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Pelkmans W, Shekari M, Brugulat‐Serrat A, Sánchez‐Benavides G, Minguillón C, Fauria K, Molinuevo JL, Grau‐Rivera O, González Escalante A, Kollmorgen G, Carboni M, Ashton NJ, Zetterberg H, Blennow K, Suarez‐Calvet M, Gispert JD. Astrocyte biomarkers GFAP and YKL-40 mediate early Alzheimer's disease progression. Alzheimers Dement 2024; 20:483-493. [PMID: 37690071 PMCID: PMC10917053 DOI: 10.1002/alz.13450] [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: 05/05/2023] [Revised: 07/11/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023]
Abstract
INTRODUCTION We studied how biomarkers of reactive astrogliosis mediate the pathogenic cascade in the earliest Alzheimer's disease (AD) stages. METHODS We performed path analysis on data from 384 cognitively unimpaired individuals from the ALzheimer and FAmilies (ALFA)+ study using structural equation modeling to quantify the relationships between biomarkers of reactive astrogliosis and the AD pathological cascade. RESULTS Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/40 was associated with Aβ aggregation on positron emission tomography (PET) and with CSF p-tau181 , which was in turn directly associated with CSF neurofilament light (NfL). Plasma glial fibrillary acidic protein (GFAP) mediated the relationship between CSF Aβ42/40 and Aβ-PET, and CSF YKL-40 partly explained the association between Aβ-PET, p-tau181 , and NfL. DISCUSSION Our results suggest that reactive astrogliosis, as indicated by different fluid biomarkers, influences the pathogenic cascade during the preclinical stage of AD. While plasma GFAP mediates the early association between soluble and insoluble Aβ, CSF YKL-40 mediates the latter association between Aβ and downstream Aβ-induced tau pathology and tau-induced neuronal injury. HIGHLIGHTS Lower CSF Aβ42/40 was directly linked to higher plasma GFAP concentrations. Plasma GFAP partially explained the relationship between soluble Aβ and insoluble Aβ. CSF YKL-40 mediated Aβ-induced tau phosphorylation and tau-induced neuronal injury.
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Affiliation(s)
- Wiesje Pelkmans
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | - Anna Brugulat‐Serrat
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Gonzalo Sánchez‐Benavides
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Jose Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Lundbeck A/SCopenhagenDenmark
| | - Oriol Grau‐Rivera
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Armand González Escalante
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
| | | | | | - Nicholas J. Ashton
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- NIHR Biomedical Research Centre for Mental HealthBiomedical Research Unit for Dementia at South LondonMaudsley NHS FoundationLondonUK
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgGothenburgSweden
- Institute of PsychiatryPsychology & NeuroscienceKing's College LondonLondonUK
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- UK Dementia Research Institute at UCLLondonUK
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Marc Suarez‐Calvet
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Lundbeck A/SCopenhagenDenmark
- Servei de NeurologiaHospital del MarBarcelonaSpain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Medical Research Institute (IMIM)BarcelonaSpain
- Lundbeck A/SCopenhagenDenmark
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBER‐BBN)MadridSpain
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Zhang W, Wang HF, Kuo K, Wang L, Li Y, Yu J, Feng J, Cheng W. Contribution of Alzheimer's disease pathology to biological and clinical progression: A longitudinal study across two cohorts. Alzheimers Dement 2023; 19:3602-3612. [PMID: 36840615 DOI: 10.1002/alz.12992] [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: 11/10/2022] [Revised: 01/13/2023] [Accepted: 01/15/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION Amyloid beta (Aβ) deposition, tau accumulation, and brain atrophy occurr in sequence, but the contribution of Alzheimer's disease (AD) pathology to biological and clinical progression remains unclear. METHODS We included 290 and 70 participants with longitudinal assessment on Aβ-positron emission tomography (PET), tau-PET, magnetic resonance imaging, and cognitive function from the Harvard Aging Brain Study (HABS) and Alzheimer's Disease Neuroimaging Initiative (ADNI) datasets, respectively. Partial least squares structural equation modeling (PLS-SEM) was used to determine the contribution of AD pathology to the biological and clinical longitudinal changes. RESULTS Imaging biomarkers and cognitive function were significantly associated in cross-sectional and longitudinal analyses. At the final time point, the percentage of variance explained by PLS-SEM was 27% for Aβ, 30% for tau (Aβ accounted for 61%), 29% for brain atrophy (tau accounted for 37%), and 37% for cognitive decline (brain atrophy accounted for 35%). DISCUSSION This study highlights distinctive contributing proportions of AD pathology to biological and clinical progression. Treatments targeting Aβ and tau may partially block AD progression.
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Affiliation(s)
- Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Hui-Fu Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Kevin Kuo
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Linbo Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Yuzhu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jintai Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
- School of Data Science, Fudan University, Shanghai, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, and Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Fudan University, Shanghai, China
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Du Y, Guo J, Zhou Y, Yan S, Xu B, Wang Y, Lu D, Ma Z, Chen Q, Tang Q, Zhang W, Zhu J, Huang Y, Yang C. Revealing the Mechanisms of Byu dMar 25 in the Treatment of Alzheimer's Disease through Network Pharmacology, Molecular Docking, and In Vivo Experiment. ACS OMEGA 2023; 8:25066-25080. [PMID: 37483184 PMCID: PMC10357573 DOI: 10.1021/acsomega.3c01683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/25/2023] [Indexed: 07/25/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is the most common neurodegenerative disease, severely reducing the cognitive level and life quality of patients. Byu dMar 25 (BM25) has been proved to have a therapeutic effect on AD. However, the pharmacological mechanism is still unclear. Therefore, this study aims to reveal the potential mechanism of BM25 affecting AD from the perspective of network pharmacology and experimental validation. METHODS The potential active ingredients of BM25 were obtained from the TCMSP database and literature. Possible targets were predicted using SwissTargetPrediction tools. AD-related genes were identified by using GeneCards, OMIM, DisGeNET, and Drugbank databases. The candidate genes were obtained by extraction of the intersection network. Additionally, the "drug-target-disease" network was constructed by Cytoscape 3.7.2 for visualization. The PPI network was constructed by the STRING database, and the core network modules were filtered by Cytoscape 3.7.2. Enrichment analysis of GO and KEGG was carried out in the Metascape platform. Ledock software was used to dock the critical components with the core target. Furthermore, protein levels were evaluated by immunohistochemistry. RESULTS In this study, 112 active components, 1112 disease candidate genes, 3084 GO functions, and 277 KEGG pathways were obtained. Molecular docking showed that the effective components of BM25 in treating AD were β-asarone and hydroxysafflor yellow A. The most important targets were APP, PIK3R1, and PIK3CA. Enrichment analysis indicated that the Golgi genetic regulation, peroxidase activity regulation, phosphatidylinositol 3-kinase complex IA, 5-hydroxytryptamine receptor complexes, cancer pathways, and neuroactive ligand-receptor interactions played vital roles against AD. The rat experiment verified that BM25 affected PI3K-Akt pathway activation in AD. CONCLUSIONS This study reveals the mechanism of BM25 in treating AD with network pharmacology, which provides a foundation for further study on the molecular mechanism of AD treatment.
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Affiliation(s)
- Yikuan Du
- Central
Laboratory, The Tenth Affiliated Hospital
of Southern Medical University, Dongguan 523059, China
| | - Jinyan Guo
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Yuqi Zhou
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Simin Yan
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Bijun Xu
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Yuni Wang
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Duoduo Lu
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Zhendong Ma
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Qianwen Chen
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Qibin Tang
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Weichui Zhang
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Jinfeng Zhu
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Yixing Huang
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
| | - Chun Yang
- Dongguan
Key Laboratory of Chronic Inflammatory Diseases, The First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan 523000, China
- Dongguan
Key Laboratory of stem cell and regenerative tissue engineering, Guangdong Medical University, Dongguan 523808, China
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Salvadó G, Larsson V, Cody KA, Cullen NC, Jonaitis EM, Stomrud E, Kollmorgen G, Wild N, Palmqvist S, Janelidze S, Mattsson-Carlgren N, Zetterberg H, Blennow K, Johnson SC, Ossenkoppele R, Hansson O. Optimal combinations of CSF biomarkers for predicting cognitive decline and clinical conversion in cognitively unimpaired participants and mild cognitive impairment patients: A multi-cohort study. Alzheimers Dement 2023; 19:2943-2955. [PMID: 36648169 PMCID: PMC10350470 DOI: 10.1002/alz.12907] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 10/30/2022] [Accepted: 11/15/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Our objective was determining the optimal combinations of cerebrospinal fluid (CSF) biomarkers for predicting disease progression in Alzheimer's disease (AD) and other neurodegenerative diseases. METHODS We included 1,983 participants from three different cohorts with longitudinal cognitive and clinical data, and baseline CSF levels of Aβ42, Aβ40, phosphorylated tau at threonine-181 (p-tau), neurofilament light (NfL), neurogranin, α-synuclein, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), glial fibrillary acidic protein (GFAP), YKL-40, S100b, and interleukin 6 (IL-6) (Elecsys NeuroToolKit). RESULTS Change of modified Preclinical Alzheimer's Cognitive Composite (mPACC) in cognitively unimpaired (CU) was best predicted by p-tau/Aβ42 alone (R2 ≥ 0.31) or together with NfL (R2 = 0.25), while p-tau/Aβ42 (R2 ≥ 0.19) was sufficient to accurately predict change of the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) patients. P-tau/Aβ42 (AUC ≥ 0.87) and p-tau/Aβ42 together with NfL (AUC ≥ 0.75) were the best predictors of conversion to AD and all-cause dementia, respectively. DISCUSSION P-tau/Aβ42 is sufficient for predicting progression in AD, with very high accuracy. Adding NfL improves the prediction of all-cause dementia conversion and cognitive decline.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Victoria Larsson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Karly A Cody
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | | | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center University of Wisconsin School of Medicine and Public Health Madison Wisconsin, Madison, Wisconsin, USA
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Geriatric Research, Education and Clinical Center at the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Matafora V, Gorb A, Yang F, Noble W, Bachi A, Perez‐Nievas BG, Jimenez‐Sanchez M. Proteomics of the astrocyte secretome reveals changes in their response to soluble oligomeric Aβ. J Neurochem 2023; 166:346-366. [PMID: 37303123 PMCID: PMC10952722 DOI: 10.1111/jnc.15875] [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: 01/27/2023] [Revised: 05/15/2023] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
Astrocytes associate with amyloid plaques in Alzheimer's disease (AD). Astrocytes react to changes in the brain environment, including increasing concentrations of amyloid-β (Aβ). However, the precise response of astrocytes to soluble small Aβ oligomers at concentrations similar to those present in the human brain has not been addressed. In this study, we exposed astrocytes to media from neurons that express the human amyloid precursor protein (APP) transgene with the double Swedish mutation (APPSwe), and which contains APP-derived fragments, including soluble human Aβ oligomers. We then used proteomics to investigate changes in the astrocyte secretome. Our data show dysregulated secretion of astrocytic proteins involved in the extracellular matrix and cytoskeletal organization and increase secretion of proteins involved in oxidative stress responses and those with chaperone activity. Several of these proteins have been identified in previous transcriptomic and proteomic studies using brain tissue from human AD and cerebrospinal fluid (CSF). Our work highlights the relevance of studying astrocyte secretion to understand the brain response to AD pathology and the potential use of these proteins as biomarkers for the disease.
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Affiliation(s)
| | - Alena Gorb
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Fangjia Yang
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Wendy Noble
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Angela Bachi
- IFOM ETS‐ The AIRC Institute of Molecular OncologyMilanItaly
| | - Beatriz Gomez Perez‐Nievas
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
| | - Maria Jimenez‐Sanchez
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUK
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Cui SS, Jiang QW, Chen SD. Sex difference in biological change and mechanism of Alzheimer’s disease: from macro- to micro-landscape. Ageing Res Rev 2023; 87:101918. [PMID: 36967089 DOI: 10.1016/j.arr.2023.101918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 02/16/2023] [Accepted: 03/23/2023] [Indexed: 04/05/2023]
Abstract
Alzheimer's disease (AD) is the most common form of dementia and numerous studies reported a higher prevalence and incidence of AD among women. Although women have longer lifetime, longevity does not wholly explain the higher frequency and lifetime risk in women. It is important to understand sex differences in AD pathophysiology and pathogenesis, which could provide foundation for future clinical AD research. Here, we reviewed the most recent and relevant literature on sex differences in biological change of AD from macroscopical neuroimaging to microscopical pathologic change (neuronal degeneration, synaptic dysfunction, amyloid-beta and tau accumulation). We also discussed sex differences in cellular mechanisms related to AD (neuroinflammation, mitochondria dysfunction, oxygen stress, apoptosis, autophagy, blood-brain-barrier dysfunction, gut microbiome alteration, bulk and single cell/nucleus omics) and possible causes underlying these differences including sex-chromosome, sex hormone and hypothalamic-pituitary- adrenal (HPA) axis effects.
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Affiliation(s)
- Shi-Shuang Cui
- Department of Neurology & Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Department of Geriatrics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qian-Wen Jiang
- Department of Neurology & Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Department of Geriatrics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Sheng-Di Chen
- Department of Neurology & Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
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Sun Y, Hu HY, Hu H, Huang LY, Tan L, Yu JT. Cerebral Small Vessel Disease Burden Predicts Neurodegeneration and Clinical Progression in Prodromal Alzheimer's Disease. J Alzheimers Dis 2023; 93:283-294. [PMID: 36970905 DOI: 10.3233/jad-221207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). OBJECTIVE This study aimed to comprehensively investigated the associations of CSVD burden with cognition and AD pathologies. METHODS A total of 546 non-demented participants (mean age, 72.1 years, range, 55-89; 47.4% female) were included. The longitudinal neuropathological and clinical correlates of CSVD burden were assessed using linear mixed-effects and Cox proportional-hazard models. Partial least squares structural equation model (PLS-SEM) was used to assess the direct and indirect effects of CSVD burden on cognition. RESULTS We found that higher CSVD burden was associated with worse cognition (MMSE, β= -0.239, p = 0.006; MoCA, β= -0.493, p = 0.013), lower cerebrospinal fluid (CSF) Aβ level (β= -0.276, p < 0.001) and increased amyloid burden (β= 0.048, p = 0.002). In longitudinal, CSVD burden contributed to accelerated rates of hippocampus atrophy, cognitive decline, and higher risk of AD dementia. Furthermore, as the results of PLS-SEM, we observed both significant direct and indirect impact of advanced age (direct, β= -0.206, p < 0.001; indirect, β= -0.002, p = 0.043) and CSVD burden (direct, β= -0.096, p = 0.018; indirect, β= -0.005, p = 0.040) on cognition by Aβ-p-tau-tau pathway. CONCLUSION CSVD burden could be a prodromal predictor for clinical and pathological progression. Simultaneously, we found that the effects were mediated by the one-direction-only sequence of pathological biomarker changes starting with Aβ, through abnormal p-tau, and neurodegeneration.
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Affiliation(s)
- Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - He-Ying Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hao Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Liang-Yu Huang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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9
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Zhong S, Zhao B, Ma YH, Sun Y, Zhao YL, Liu WH, Ou YN, Dong Q, Tan L, Yu JT. Associations of Physical Activity with Alzheimer’s Disease Pathologies and Cognition: The CABLE Study. J Alzheimers Dis 2022; 89:483-492. [PMID: 35871345 DOI: 10.3233/jad-220389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: The associations of physical activity with Alzheimer’s disease (AD) pathologies remain controversial. Objective: To quantitatively assess the association between the frequency of physical activity with cerebrospinal fluid (CSF) biomarkers in AD and further explore the mechanism by which AD pathologies regulate the correlation between physical activity and cognition. Methods: A total of 918 participants without dementia from Chinese Alzheimer’s Biomarker and Lifestyle (CABLE) were examined in this population-based cross-sectional study. Multiple linear models were used to evaluate the associations of physical activity with CSF biomarkers and cognition. Moreover, mediation analyses were conducted to investigate the potential relationships between physical activity, AD pathologies, and cognitive function. Results: Regular physical activity was positively associated with CSF Aβ 42 (p < 0.001) and Aβ 42/40 (p < 0.001), while it was negatively associated with p-tau/Aβ 42 (p < 0.001) and t-tau/Aβ 42 (p < 0.001). Of all participants, regular physical activity was associated with increased cognitive function (p < 0.001). The interaction effect indicated that age moderated the association between physical activity frequency and CSF Aβ 42 (p = 0.014) and p-tau/Aβ 42 (p = 0.041). The impact of physical activity on cognition was mediated in part by amyloid pathologies, accounting for 4.87% to 21.56% of the total effect (p < 0.05). Conclusion: This study showed the beneficial impact of physical activity on AD pathologies and cognition in participants without dementia.
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Affiliation(s)
- Shuang Zhong
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Bing Zhao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yong-Li Zhao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wen-Hui Liu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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10
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Salvadó G, Milà-Alomà M, Shekari M, Ashton NJ, Operto G, Falcon C, Cacciaglia R, Minguillon C, Fauria K, Niñerola-Baizán A, Perissinotti A, Benedet AL, Kollmorgen G, Suridjan I, Wild N, Molinuevo JL, Zetterberg H, Blennow K, Suárez-Calvet M, Gispert JD. Reactive astrogliosis is associated with higher cerebral glucose consumption in the early Alzheimer's continuum. Eur J Nucl Med Mol Imaging 2022; 49:4567-4579. [PMID: 35849149 DOI: 10.1007/s00259-022-05897-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 06/28/2022] [Indexed: 11/04/2022]
Abstract
PURPOSE Glial activation is one of the earliest mechanisms to be altered in Alzheimer's disease (AD). Glial fibrillary acidic protein (GFAP) relates to reactive astrogliosis and can be measured in both cerebrospinal fluid (CSF) and blood. Plasma GFAP has been suggested to become altered earlier in AD than its CSF counterpart. Although astrocytes consume approximately half of the glucose-derived energy in the brain, the relationship between reactive astrogliosis and cerebral glucose metabolism is poorly understood. Here, we aimed to investigate the association between fluorodeoxyglucose ([18F]FDG) uptake and reactive astrogliosis, by means of GFAP quantified in both plasma and CSF for the same participants. METHODS We included 314 cognitively unimpaired participants from the ALFA + cohort, 112 of whom were amyloid-β (Aβ) positive. Associations between GFAP markers and [18F]FDG uptake were studied. We also investigated whether these associations were modified by Aβ and tau status (AT stages). RESULTS Plasma GFAP was positively associated with glucose consumption in the whole brain, while CSF GFAP associations with [18F]FDG uptake were only observed in specific smaller areas like temporal pole and superior temporal lobe. These associations persisted when accounting for biomarkers of Aβ pathology but became negative in Aβ-positive and tau-positive participants (A + T +) in similar areas of AD-related hypometabolism. CONCLUSIONS Higher astrocytic reactivity, probably in response to early AD pathological changes, is related to higher glucose consumption. With the onset of tau pathology, the observed uncoupling between astrocytic biomarkers and glucose consumption might be indicative of a failure to sustain the higher energetic demands required by reactive astrocytes.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, King's College London, Maurice Wohl Clinical Neuroscience Institute, Psychology & Neuroscience, London, UK.,NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingeniería, (CIBER-BBN), Biomateriales Y Nanomedicina, Barcelona, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain
| | - Aida Niñerola-Baizán
- Centro de Investigación Biomédica en Red Bioingeniería, (CIBER-BBN), Biomateriales Y Nanomedicina, Barcelona, Spain.,Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Andrés Perissinotti
- Centro de Investigación Biomédica en Red Bioingeniería, (CIBER-BBN), Biomateriales Y Nanomedicina, Barcelona, Spain.,Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | | | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain.,H. Lundbeck A/S, Copenhagen, Denmark
| | - Henrik Zetterberg
- Universitat Pompeu Fabra, Barcelona, Spain.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Universitat Pompeu Fabra, Barcelona, Spain.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Fragilidad Y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain. .,Servei de Neurologia, Hospital del Mar, Barcelona, Spain.
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ Wellington, 30, 08005, Barcelona, Spain. .,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain. .,Centro de Investigación Biomédica en Red Bioingeniería, (CIBER-BBN), Biomateriales Y Nanomedicina, Barcelona, Spain.
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11
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Salvadó G, Shekari M, Falcon C, Operto G, Milà-Alomà M, Sánchez-Benavides G, Cacciaglia R, Arenaza-Urquijo E, Niñerola-Baizán A, Perissinotti A, Minguillon C, Fauria K, Kollmorgen G, Suridjan I, Molinuevo JL, Zetterberg H, Blennow K, Suárez-Calvet M, Gispert JD. Brain alterations in the early Alzheimer's continuum with amyloid-β, tau, glial and neurodegeneration CSF markers. Brain Commun 2022; 4:fcac134. [PMID: 35702732 PMCID: PMC9185381 DOI: 10.1093/braincomms/fcac134] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 03/03/2022] [Accepted: 05/20/2022] [Indexed: 11/15/2022] Open
Abstract
Higher grey matter volumes/cortical thickness and fluorodeoxyglucose uptake have been consistently found in cognitively unimpaired individuals with abnormal Alzheimer’s disease biomarkers compared with those with normal biomarkers. It has been hypothesized that such transient increases may be associated with neuroinflammatory mechanisms triggered in response to early Alzheimer’s pathology. Here, we evaluated, in the earliest stages of the Alzheimer’s continuum, associations between grey matter volume and fluorodeoxyglucose uptake with CSF biomarkers of several pathophysiological mechanisms known to be altered in preclinical Alzheimer’s disease stages. We included 319 cognitively unimpaired participants from the ALFA+ cohort with available structural MRI, fluorodeoxyglucose PET and CSF biomarkers of amyloid-β and tau pathology (phosphorylated tau and total tau), synaptic dysfunction (neurogranin), neuronal and axonal injury (neurofilament light), glial activation (soluble triggering receptor on myeloid cells 2, YKL40, GFAP, interleukin-6 and S100b) and α-synuclein using the Roche NeuroToolKit. We first used the amyloid-β/tau framework to investigate differences in the neuroimaging biomarkers between preclinical Alzheimer’s disease stages. Then, we looked for associations between the neuroimaging markers and all the CSF markers. Given the non-negative nature of the concentrations of CSF biomarkers and their high collinearity, we clustered them using non-negative matrix factorization approach (components) and sought associations with the imaging markers. By groups, higher grey matter volumes were found in the amyloid-β-positive tau-negative participants with respect to the reference amyloid-β-negative tau-negative group. Both amyloid-β and tau-positive participants showed higher fluorodeoxyglucose uptake than tau-negative individuals. Using the obtained components, we observed that tau pathology accompanied by YKL-40 (astrocytic marker) was associated with higher grey matter volumes and fluorodeoxyglucose uptake in extensive brain areas. Higher grey matter volumes in key Alzheimer-related regions were also found in association with two other components characterized by a higher expression of amyloid-β in combination with different glial markers: one with higher GFAP and S100b levels (astrocytic markers) and the other one with interleukin-6 (pro-inflammatory). Notably, these components’ expression had different behaviours across amyloid-β/tau stages. Taken together, our results show that CSF amyloid-β and phosphorylated tau, in combination with different aspects of glial response, have distinctive associations with higher grey matter volumes and increased glucose metabolism in key Alzheimer-related regions. These mechanisms combine to produce transient higher grey matter volumes and fluorodeoxyglucose uptake at the earliest stages of the Alzheimer’s continuum, which may revert later on the course of the disease when neurodegeneration drives structural and metabolic cerebral changes.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Eider Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aida Niñerola-Baizán
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Andrés Perissinotti
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
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12
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Xie Q, Ni M, Gao F, Dai LB, Lv XY, Zhang YF, Shi Q, Zhu XX, Xie JK, Shen Y, Wang SC. Correlation between Cerebrospinal Fluid Core Alzheimer's Disease Biomarkers and β-Amyloid PET in Chinese Dementia Population. ACS Chem Neurosci 2022; 13:1558-1565. [PMID: 35476397 DOI: 10.1021/acschemneuro.2c00120] [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] [Indexed: 01/05/2023] Open
Abstract
The current diagnoses of Alzheimer's disease (AD) mainly rely on such measures as amyloid-β (Aβ) and tau neuropathology biomarkers in vivo via cerebrospinal fluid (CSF) and positron emission tomography (PET) imaging, which had been systematically studied in Caucasian individuals, whereas diagnostic performances of these approaches in Chinese dementia population still remain unclear. This study investigated the associations between the levels of CSF core AD biomarkers, including phosphorylated tau (p-Tau181), total tau (t-Tau), Aβ42, and Aβ40 measured by the single-molecule array (Simoa) and cerebral Aβ deposition status assessed by 18F-Florbetapir PET (Aβ PET), and evaluated the predictive values of CSF core AD biomarkers in discriminating Aβ PET status in a clinical dementia cohort of the Chinese population, which consisted of patients with mild cognitive impairment (MCI), AD dementia, and non-Alzheimer's dementia disease (Non-ADD). Global standard uptake value ratios (SUVRs) were calculated by Aβ PET, which was divided into positive (Aβ+) and negative (Aβ-) through visual analysis. CSF p-Tau181 and p-Tau181/t-Tau ratio were positively correlated with the global SUVR, while CSF Aβ42 and Aβ42/Aβ40 ratio were negatively correlated with the global SUVR. CSF Aβ40 has the highest predictive value in discriminating the MCI group from the AD group, while CSF p-Tau181 was applied to discriminate the AD group from the non-ADD group. CSF Aβ42/Aβ40 ratio, as the optimal predictive factor, was combined with APOE ε4 status rather than age and education, which could improve the predictive ability in differentiating the Aβ+ group from the Aβ- group. The results reveal the universal applicability of CSF core AD biomarkers and Aβ PET imaging in Chinese dementia population, which is helpful in clinical practice and drug trials in China.
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Affiliation(s)
- Qiang Xie
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Ming Ni
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Feng Gao
- Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Lin-Bin Dai
- Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Xin-Yi Lv
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Yi-Fan Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Qin Shi
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Xing-Xing Zhu
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Ji-Kui Xie
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Yong Shen
- Institute on Aging and Brain Disorders, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Anhui Province Key Laboratory of Biomedical Aging Research, Hefei 230001, China
| | - Shi-Cun Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
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13
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Salvadó G, Milà‐Alomà M, Shekari M, Minguillon C, Fauria K, Niñerola‐Baizán A, Perissinotti A, Kollmorgen G, Buckley C, Farrar G, Zetterberg H, Blennow K, Suárez‐Calvet M, Molinuevo JL, Gispert JD. Cerebral amyloid-β load is associated with neurodegeneration and gliosis: Mediation by p-tau and interactions with risk factors early in the Alzheimer's continuum. Alzheimers Dement 2021; 17:788-800. [PMID: 33663013 PMCID: PMC8252618 DOI: 10.1002/alz.12245] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 10/06/2020] [Accepted: 10/24/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The association between cerebral amyloid-β accumulation and downstream CSF biomarkers is not fully understood, particularly in asymptomatic stages. METHODS In 318 cognitively unimpaired participants, we assessed the association between amyloid-β PET (Centiloid), and cerebrospinal fluid (CSF) biomarkers of several pathophysiological pathways. Interactions by Alzheimer's disease risk factors (age, sex and APOE-ε4), and the mediation effect of tau and neurodegeneration were also investigated. RESULTS Centiloids were positively associated with CSF biomarkers of tau pathology (p-tau), neurodegeneration (t-tau, NfL), synaptic dysfunction (neurogranin) and neuroinflammation (YKL-40, GFAP, sTREM2), presenting interactions with age (p-tau, t-tau, neurogranin) and sex (sTREM2, NfL). Most of these associations were mediated by p-tau, except for NfL. The interaction between sex and amyloid-β on sTREM2 and NfL was also tau-independent. DISCUSSION Early amyloid-β accumulation has a tau-independent effect on neurodegeneration and a tau-dependent effect on neuroinflammation. Besides, sex has a modifier effect on these associations independent of tau.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
| | - Marta Milà‐Alomà
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Aida Niñerola‐Baizán
- Nuclear Medicine DepartmentHospital Clínic BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER‐BBN)BarcelonaSpain
| | - Andrés Perissinotti
- Nuclear Medicine DepartmentHospital Clínic BarcelonaBarcelonaSpain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER‐BBN)BarcelonaSpain
| | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Marc Suárez‐Calvet
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
- Servei de NeurologiaHospital del MarBarcelonaSpain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER‐BBN)BarcelonaSpain
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