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Capogna E, Sørensen Ø, Watne LO, Roe J, Strømstad M, Idland AV, Halaas NB, Blennow K, Zetterberg H, Walhovd KB, Fjell AM, Vidal-Piñeiro D. Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers. Neurobiol Aging 2025; 147:124-140. [PMID: 39740372 DOI: 10.1016/j.neurobiolaging.2024.12.009] [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: 03/22/2024] [Revised: 12/20/2024] [Accepted: 12/20/2024] [Indexed: 01/02/2025]
Abstract
Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.
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Affiliation(s)
- Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway.
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - James Roe
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Marie Strømstad
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Ane Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, Campus Ullevål, University of Oslo, Oslo, Norway.
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France; Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, PR China
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Center for Neurodegenerative Diseases, Hong Kong; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
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Xie L, Das SR, Li Y, Wisse LEM, McGrew E, Lyu X, DiCalogero M, Shah U, Ilesanmi A, Denning AE, Brown CA, Cohen J, Sreepada L, Dong M, Sadeghpour N, Khandelwal P, Ittyerah R, Ravikumar S, Sadaghiani S, Hrybouski S, de Flores R, Gibson E, Yushkevich PA, Wolk DA, for the Alzheimer's Disease Neuroimaging Initiative. A multi-cohort study of longitudinal and cross-sectional Alzheimer's disease biomarkers in cognitively unimpaired older adults. Alzheimers Dement 2025; 21:e14492. [PMID: 39868491 PMCID: PMC11848397 DOI: 10.1002/alz.14492] [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: 05/03/2024] [Revised: 11/26/2024] [Accepted: 11/27/2024] [Indexed: 01/28/2025]
Abstract
INTRODUCTION The generalizability of neuroimaging and cognitive biomarkers in their sensitivity to detect preclinical Alzheimer's disease (AD) and power to predict progression in large, multisite cohorts remains unclear. METHOD Longitudinal demographics, T1-weighted magnetic resonance imaging (MRI), and cognitive scores of 3036 cognitively unimpaired (CU) older adults (amyloid beta [Aβ]-negative/positive [A-/A+]: 1270/1558) were included. Cross-sectional and longitudinal cognition and medial temporal lobe (MTL) structural measures were extracted. Cross-sectional MTL tau burden (T) was computed from tau positron emission tomography (N = 1095). RESULTS We found cross-sectional tau and longitudinal structural biomarkers best separated A+ CU from A- CU. A-T+ CU had significantly faster neurodegeneration rate compared to A-T- CU. MTL tau was significantly correlated with MRI and cognitive biomarkers regardless of Aβ status. MTL tau, MRI, and cognition provided complementary information about disease progression. DISCUSSION This large multisite study replicates prior findings in CU older adults, supporting the utility of neuroimaging and cognitive biomarkers in preclinical AD clinical trials and normal aging studies. HIGHLIGHTS We investigated neuroimaging and cognitive biomarkers in 3036 cognitively unimpaired (CU) participants. Medial temporal lobe (MTL) tau and longitudinal MTL atrophy best separate amyloid beta positive (A+) CU from amyloid beta negative (A-) CU. A- tau positive (T+) CU had a significantly faster neurodegeneration rate compared to A-T- CU. MTL tau correlated with structural magnetic resonance imaging (MRI) and cognition regardless of amyloid beta status. Combined baseline MTL tau, MRI, and cognition best predict Alzheimer's disease progression.
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Affiliation(s)
- Long Xie
- Department of Digital Technology and InnovationSiemens HealthineersPrincetonNew JerseyUSA
| | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Yue Li
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Emily McGrew
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Xueying Lyu
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Ujashi Shah
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ademola Ilesanmi
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Amanda E. Denning
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Chris A. Brown
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Jesse Cohen
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Lasya Sreepada
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Mengjin Dong
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Niyousha Sadeghpour
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Pulkit Khandelwal
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sadhana Ravikumar
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shokufeh Sadaghiani
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Stanislau Hrybouski
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Eli Gibson
- Department of Digital Technology and InnovationSiemens HealthineersPrincetonNew JerseyUSA
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL)Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Zhou B, Fukushima M. Differential risk of Alzheimer's disease in MCI subjects with elevated Abeta. J Neurol Sci 2024; 467:123319. [PMID: 39612639 DOI: 10.1016/j.jns.2024.123319] [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: 09/06/2024] [Revised: 10/30/2024] [Accepted: 11/18/2024] [Indexed: 12/01/2024]
Abstract
BACKGROUNDS People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. PURPOSE The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. METHODS The risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol. RESULTS In total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up. DISCUSSION Risk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up.
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Affiliation(s)
- Bin Zhou
- Foundation for Learning Health Society Institute, Nagoya, Aichi 450-0003, Japan.
| | - Masanori Fukushima
- Foundation for Learning Health Society Institute, Nagoya, Aichi 450-0003, Japan
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Isidro F. Brain aging and Alzheimer's disease, a perspective from non-human primates. Aging (Albany NY) 2024; 16:13145-13171. [PMID: 39475348 PMCID: PMC11552644 DOI: 10.18632/aging.206143] [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: 03/09/2024] [Accepted: 06/03/2024] [Indexed: 11/07/2024]
Abstract
Brain aging is compared between Cercopithecinae (macaques and baboons), non-human Hominidae (chimpanzees, orangutans, and gorillas), and their close relative, humans. β-amyloid deposition in the form of senile plaques (SPs) and cerebral β-amyloid angiopathy (CAA) is a frequent neuropathological change in non-human primate brain aging. SPs are usually diffuse, whereas SPs with dystrophic neurites are rare. Tau pathology, if present, appears later, and it is generally mild or moderate, with rare exceptions in rhesus macaques and chimpanzees. Behavior and cognitive impairment are usually mild or moderate in aged non-human primates. In contrast, human brain aging is characterized by early tau pathology manifested as neurofibrillary tangles (NFTs), composed of paired helical filaments (PHFs), progressing from the entorhinal cortex, hippocampus, temporal cortex, and limbic system to other brain regions. β-amyloid pathology appears decades later, involves the neocortex, and progresses to the paleocortex, diencephalon, brain stem, and cerebellum. SPs with dystrophic neurites containing PHFs and CAA are common. Cognitive impairment and dementia of Alzheimer's type occur in about 1-5% of humans aged 65 and about 25% aged 85. In addition, other proteinopathies, such as limbic-predominant TDP-43 encephalopathy, amygdala-predominant Lewy body disease, and argyrophilic grain disease, primarily affecting the archicortex, paleocortex, and amygdala, are common in aged humans but non-existent in non-human primates. These observations show that human brain aging differs from brain aging in non-human primates, and humans constitute the exception among primates in terms of severity and extent of brain aging damage.
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Affiliation(s)
- Ferrer Isidro
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Hospitalet de Llobregat, Barcelona, Spain
- Reial Acadèmia de Medicina de Catalunya, Barcelona, Spain
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Kapasi A, Yu L, Leurgans SE, Agrawal S, Boyle PA, Bennett DA, Schneider JA. Association between hippocampal microglia, AD and LATE-NC, and cognitive decline in older adults. Alzheimers Dement 2024; 20:3193-3202. [PMID: 38494787 PMCID: PMC11095444 DOI: 10.1002/alz.13780] [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: 10/26/2023] [Accepted: 01/29/2024] [Indexed: 03/19/2024]
Abstract
INTRODUCTION This study investigates the relationship between microglia inflammation in the hippocampus, brain pathologies, and cognitive decline. METHODS Participants underwent annual clinical evaluations and agreed to brain donation. Neuropathologic evaluations quantified microglial burden in the hippocampus, amyloid beta (Aβ), tau tangles, and limbic age-related transactive response DNA-binding protein 43 (TDP-43) encephalopathy neuropathologic changes (LATE-NC), and other common brain pathologies. Mixed-effect and linear regression models examined the association of microglia with a decline in global and domain-specific cognitive measures, and separately with brain pathologies. Path analyses estimated direct and indirect effects of microglia on global cognition. RESULT Hippocampal microglia were associated with a faster decline in global cognition, specifically in episodic memory, semantic memory, and perceptual speed. Tau tangles and LATE-NC were independently associated with microglia. Other pathologies, including Aβ, were not related. Regional hippocampal burden of tau tangles and TDP-43 accounted for half of the association of microglia with cognitive decline. DISCUSSION Microglia inflammation in the hippocampus contributes to cognitive decline. Tau tangles and LATE-NC partially mediate this association.
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Affiliation(s)
- Alifiya Kapasi
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of PathologyRush University Medical CenterChicagoIllinoisUSA
| | - Lei Yu
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
| | - Sue E Leurgans
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
| | - Sonal Agrawal
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of PathologyRush University Medical CenterChicagoIllinoisUSA
| | - Patricia A Boyle
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Psychiatry and Behavioral SciencesRush University Medical CenterChicagoIllinoisUSA
| | - David A Bennett
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
| | - Julie A Schneider
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of PathologyRush University Medical CenterChicagoIllinoisUSA
- Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
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Capogna E, Sørensen Ø, Watne LO, Roe J, Strømstad M, Idland AV, Halaas NB, Blennow K, Zetterberg H, Walhovd KB, Fjell AM, Vidal-Piñeiro D. Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583291. [PMID: 38496633 PMCID: PMC10942348 DOI: 10.1101/2024.03.04.583291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.
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Affiliation(s)
- Elettra Capogna
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Leiv Otto Watne
- Department of Geriatric Medicine, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - James Roe
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Marie Strømstad
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Ane Victoria Idland
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Nathalie Bodd Halaas
- Oslo Delirium Research Group, Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Campus UllevÅl, University of Oslo, Oslo, Norway
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, the Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kristine Beate Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders Martin Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373 Oslo, Norway
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Chen X, Toueg TN, Harrison TM, Baker SL, Jagust WJ. Regional Tau Deposition Reflects Different Pathways of Subsequent Neurodegeneration and Memory Decline in Cognitively Normal Older Adults. Ann Neurol 2024; 95:249-259. [PMID: 37789559 PMCID: PMC10843500 DOI: 10.1002/ana.26813] [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: 05/20/2023] [Revised: 09/12/2023] [Accepted: 09/27/2023] [Indexed: 10/05/2023]
Abstract
OBJECTIVE Tau pathology is recognized as a primary contributor to neurodegeneration and clinical symptoms in Alzheimer's disease (AD). This study aims to localize the early tau pathology in cognitively normal older people that is predictive of subsequent neurodegeneration and memory decline, and delineate factors underlying tau-related memory decline in individuals with and without β-amyloid (Aβ). METHODS A total of 138 cognitively normal older individuals from the Berkeley Aging Cohort Study underwent 11 C-Pittsburgh Compound-B (PiB) positron emission tomography (PET) to determine Aβ positivity and 18 F-Flortaucipir (FTP) PET to measure tau deposition, with prospective cognitive assessments and structural magnetic resonance imaging. Voxel-wise FTP analyses examined associations between baseline tau deposition and longitudinal memory decline, longitudinal hippocampal atrophy, and longitudinal cortical thinning in AD signature regions. We also examined whether hippocampal atrophy and cortical thinning mediate tau effects on future memory decline. RESULTS We found Aβ-dependent tau associations with memory decline in the entorhinal and temporoparietal regions, Aβ-independent tau associations with hippocampal atrophy within the medial temporal lobe (MTL), and that widespread tau was associated with mean cortical thinning in AD signature regions. Tau-related memory decline was mediated by hippocampal atrophy in Aβ- individuals and by mean cortical thinning in Aβ+ individuals. INTERPRETATION Our results suggest that tau may affect memory through different mechanisms in normal aging and AD. Early tau deposition independent of Aβ predicts subsequent hippocampal atrophy that may lead to memory deficits in normal older individuals, whereas elevated cortical tau deposition is associated with cortical thinning that may lead to more severe memory decline in AD. ANN NEUROL 2024;95:249-259.
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Affiliation(s)
- Xi Chen
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Tyler N Toueg
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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Ferrer I. Amyloid-β Pathology Is the Common Nominator Proteinopathy of the Primate Brain Aging. J Alzheimers Dis 2024; 100:S153-S164. [PMID: 39031364 PMCID: PMC11380266 DOI: 10.3233/jad-240389] [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] [Accepted: 05/27/2024] [Indexed: 07/22/2024]
Abstract
Senile plaques, mainly diffuse, and cerebral amyloid-β (Aβ) angiopathy are prevalent in the aging brain of non-human primates, from lemurs to non-human Hominidae. Aβ but not hyper-phosphorylated tau (HPtau) pathology is the common nominator proteinopathy of non-human primate brain aging. The abundance of Aβ in the aging primate brain is well tolerated, and the impact on cognitive functions is usually limited to particular tasks. In contrast, human brain aging is characterized by the early appearance of HPtau pathology, mainly forming neurofibrillary tangles, dystrophic neurites of neuritic plaques, and neuropil threads, preceding Aβ deposits by several decades and by its severity progressing from selected nuclei of the brain stem, entorhinal cortex, and hippocampus to the limbic system, neocortex, and other brain regions. Neurofibrillary tangles correlate with cognitive impairment and dementia in advanced cases. Aβ pathology is linked in humans to altered membrane protein and lipid composition, particularly involving lipid rafts. Although similar membrane alterations are unknown in non-human primates, membrane senescence is postulated to cause the activated β-amyloidogenic pathway, and Aβ pathology is the prevailing signature of non-human and human primate brain aging.
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Affiliation(s)
- Isidro Ferrer
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Barcelona, Spain
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9
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Bachmann D, Buchmann A, Studer S, Saake A, Rauen K, Zuber I, Gruber E, Nitsch RM, Hock C, Gietl A, Treyer V. Age-, sex-, and pathology-related variability in brain structure and cognition. Transl Psychiatry 2023; 13:278. [PMID: 37574523 PMCID: PMC10423720 DOI: 10.1038/s41398-023-02572-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/15/2023] Open
Abstract
This work aimed to investigate potential pathways linking age and imaging measures to early age- and pathology-related changes in cognition. We used [18F]-Flutemetamol (amyloid) and [18F]-Flortaucipir (tau) positron emission tomography (PET), structural MRI, and neuropsychological assessment from 232 elderly individuals aged 50-89 years (46.1% women, 23% APOE-ε4 carrier, 23.3% MCI). Tau-PET was available for a subsample of 93 individuals. Structural equation models were used to evaluate cross-sectional pathways between age, amyloid and tau burden, grey matter thickness and volumes, white matter hyperintensity volume, lateral ventricle volume, and cognition. Our results show that age is associated with worse outcomes in most of the measures examined and had similar negative effects on episodic memory and executive functions. While increased lateral ventricle volume was consistently associated with executive function dysfunction, participants with mild cognitive impairment drove associations between structural measures and episodic memory. Both age and amyloid-PET could be associated with medial temporal lobe tau, depending on whether we used a continuous or a dichotomous amyloid variable. Tau burden in entorhinal cortex was related to worse episodic memory in individuals with increased amyloid burden (Centiloid >12) independently of medial temporal lobe atrophy. Testing models for sex differences revealed that amyloid burden was more strongly associated with regional atrophy in women compared with men. These associations were likely mediated by higher tau burden in women. These results indicate that influences of pathological pathways on cognition and sex-specific vulnerabilities are dissociable already in early stages of neuropathology and cognitive impairment.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland.
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
| | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
| | - Isabelle Zuber
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
- Neurimmune AG, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
- Neurimmune AG, Schlieren, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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de Flores R, Demeilliez-Servouin S, Kuhn E, Chauveau L, Landeau B, Delcroix N, Gonneaud J, Vivien D, Chételat G. Respective influence of beta-amyloid and APOE ε4 genotype on medial temporal lobe subregions in cognitively unimpaired older adults. Neurobiol Dis 2023; 181:106127. [PMID: 37061167 DOI: 10.1016/j.nbd.2023.106127] [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: 01/23/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 04/17/2023] Open
Abstract
Medial temporal lobe (MTL) subregions are differentially affected in Alzheimer's disease (AD), with a specific involvement of the entorhinal cortex (ERC), perirhinal cortex and hippocampal cornu ammonis (CA)1. While amyloid (Aβ) and APOEε4 are respectively the first molecular change and the main genetic risk factor in AD, their links with MTL atrophy remain relatively unclear. Our aim was to uncover these effects using baseline data from 130 participants included in the Age-Well study, for whom ultra-high-resolution structural MRI, amyloid-PET and APOEε4 genotype were available. No volume differences were observed between Aβ + (n = 24) and Aβ- (n = 103), nor between APOE4+ (n = 35) and APOE4- (n = 95) participants. However, our analyses showed that both Aβ and APOEε4 status interacted with age on CA1, which is known to be specifically atrophied in early AD. In addition, APOEε4 status moderated the effects of age on other subregions (subiculum, ERC), suggesting a more important contribution of APOEε4 than Aβ to MTL atrophy in cognitively unimpaired population. These results are crucial to develop MRI-based biomarkers to detect early AD.
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Affiliation(s)
- Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France.
| | - Solène Demeilliez-Servouin
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Elizabeth Kuhn
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Léa Chauveau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Brigitte Landeau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | | | - Julie Gonneaud
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Denis Vivien
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Gaël Chételat
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
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Xie L, Das SR, Wisse LEM, Ittyerah R, de Flores R, Shaw LM, Yushkevich PA, Wolk DA. Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer's disease. Alzheimers Res Ther 2023; 15:79. [PMID: 37041649 PMCID: PMC10088234 DOI: 10.1186/s13195-023-01210-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 03/13/2023] [Indexed: 04/13/2023]
Abstract
BACKGROUND Crucial to the success of clinical trials targeting early Alzheimer's disease (AD) is recruiting participants who are more likely to progress over the course of the trials. We hypothesize that a combination of plasma and structural MRI biomarkers, which are less costly and non-invasive, is predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a practical alternative to PET or cerebrospinal fluid biomarkers. METHODS Longitudinal T1-weighted MRI, cognitive (memory-related test scores and clinical dementia rating scale), and plasma measurements of 245 cognitively normal (CN) and 361 mild cognitive impairment (MCI) patients from ADNI were included. Subjects were further divided into β-amyloid positive/negative (Aβ+/Aβ-)] subgroups. Baseline plasma (p-tau181 and neurofilament light chain) and MRI-based structural medial temporal lobe subregional measurements and their association with longitudinal measures of atrophy and cognitive decline were tested using stepwise linear mixed effect modeling in CN and MCI, as well as separately in the Aβ+/Aβ- subgroups. Receiver operating characteristic (ROC) analyses were performed to investigate the discriminative power of each model in separating fast and slow progressors (first and last terciles) of each longitudinal measurement. RESULTS A total of 245 CN (35.0% Aβ+) and 361 MCI (53.2% Aβ+) participants were included. In the CN and MCI groups, both baseline plasma and structural MRI biomarkers were included in most models. These relationships were maintained when limited to the Aβ+ and Aβ- subgroups, including Aβ- CN (normal aging). ROC analyses demonstrated reliable discriminative power in identifying fast from slow progressors in MCI [area under the curve (AUC): 0.78-0.93] and more modestly in CN (0.65-0.73). CONCLUSIONS The present data support the notion that plasma and MRI biomarkers, which are relatively easy to obtain, provide a prediction for the rate of future cognitive and neurodegenerative progression that may be particularly useful in clinical trial stratification and prognosis. Additionally, the effect in Aβ- CN indicates the potential use of these biomarkers in predicting a normal age-related decline.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA.
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E M Wisse
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - Robin de Flores
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - David A Wolk
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
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Adams JN, Márquez F, Larson MS, Janecek JT, Miranda BA, Noche JA, Taylor L, Hollearn MK, McMillan L, Keator DB, Head E, Rissman RA, Yassa MA. Differential involvement of hippocampal subfields in the relationship between Alzheimer's pathology and memory interference in older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12419. [PMID: 37035460 PMCID: PMC10075195 DOI: 10.1002/dad2.12419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 02/15/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023]
Abstract
Introduction We tested whether Alzheimer's disease (AD) pathology predicts memory deficits in non-demented older adults through its effects on medial temporal lobe (MTL) subregional volume. Methods Thirty-two, non-demented older adults with cerebrospinal fluid (CSF) (amyloid-beta [Aβ]42/Aβ40, phosphorylated tau [p-tau]181, total tau [t-tau]), positron emission tomography (PET; 18F-florbetapir), high-resolution structural magnetic resonance imaging (MRI), and neuropsychological assessment were analyzed. We examined relationships between biomarkers and a highly granular measure of memory consolidation, retroactive interference (RI). Results Biomarkers of AD pathology were related to RI. Dentate gyrus (DG) and CA3 volume were uniquely associated with RI, whereas CA1 and BA35 volume were related to both RI and overall memory recall. AD pathology was associated with reduced BA35, CA1, and subiculum volume. DG volume and Aβ were independently associated with RI, whereas CA1 volume mediated the relationship between AD pathology and RI. Discussion Integrity of distinct hippocampal subfields demonstrate differential relationships with pathology and memory function, indicating specificity in vulnerability and contribution to different memory processes.
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Affiliation(s)
- Jenna N. Adams
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Freddie Márquez
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Myra S. Larson
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - John T. Janecek
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Blake A. Miranda
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Jessica A. Noche
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Lisa Taylor
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Martina K. Hollearn
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - Liv McMillan
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
| | - David B. Keator
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | - Elizabeth Head
- Department of Pathology and Laboratory MedicineUniversity of CaliforniaIrvineCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaIrvineCaliforniaUSA
- Department of NeurologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Robert A. Rissman
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
- Veterans Affairs San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Michael A. Yassa
- Department of Neurobiology and Behavior and Center for the Neurobiology of Learning and MemoryUniversity of CaliforniaIrvineCaliforniaUSA
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Abstract
National Institute on Aging-Alzheimer's Association definition and classification of sporadic Alzheimer's disease (sAD) is based on the assumption that β-amyloid drives the pathogenesis of sAD, and therefore, β-amyloid pathology is the sine-qua-non condition for the diagnosis of sAD. The neuropathological diagnosis is based on the concurrence of senile plaques (SPs) and neurofibrillary tangles (NFTs) designated as Alzheimer's disease neuropathological changes. However, NFTs develop in the brain decades before the appearance of SPs, and their distribution does not parallel the distribution of SPs. Moreover, NFTs are found in about 85% of individuals at age 65 and around 97% at age 80. SPs occur in 30% at age 65 and 50%-60% at age 80. More than 70 genetic risk factors have been identified in sAD; the encoded proteins modulate cell membranes, synapses, lipid metabolism, and neuroinflammation. Alzheimer's disease (AD) overture provides a new concept and definition of brain aging and sAD for further discussion. AD overture proposes that sAD is: (i) a multifactorial and progressive neurodegenerative biological process, (ii) characterized by the early appearance of 3R + 4Rtau NFTs, (iii) later deposition of β-amyloid and SPs, (iv) with particular non-overlapped regional distribution of NFTs and SPs, (v) preceded by or occurring in parallel with molecular changes affecting cell membranes, cytoskeleton, synapses, lipid and protein metabolism, energy metabolism, neuroinflammation, cell cycle, astrocytes, microglia, and blood vessels; (vi) accompanied by progressive neuron loss and brain atrophy, (vii) prevalent in human brain aging, and (viii) manifested as pre-clinical AD, and progressing not universally to mild cognitive impairment due to AD, and mild, moderate, and severe AD dementia.
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Affiliation(s)
- Isidro Ferrer
- Department of Pathology and Experimental TherapeuticsUniversity of Barcelona (UB)BarcelonaSpain
- Neuropathology groupInstitute of Biomedical Research of Bellvitge (IDIBELL)BarcelonaSpain
- Network Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos IIIBarcelonaSpain
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Ferrer I. Alzheimer's disease is an inherent, natural part of human brain aging: an integrated perspective. FREE NEUROPATHOLOGY 2022; 3:17. [PMID: 37284149 PMCID: PMC10209894 DOI: 10.17879/freeneuropathology-2022-3806] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 06/21/2022] [Indexed: 06/08/2023]
Abstract
Alzheimer disease is one of the most challenging demons in our society due to its very high prevalence and its clinical manifestations which cause deterioration of cognition, intelligence, and emotions - the very capacities that distinguish Homo sapiens from other animal species. Besides the personal, social, and economical costs, late stages of AD are vivid experiences for the family, relatives, friends, and general observers of the progressive ruin of an individual who turns into a being with lower mental and physical capacities than less evolved species. A human brain with healthy cognition, conscience, and emotions can succeed in dealing with most difficulties that life may pose. Without these capacities, the same person probably cannot. Due, in part, to this emotional impact, the absorbing study of AD has generated, over the years, a fascinating and complex story of theories, hypotheses, controversies, fashion swings, and passionate clashes, together with tremendous efforts and achievements geared to improve understanding of the pathogenesis and treatment of the disorder. Familal AD is rare and linked to altered genetic information associated with three genes. Sporadic AD (sAD) is much more common and multifactorial. A major point of clinical discussion has been, and still is, establishing the differences between brain aging and sAD. This is not a trivial question, as the neuropathological and molecular characteristics of normal brain aging and the first appearance of early stages of sAD-related pathology are not easily distinguishable in most individuals. Another important point is confidence in assigning responsibility for the beginning of sAD to a few triggering molecules, without considering the wide number of alterations that converge in the pathogenesis of aging and sAD. Genetic risk factors covering multiple molecular signals are increasing in number. In the same line, molecular pathways are altered at early stages of sAD pathology, currently grouped under the aegis of normal brain aging, only to increase massively at advanced stages of the process. Sporadic AD is here considered an inherent, natural part of human brain aging, which is prevalent in all humans, and variably present or not in a few individuals in other species. The progression of the process has devastating effects in a relatively low percentage of human beings eventually evolving to dementia. The continuum of brain aging and sAD implies the search for a different approach in the study of human brain aging at the first stages of the biological process, and advances in the use of new technologies aimed at slowing down the molecular defects underlying human brain aging and sAD at the outset, and transfering information and tasks to AI and coordinated devices.
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Affiliation(s)
- Isidro Ferrer
- Department of Pathology and Experimental Therapeutics, University of Barcelona; Emeritus Researcher of the Bellvitge Institute of Biomedical Research (IDIBELL); Biomedical Research Network of Neurodegenerative Diseases (CIBERNED); Institute of Neurosciences, University of Barcelona; Hospitalet de Llobregat, Barcelona, Spain
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