:1355695. [PMID: 38655107 PMCID: PMC11036869 DOI: 10.3389/fnins.2024.1355695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/07/2024] [Indexed: 04/26/2024] Open
Abstract
Introduction Heterogeneity in downstream atrophy in Alzheimer's disease (AD) is predominantly investigated in relation to pathological hallmarks (Aβ, tau) and co-pathologies (cerebrovascular burden) independently. However, the proportional contribution of each pathology in determining atrophy pattern remains unclear. We assessed heterogeneity in atrophy using two recently conceptualized dimensions: typicality (typical AD atrophy at the center and deviant atypical atrophy on either extreme including limbic predominant to hippocampal sparing patterns) and severity (overall neurodegeneration spanning minimal atrophy to diffuse typical AD atrophy) in relation to Aβ, tau, and cerebrovascular burden. Methods We included 149 Aβ + individuals on the AD continuum (cognitively normal, prodromal AD, AD dementia) and 163 Aβ- cognitively normal individuals from the ADNI. We modeled heterogeneity in MRI-based atrophy with continuous-scales of typicality (ratio of hippocampus to cortical volume) and severity (total gray matter volume). Partial correlation models investigated the association of typicality/severity with (a) Aβ (global Aβ PET centiloid), tau (global tau PET SUVR), cerebrovascular (total white matter hypointensity volume) burden (b) four cognitive domains (memory, executive function, language, visuospatial composites). Using multiple regression, we assessed the association of each pathological burden and typicality/severity with cognition. Results (a) In the AD continuum, typicality (r = -0.31, p < 0.001) and severity (r = -0.37, p < 0.001) were associated with tau burden after controlling for Aβ, cerebrovascular burden and age. Findings imply greater tau pathology in limbic predominant atrophy and diffuse atrophy. (b) Typicality was associated with memory (r = 0.49, p < 0.001) and language scores (r = 0.19, p = 0.02). Severity was associated with memory (r = 0.26, p < 0.001), executive function (r = 0.24, p = 0.003) and language scores (r = 0.29, p < 0.001). Findings imply better cognitive performance in hippocampal sparing and minimal atrophy patterns. Beyond typicality/severity, tau burden but not Aβ and cerebrovascular burden explained cognition. Conclusion In the AD continuum, atrophy-based severity was more strongly associated with tau burden than typicality after accounting for Aβ and cerebrovascular burden. Cognitive performance in memory, executive function and language domains was explained by typicality and/or severity and additionally tau pathology. Typicality and severity may differentially reflect burden arising from tau pathology but not Aβ or cerebrovascular pathologies which need to be accounted for when investigating AD heterogeneity.
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Affiliation(s)
- Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas, Spain
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Karolinska Institutet, Huddinge, Sweden
- Department of Neuroimaging, Center for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, United Kingdom
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Petersen SI, Okolicsanyi RK, Haupt LM. Exploring Heparan Sulfate Proteoglycans as Mediators of Human Mesenchymal Stem Cell Neurogenesis. Cell Mol Neurobiol 2024; 44:30. [PMID: 38546765 PMCID: PMC10978659 DOI: 10.1007/s10571-024-01463-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/19/2024] [Indexed: 04/01/2024]
Abstract
Alzheimer's disease (AD) and traumatic brain injury (TBI) are major public health issues worldwide, with over 38 million people living with AD and approximately 48 million people (27-69 million) experiencing TBI annually. Neurodegenerative conditions are characterised by the accumulation of neurotoxic amyloid beta (Aβ) and microtubule-associated protein Tau (Tau) with current treatments focused on managing symptoms rather than addressing the underlying cause. Heparan sulfate proteoglycans (HSPGs) are a diverse family of macromolecules that interact with various proteins and ligands and promote neurogenesis, a process where new neural cells are formed from stem cells. The syndecan (SDC) and glypican (GPC) HSPGs have been implicated in AD pathogenesis, acting as drivers of disease, as well as potential therapeutic targets. Human mesenchymal stem cells (hMSCs) provide an attractive therapeutic option for studying and potentially treating neurodegenerative diseases due to their relative ease of isolation and subsequent extensive in vitro expansive potential. Understanding how HSPGs regulate protein aggregation, a key feature of neurodegenerative disorders, is essential to unravelling the underlying disease processes of AD and TBI, as well as any link between these two neurological disorders. Further research may validate HSPG, specifically SDCs or GPCs, use as neurodegenerative disease targets, either via driving hMSC stem cell therapy or direct targeting.
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Affiliation(s)
- Sofia I Petersen
- Stem Cell and Neurogenesis Group, School of Biomedical Sciences, Genomics Research Centre, Centre for Genomics and Personalised Health, Queensland University of Technology (QUT), 60 Musk Ave, Kelvin Grove, QLD, 4059, Australia
| | - Rachel K Okolicsanyi
- Stem Cell and Neurogenesis Group, School of Biomedical Sciences, Genomics Research Centre, Centre for Genomics and Personalised Health, Queensland University of Technology (QUT), 60 Musk Ave, Kelvin Grove, QLD, 4059, Australia
- Max Planck Queensland Centre for the Materials Sciences of Extracellular Matrices, Kelvin Grove, Australia
| | - Larisa M Haupt
- Stem Cell and Neurogenesis Group, School of Biomedical Sciences, Genomics Research Centre, Centre for Genomics and Personalised Health, Queensland University of Technology (QUT), 60 Musk Ave, Kelvin Grove, QLD, 4059, Australia.
- ARC Training Centre for Cell and Tissue Engineering Technologies, Queensland University of Technology (QUT), Kelvin Grove, Australia.
- Max Planck Queensland Centre for the Materials Sciences of Extracellular Matrices, Kelvin Grove, Australia.
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Pang M, Gabelle A, Saha‐Chaudhuri P, Huijbers W, Gafson A, Matthews PM, Tian L, Rubino I, Hughes R, de Moor C, Belachew S, Shen C. Precision medicine analysis of heterogeneity in individual-level treatment response to amyloid beta removal in early Alzheimer's disease. Alzheimers Dement 2024; 20:1102-1111. [PMID: 37882364 PMCID: PMC10917030 DOI: 10.1002/alz.13431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/27/2023] [Accepted: 07/23/2023] [Indexed: 10/27/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) is a neurological disorder with variability in pathology and clinical progression. AD patients may differ in individual-level benefit from amyloid beta removal therapy. METHODS Random forest models were applied to the EMERGE trial to create an individual-level treatment response (ITR) score which represents individual-level benefit of high-dose aducanumab relative to the placebo. This ITR score was used to test the existence of heterogeneity in treatment effect (HTE). RESULTS We found statistical evidence of HTE in the Clinical Dementia Rating-Sum of Boxes (CDR-SB;P = 0.034). The observed CDR-SB benefit was 0.79 points greater in the group with the top 25% of ITR score compared to the remaining 75% (P = 0.020). Of note, the highest treatment responders had lower hippocampal volume, higher plasma phosphorylated tau 181 and a shorter duration of clinical AD at baseline. DISCUSSION This ITR analysis provides a proof of concept for precision medicine in future AD research and drug development. HIGHLIGHTS Emerging trials have shown a population-level benefit from amyloid beta (Aβ) removal in slowing cognitive decline in early Alzheimer's disease (AD). This work demonstrates significant heterogeneity of individual-level treatment effect of aducanumab in early AD. The greatest clinical responders to Aβ removal therapy have a pattern of more severe neurodegenerative process.
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Affiliation(s)
- Menglan Pang
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Audrey Gabelle
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | | | - Willem Huijbers
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Arie Gafson
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Paul M. Matthews
- Department of Brain SciencesFaculty of MedicineImperial College LondonLondonUK
- UK Dementia Research Institute at Imperial College LondonLondonUK
| | - Lu Tian
- Biomedical Data Science and StatisticsStanford University School of MedicineStanfordCaliforniaUSA
| | | | - Richard Hughes
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Carl de Moor
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Shibeshih Belachew
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
| | - Changyu Shen
- Biogen Digital HealthBiogenCambridgeMassachusettsUSA
- BiogenCambridgeMassachusettsUSA
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Veitch DP, Weiner MW, Miller M, Aisen PS, Ashford MA, Beckett LA, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Nho KT, Nosheny R, Okonkwo O, Perrin RJ, Petersen RC, Rivera Mindt M, Saykin A, Shaw LM, Toga AW, Tosun D. The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022. Alzheimers Dement 2024; 20:652-694. [PMID: 37698424 PMCID: PMC10841343 DOI: 10.1002/alz.13449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 09/13/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Melanie Miller
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Miriam A. Ashford
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Laurel A. Beckett
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | - Robert C. Green
- Division of GeneticsDepartment of MedicineBrigham and Women's HospitalBroad Institute Ariadne Labs and Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Kwangsik T. Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rachel Nosheny
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | - Monica Rivera Mindt
- Department of PsychologyLatin American and Latino Studies InstituteAfrican and African American StudiesFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine and the PENN Alzheimer's Disease Research CenterCenter for Neurodegenerative ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingInstitute of Neuroimaging and InformaticsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
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10
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Hanyu H, Koyama Y, Horita H, Watanabe S, Sato T, Kanetaka H, Shimizu S, Hirao K. Longitudinal patterns of Alzheimer's disease subtypes: A follow-up magnetic resonance imaging and single-photon emission computed tomography study. Geriatr Gerontol Int 2023; 23:919-924. [PMID: 37905589 DOI: 10.1111/ggi.14712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 09/21/2023] [Accepted: 10/07/2023] [Indexed: 11/02/2023]
Abstract
AIM Alzheimer's disease (AD) is a biologically heterogenous disease. In a previous study, we classified 245 patients with probable AD into the typical AD (TAD), limbic-predominant (LP), hippocampal-sparing (HS) and minimal-change (MC) subtypes based on their medial temporal lobe atrophy on magnetic resonance imaging and posterior hypoperfusion on single-photon emission computed tomography, and described differences in clinical features among the patients with different AD subtypes. This study aimed to clarify the longitudinal patterns of changes in patients with the various AD subtypes by follow-up brain imaging analyses. METHODS Follow-up magnetic resonance imaging or single-photon emission computed tomography data obtained 12-48 months after the first brain imaging were investigated in 79 patients with probable AD, comprising 25 of the TAD subtype, 19 of the LP subtype, 17 of the HS subtype and 18 of the MC subtype. RESULTS All patients of the TAD subtype remained as the same subtype at follow up. Approximately 37% of patients of the LP subtype and 29% of patients of the HS subtype progressed to the TAD subtype, and 17%, 33% and 6% of the MC subtype progressed to the TAD, LP and HS subtypes, respectively. The group of patients showing subtype progression was associated only with a longer follow-up duration. CONCLUSIONS There might be different progression patterns and progression rates of changes among the atypical AD subtypes. Further longitudinal brain imaging studies might provide information regarding the pathophysiological association between the various AD subtypes, and might be helpful for determining appropriate therapies and management methods. Geriatr Gerontol Int 2023; 23: 919-924.
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Affiliation(s)
- Haruo Hanyu
- Dementia Research Center, Tokyo General Hospital, Tokyo, Japan
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Yumi Koyama
- Department of Rehabilitation, Tokyo General Hospital, Tokyo, Japan
| | - Haruka Horita
- Department of Rehabilitation, Tokyo General Hospital, Tokyo, Japan
| | | | - Tomohiko Sato
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Hidekazu Kanetaka
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Soichiro Shimizu
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
| | - Kentaro Hirao
- Department of Geriatric Medicine, Tokyo Medical University, Tokyo, Japan
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11
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Silva-Rodríguez J, Labrador-Espinosa MA, Moscoso A, Schöll M, Mir P, Grothe MJ. Characteristics of amnestic patients with hypometabolism patterns suggestive of Lewy body pathology. Brain 2023; 146:4520-4531. [PMID: 37284793 PMCID: PMC10629761 DOI: 10.1093/brain/awad194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/27/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023] Open
Abstract
A clinical diagnosis of Alzheimer's disease dementia (ADD) encompasses considerable pathological and clinical heterogeneity. While Alzheimer's disease patients typically show a characteristic temporo-parietal pattern of glucose hypometabolism on 18F-fluorodeoxyglucose (FDG)-PET imaging, previous studies have identified a subset of patients showing a distinct posterior-occipital hypometabolism pattern associated with Lewy body pathology. Here, we aimed to improve the understanding of the clinical relevance of these posterior-occipital FDG-PET patterns in patients with Alzheimer's disease-like amnestic presentations. Our study included 1214 patients with clinical diagnoses of ADD (n = 305) or amnestic mild cognitive impairment (aMCI, n = 909) from the Alzheimer's Disease Neuroimaging Initiative, who had FDG-PET scans available. Individual FDG-PET scans were classified as being suggestive of Alzheimer's (AD-like) or Lewy body (LB-like) pathology by using a logistic regression classifier trained on a separate set of patients with autopsy-confirmed Alzheimer's disease or Lewy body pathology. AD- and LB-like subgroups were compared on amyloid-β and tau-PET, domain-specific cognitive profiles (memory versus executive function performance), as well as the presence of hallucinations and their evolution over follow-up (≈6 years for aMCI, ≈3 years for ADD). Around 12% of the aMCI and ADD patients were classified as LB-like. For both aMCI and ADD patients, the LB-like group showed significantly lower regional tau-PET burden than the AD-like subgroup, but amyloid-β load was only significantly lower in the aMCI LB-like subgroup. LB- and AD-like subgroups did not significantly differ in global cognition (aMCI: d = 0.15, P = 0.16; ADD: d = 0.02, P = 0.90), but LB-like patients exhibited a more dysexecutive cognitive profile relative to the memory deficit (aMCI: d = 0.35, P = 0.01; ADD: d = 0.85 P < 0.001), and had a significantly higher risk of developing hallucinations over follow-up [aMCI: hazard ratio = 1.8, 95% confidence interval = (1.29, 3.04), P = 0.02; ADD: hazard ratio = 2.2, 95% confidence interval = (1.53, 4.06) P = 0.01]. In summary, a sizeable group of clinically diagnosed ADD and aMCI patients exhibit posterior-occipital FDG-PET patterns typically associated with Lewy body pathology, and these also show less abnormal Alzheimer's disease biomarkers as well as specific clinical features typically associated with dementia with Lewy bodies.
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Affiliation(s)
- Jesús Silva-Rodríguez
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
| | - Miguel A Labrador-Espinosa
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
| | - Alexis Moscoso
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
| | - Michael Schöll
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, WC1ELondon, UK
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Departamento de Medicina, Facultad de Medicina, Universidad de Sevilla, 41009 Sevilla, Spain
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, 41013 Sevilla, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, 41345 Gothenburg, Sweden
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12
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Boon BDC, Labuzan SA, Peng Z, Matchett BJ, Kouri N, Hinkle KM, Lachner C, Ross OA, Ertekin-Taner N, Carter RE, Ferman TJ, Duara R, Dickson DW, Graff-Radford NR, Murray ME. Retrospective Evaluation of Neuropathologic Proxies of the Minimal Atrophy Subtype Compared With Corticolimbic Alzheimer Disease Subtypes. Neurology 2023; 101:e1412-e1423. [PMID: 37580158 PMCID: PMC10573142 DOI: 10.1212/wnl.0000000000207685] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 06/07/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Alzheimer disease (AD) is neuropathologically classified into 3 corticolimbic subtypes based on the neurofibrillary tangle distribution throughout the hippocampus and association cortices: limbic predominant, typical, and hippocampal sparing. In vivo, a fourth subtype, dubbed "minimal atrophy," was identified using structural MRI. The objective of this study was to identify a neuropathologic proxy for the neuroimaging-defined minimal atrophy subtype. METHODS We applied 2 strategies in the Florida Autopsied Multi-Ethnic (FLAME) cohort to evaluate a neuropathologic proxy for the minimal atrophy subtype. In the first strategy, we selected AD cases with a Braak tangle stage IV (Braak IV) because of the relative paucity of neocortical tangle involvement compared with Braak >IV. Braak IV cases were compared with the 3 AD subtypes. In the alternative strategy, typical AD was stratified by brain weight and cases having a relatively high brain weight (>75th percentile) were defined as minimal atrophy. RESULTS Braak IV cases (n = 37) differed from AD subtypes (limbic predominant [n = 174], typical [n = 986], and hippocampal sparing [n = 187] AD) in having the least years of education (median 12 years, group-wise p < 0.001) and the highest brain weight (median 1,140 g, p = 0.002). Braak IV cases most resembled the limbic predominant cases owing to their high proportion of APOE ε4 carriers (75%, p < 0.001), an amnestic syndrome (100%, p < 0.001), as well as older age of cognitive symptom onset and death (median 79 and 85 years, respectively, p < 0.001). Only 5% of Braak IV cases had amygdala-predominant Lewy bodies (the lowest frequency observed, p = 0.017), whereas 32% had coexisting pathology of Lewy body disease, which was greater than the other subtypes (p = 0.005). Nearly half (47%) of the Braak IV samples had coexisting limbic predominant age-related TAR DNA-binding protein 43 encephalopathy neuropathologic change. Cases with a high brain weight (n = 201) were less likely to have amygdala-predominant Lewy bodies (14%, p = 0.006) and most likely to have Lewy body disease (31%, p = 0.042) compared with those with middle (n = 455) and low (n = 203) brain weight. DISCUSSION The frequency of Lewy body disease was increased in both neuropathologic proxies of the minimal atrophy subtype. We hypothesize that Lewy body disease may underlie cognitive decline observed in minimal atrophy cases.
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Affiliation(s)
- Baayla D C Boon
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Sydney A Labuzan
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Zhongwei Peng
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Billie J Matchett
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Naomi Kouri
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Kelly M Hinkle
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Christian Lachner
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Owen A Ross
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Nilufer Ertekin-Taner
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Rickey E Carter
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Tanis J Ferman
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Ranjan Duara
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Dennis W Dickson
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Neill R Graff-Radford
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL
| | - Melissa E Murray
- From the Department of Neuroscience (B.D.C.B., S.A.L., B.J.M., N.K., K.M.H., O.A.R., N.E.-T., D.W.D., M.E.M.), Department of Quantitative Health Sciences (Z.P., R.E.C.), Department of Neurology (C.L., N.E.-T., N.R.G.-R.), and Department of Psychiatry & Psychology (C.L., T.J.F.), Mayo Clinic, Jacksonville; and Wien Center for Alzheimer's Disease and Memory Disorders (R.D.), Mount Sinai Medical Center, Miami Beach, FL.
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13
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Diaz-Galvan P, Lorenzon G, Mohanty R, Mårtensson G, Cavedo E, Lista S, Vergallo A, Kantarci K, Hampel H, Dubois B, Grothe MJ, Ferreira D, Westman E. Differential response to donepezil in MRI subtypes of mild cognitive impairment. Alzheimers Res Ther 2023; 15:117. [PMID: 37353809 PMCID: PMC10288762 DOI: 10.1186/s13195-023-01253-2] [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: 09/02/2022] [Accepted: 06/01/2023] [Indexed: 06/25/2023]
Abstract
BACKGROUND Donepezil is an approved therapy for the treatment of Alzheimer's disease (AD). Results across clinical trials have been inconsistent, which may be explained by design-methodological issues, the pathophysiological heterogeneity of AD, and diversity of included study participants. We investigated whether response to donepezil differs in mild cognitive impaired (MCI) individuals demonstrating different magnetic resonance imaging (MRI) subtypes. METHODS From the Hippocampus Study double-blind, randomized clinical trial, we included 173 MCI individuals (donepezil = 83; placebo = 90) with structural MRI data, at baseline and at clinical follow-up assessments (6-12-month). Efficacy outcomes were the annualized percentage change (APC) in hippocampal, ventricular, and total grey matter volumes, as well as in the AD cortical thickness signature. Participants were classified into MRI subtypes as typical AD, limbic-predominant, hippocampal-sparing, or minimal atrophy at baseline. We primarily applied a subtyping approach based on continuous scale of two subtyping dimensions. We also used the conventional categorical subtyping approach for comparison. RESULTS Donepezil-treated MCI individuals showed slower atrophy rates compared to the placebo group, but only if they belonged to the minimal atrophy or hippocampal-sparing subtypes. Importantly, only the continuous subtyping approach, but not the conventional categorical approach, captured this differential response. CONCLUSIONS Our data suggest that individuals with MCI, with hippocampal-sparing or minimal atrophy subtype, may have improved benefit from donepezil, as compared with MCI individuals with typical or limbic-predominant patterns of atrophy. The newly proposed continuous subtyping approach may have advantages compared to the conventional categorical approach. Future research is warranted to demonstrate the potential of subtype stratification for disease prognosis and response to treatment. TRIAL REGISTRATION ClinicalTrial.gov NCT00403520. Submission Date: November 21, 2006.
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Affiliation(s)
| | - Giulia Lorenzon
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Gustav Mårtensson
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Enrica Cavedo
- Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de L'hôpital, Paris, France
| | - Simone Lista
- Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de L'hôpital, Paris, France
| | - Andrea Vergallo
- Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de L'hôpital, Paris, France
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Harald Hampel
- Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de L'hôpital, Paris, France
| | - Bruno Dubois
- Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Boulevard de L'hôpital, Paris, France
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío, CSIC, Sevilla, Spain
- Wallenberg Center for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Daniel Ferreira
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
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14
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Mohanty R, Ferreira D, Nordberg A, Westman E. Associations between different tau-PET patterns and longitudinal atrophy in the Alzheimer's disease continuum: biological and methodological perspectives from disease heterogeneity. Alzheimers Res Ther 2023; 15:37. [PMID: 36814346 PMCID: PMC9945609 DOI: 10.1186/s13195-023-01173-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 01/18/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Subtypes and patterns are defined using tau-PET (tau pathology) and structural MRI (atrophy) in Alzheimer's disease (AD). However, the relationship between tau pathology and atrophy across these subtypes/patterns remains unclear. Therefore, we investigated the biological association between baseline tau-PET patterns and longitudinal atrophy in the AD continuum; and the methodological characterization of heterogeneity as a continuous phenomenon over the conventional discrete subgrouping. METHODS In 366 individuals (amyloid-beta-positive cognitively normal, prodromal AD, AD dementia; amyloid-beta-negative cognitively normal), we examined the association between tau-PET patterns and longitudinal MRI. We modeled tau-PET patterns as a (a) continuous phenomenon with key dimensions: typicality and severity; and (b) discrete phenomenon by categorization into patterns: typical, limbic predominant, cortical predominant and minimal tau. Tau-PET patterns and associated longitudinal atrophy were contextualized within the Amyloid/Tau/Neurodegeneration (A/T/N) biomarker scheme. RESULTS Localization and longitudinal atrophy change vary differentially across different tau-PET patterns in the AD continuum. Atrophy, a downstream event, did not always follow a topography akin to the corresponding tau-PET pattern. Further, heterogeneity as a continuous phenomenon offered an alternative and useful characterization, sharing correspondence with the conventional subgrouping. Tau-PET patterns also show differential A/T/N profiles. CONCLUSIONS The site and rate of atrophy are different across the tau-PET patterns. Heterogeneity should be treated as a continuous, not discrete, phenomenon for greater sensitivity. Pattern-specific A/T/N profiles highlight differential multimodal interactions underlying heterogeneity. Therefore, tracking multimodal interactions among biomarkers longitudinally, modeling disease heterogeneity as a continuous phenomenon, and examining heterogeneity across the AD continuum could offer avenues for precision medicine.
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Affiliation(s)
- Rosaleena Mohanty
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden.
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research. Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16, 14152, Huddinge, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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15
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Neuropathologic Features of Antemortem Atrophy-Based Subtypes of Alzheimer Disease. Neurology 2023; 100:165. [PMID: 36180246 PMCID: PMC10499412 DOI: 10.1212/wnl.0000000000201298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/11/2022] [Indexed: 01/18/2023] Open
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16
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Calderón-Garcidueñas L, Torres-Jardón R, Greenough GP, Kulesza R, González-Maciel A, Reynoso-Robles R, García-Alonso G, Chávez-Franco DA, García-Rojas E, Brito-Aguilar R, Silva-Pereyra HG, Ayala A, Stommel EW, Mukherjee PS. Sleep matters: Neurodegeneration spectrum heterogeneity, combustion and friction ultrafine particles, industrial nanoparticle pollution, and sleep disorders-Denial is not an option. Front Neurol 2023; 14:1117695. [PMID: 36923490 PMCID: PMC10010440 DOI: 10.3389/fneur.2023.1117695] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 02/01/2023] [Indexed: 03/02/2023] Open
Abstract
Sustained exposures to ubiquitous outdoor/indoor fine particulate matter (PM2.5), including combustion and friction ultrafine PM (UFPM) and industrial nanoparticles (NPs) starting in utero, are linked to early pediatric and young adulthood aberrant neural protein accumulation, including hyperphosphorylated tau (p-tau), beta-amyloid (Aβ1 - 42), α-synuclein (α syn) and TAR DNA-binding protein 43 (TDP-43), hallmarks of Alzheimer's (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). UFPM from anthropogenic and natural sources and NPs enter the brain through the nasal/olfactory pathway, lung, gastrointestinal (GI) tract, skin, and placental barriers. On a global scale, the most important sources of outdoor UFPM are motor traffic emissions. This study focuses on the neuropathology heterogeneity and overlap of AD, PD, FTLD, and ALS in older adults, their similarities with the neuropathology of young, highly exposed urbanites, and their strong link with sleep disorders. Critical information includes how this UFPM and NPs cross all biological barriers, interact with brain soluble proteins and key organelles, and result in the oxidative, endoplasmic reticulum, and mitochondrial stress, neuroinflammation, DNA damage, protein aggregation and misfolding, and faulty complex protein quality control. The brain toxicity of UFPM and NPs makes them powerful candidates for early development and progression of fatal common neurodegenerative diseases, all having sleep disturbances. A detailed residential history, proximity to high-traffic roads, occupational histories, exposures to high-emission sources (i.e., factories, burning pits, forest fires, and airports), indoor PM sources (tobacco, wood burning in winter, cooking fumes, and microplastics in house dust), and consumption of industrial NPs, along with neurocognitive and neuropsychiatric histories, are critical. Environmental pollution is a ubiquitous, early, and cumulative risk factor for neurodegeneration and sleep disorders. Prevention of deadly neurological diseases associated with air pollution should be a public health priority.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT, United States.,Universidad del Valle de México, Mexico City, Mexico
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Glen P Greenough
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Randy Kulesza
- Department of Anatomy, Lake Erie College of Osteopathic Medicine, Erie, PA, United States
| | | | | | | | | | | | | | - Héctor G Silva-Pereyra
- Instituto Potosino de Investigación Científica y Tecnológica A.C., San Luis Potosi, Mexico
| | - Alberto Ayala
- Sacramento Metropolitan Air Quality Management District, Sacramento, CA, United States.,Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, United States
| | - Elijah W Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Partha S Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata, India
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17
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Ferreira D, Mohanty R, Murray ME, Nordberg A, Kantarci K, Westman E. The hippocampal sparing subtype of Alzheimer's disease assessed in neuropathology and in vivo tau positron emission tomography: a systematic review. Acta Neuropathol Commun 2022; 10:166. [PMID: 36376963 PMCID: PMC9664780 DOI: 10.1186/s40478-022-01471-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 10/30/2022] [Indexed: 11/16/2022] Open
Abstract
Neuropathology and neuroimaging studies have identified several subtypes of Alzheimer's disease (AD): hippocampal sparing AD, typical AD, and limbic predominant AD. An unresolved question is whether hippocampal sparing AD cases can present with neurofibrillary tangles (NFT) in association cortices while completely sparing the hippocampus. To address that question, we conducted a systematic review and performed original analyses on tau positron emission tomography (PET) data. We searched EMBASE, PubMed, and Web of Science databases until October 2022. We also implemented several methods for AD subtyping on tau PET to identify hippocampal sparing AD cases. Our findings show that seven out of the eight reviewed neuropathologic studies included cases at Braak stages IV or higher and therefore, could not identify hippocampal sparing cases with NFT completely sparing the hippocampus. In contrast, tau PET did identify AD participants with tracer retention in the association cortex while completely sparing the hippocampus. We conclude that tau PET can identify hippocampal sparing AD cases with NFT completely sparing the hippocampus. Based on the accumulating data, we suggest two possible pathways of tau spread: (1) a canonical pathway with early involvement of transentorhinal cortex and subsequent involvement of limbic regions and association cortices, and (2) a less common pathway that affects association cortices with limbic involvement observed at end stages of the disease or not at all.
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Affiliation(s)
- Daniel Ferreira
- Division of Clinical Geriatrics; Center for Alzheimer Research; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16 (NEO building, floor 7th), 14152, Huddinge, Stockholm, Sweden.
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
| | - Rosaleena Mohanty
- Division of Clinical Geriatrics; Center for Alzheimer Research; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16 (NEO building, floor 7th), 14152, Huddinge, Stockholm, Sweden
| | | | - Agneta Nordberg
- Division of Clinical Geriatrics; Center for Alzheimer Research; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16 (NEO building, floor 7th), 14152, Huddinge, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Eric Westman
- Division of Clinical Geriatrics; Center for Alzheimer Research; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Blickagången 16 (NEO building, floor 7th), 14152, Huddinge, Stockholm, Sweden.
- Department of Neuroimaging, Center for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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