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Aliaga A, Therriault J, Quispialaya K, Aliaga A, Kunach P, Macedo AC, Hopewell R, Rahmouni N, Soucy JP, Massarweh G, Guiot MC, Chan T, Klostranec J, Abreu Diaz AM, Rocha A, Carello-Collar G, Machado LS, De Bastiani MA, Guerini de Souza D, Souza DO, Zimmer AR, Gauthier S, Pascoal TA, Zimmer ER, Rosa-Neto P. Autoradiographic comparison between [ 11C]PiB and [ 18F]AZD4694 in human brain tissue. EJNMMI Res 2025; 15:30. [PMID: 40167827 PMCID: PMC11961831 DOI: 10.1186/s13550-025-01216-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Accepted: 03/02/2025] [Indexed: 04/02/2025] Open
Abstract
BACKGROUND Amyloid-β imaging through positron emission tomography (PET) has significantly transformed Alzheimer's disease (AD) research. [11C]PiB has been widely used for imaging β-amyloid plaques due to its high affinity and selectivity for amyloid deposits. [18F]AZD4694 is a more recently developed amyloid-PET imaging agent, which structurally resembles PiB and has less non-specific binding in the white matter than other 18F-labeled compounds. The purpose of this study is to compare the in vitro binding properties of the amyloid-PET radiotracers [11C]PiB and [18F]AZD4694 in post-mortem human brain tissue. Total binding was assessed by autoradiography in prefrontal, inferior parietal, posterior cingulate cortices and hippocampal sections of healthy control (HC) and AD autopsy-confirmed brain tissues. Furthermore, the displacement of [18F]AZD4694 by unlabeled PiB was evaluated in the above-mentioned sections of AD brain tissues. RESULTS For both radiotracers, we found significant differences (p < 0.0001) between HC and AD tissues binding in the prefrontal cortex ([11C]PiB Cohen's d = 3.424, [18F]AZD4694 Cohen's d = 5.070), inferior parietal cortex ([11C]PiB Cohen's d = 3.156, [18F]AZD4694 Cohen's d = 3.959), posterior cingulate cortex ([11C]PiB Cohen's d = 1.781, [18F]AZD4694 Cohen's d = 3.434), and hippocampus ([11C]PiB Cohen's d = 1.320, [18F]AZD4694 Cohen's d = 3.696). Higher binding was detected for [18F]AZD4694 compared to [11C]PiB in AD prefrontal, inferior parietal and posterior cingulate cortices, while binding in the hippocampus was comparable for both radioligands. Strong correlations between [18]AZD4694 and [11C]PiB were found in the prefrontal (R = 0.959, p < 0.0001), inferior parietal (R = 0.893, p < 0.0001), posterior cingulate (R = 0.838, p = 0.0006) cortices and hippocampus (R = 0.750, p < 0.0001). Bland-Altman analyses revealed strong agreement between [11C]PiB and [18F]AZD4694 in the prefrontal, inferior parietal, and posterior cingulate cortices, but lower agreement in the hippocampus. Displacement studies confirmed high binding affinity of PiB in all tissues, indicating that both amyloid-PET agents compete for the same binding sites. CONCLUSIONS This head-to-head study provides evidence that while [18F]AZD4694 and [11C]PiB bindings are highly correlated with both tracers competing for the same binding sites, [18F]AZD4694 has a slightly higher effect size when comparing between neuropathologically-confirmed AD and HC brain tissues.
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Affiliation(s)
- Antonio Aliaga
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
- Research Institute of the McGill University Health Centre, 1001, boul. Decarie -Bloc E, Offices ES2.1602, Montreal, QC, 1001H4A 3J1, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Kely Quispialaya
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Research Institute of the McGill University Health Centre, 1001, boul. Decarie -Bloc E, Offices ES2.1602, Montreal, QC, 1001H4A 3J1, Canada
- Montreal Neurological Institute, Montreal, Canada
- Department of Experimental Medicine, McGill University, Montreal, Canada
| | - Arturo Aliaga
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Peter Kunach
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Arthur C Macedo
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | | | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | | | | | - Marie-Christine Guiot
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Department of Pathology, McGill University Health Center, Montreal, Canada
| | - Tevy Chan
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Jesse Klostranec
- Department of Diagnostic Radiology, McGill University Health Center, Montreal, Canada
| | - Aida Mary Abreu Diaz
- Department of Pharmacology and Physiology, University of Montreal, Montreal, Canada
| | - Andreia Rocha
- Department of Psychiatry, Pittsburgh University, Pittsburgh, USA
| | - Giovanna Carello-Collar
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
| | - Luiza S Machado
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
| | - Marco Antônio De Bastiani
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
| | - Débora Guerini de Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
| | - Diogo O Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil
| | - Aline R Zimmer
- Department of Pharmacology, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | | | - Eduardo R Zimmer
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada.
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul, 2600 Ramiro Barcelos Street, Porto Alegre, Brazil.
- Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
- Brain Institute of Rio Grande Do Sul, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, 6875 La Salle Blvd - FBC Room 3149, Montreal, QC, H4H 1R3, Canada.
- Research Institute of the McGill University Health Centre, 1001, boul. Decarie -Bloc E, Offices ES2.1602, Montreal, QC, 1001H4A 3J1, Canada.
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.
- Montreal Neurological Institute, Montreal, Canada.
- Department of Experimental Medicine, McGill University, Montreal, Canada.
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Tao W, Lu X, Yuan S, Ye P, Zhang Z, Guan Q, Li H. Unstable functional brain states and reduced cerebro-cerebellar modularity in elderly individuals with subjective cognitive decline. Neuroimage 2025; 305:120969. [PMID: 39667538 DOI: 10.1016/j.neuroimage.2024.120969] [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: 05/21/2024] [Revised: 08/26/2024] [Accepted: 12/09/2024] [Indexed: 12/14/2024] Open
Abstract
The preclinical stage of Alzheimer's Disease (AD) holds great potential for intervention, therefore, it is crucial to elucidate the neural mechanisms underlying the progression of subjective cognitive decline (SCD). Previous studies have predominantly focused on the neural changes in the cerebrum associated with SCD, but have relatively neglected the cerebellum, and its functional relationship with the cerebrum. In the current study, we employed dynamic functional connectivity and large-scale brain network approaches to investigate the pathological characteristics of dynamic brain states and cerebro-cerebellar collaboration between SCD (n = 32) and the healthy elderly (n = 29) using resting-state fMRI. Two-way repeated measures ANOVA and permutation t-tests revealed significant group differences, with individuals with SCD exhibiting shorter state duration and more frequent transitions between states compared to the healthy elderly individuals. Additionally, individuals with SCD showed lower levels of intracerebellar functional connectivity, but higher levels of cerebellar-cerebral functional integration. Furthermore, the hub nodes of the functional networks in SCD shifted between the cerebellum and cerebrum across different brain states. These findings indicate that SCD exhibits greater state instability but may compensate for the negative effects of early disease by integrating cerebellar and cerebral networks, thereby maintaining cognitive performance. This study enhances our theoretical understanding of cerebellar-cerebral relationship changes in the early stages of AD and provides evidence for early interventions targeting the cerebellum.
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Affiliation(s)
- Wuhai Tao
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
| | - Xiaojie Lu
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China
| | - Shuaike Yuan
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China
| | - Peixuan Ye
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Qing Guan
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China; University of Health and Rehabilitation Sciences,School of Social Development and Health Management, Qingdao, Shandong, 266113, China.
| | - Hehui Li
- Center for Brain Disorders and Cognitive Sciences, School of Psychology, Shenzhen University, Shenzhen 518060, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China.
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Cai H, Sheng X, Wu G, Hu B, Cheung YM, Chen J. Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:17266-17280. [PMID: 37566497 PMCID: PMC10858979 DOI: 10.1109/tnnls.2023.3301456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2023]
Abstract
Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network much earlier before the onset of clinical symptoms, making its early diagnosis possible. Current brain network analyses treat high-dimensional network data as a regular matrix or vector, which destroys the essential network topology, thereby seriously affecting diagnosis accuracy. In this context, harmonic waves provide a solid theoretical background for exploring brain network topology. However, the harmonic waves are originally intended to discover neurological disease propagation patterns in the brain, which makes it difficult to accommodate brain disease diagnosis with high heterogeneity. To address this challenge, this article proposes a network manifold harmonic discriminant analysis (MHDA) method for accurately detecting AD. Each brain network is regarded as an instance drawn on a Stiefel manifold. Every instance is represented by a set of orthonormal eigenvectors (i.e., harmonic waves) derived from its Laplacian matrix, which fully respects the topological structure of the brain network. An MHDA method within the Stiefel space is proposed to identify the group-dependent common harmonic waves, which can be used as group-specific references for downstream analyses. Extensive experiments are conducted to demonstrate the effectiveness of the proposed method in stratifying cognitively normal (CN) controls, mild cognitive impairment (MCI), and AD.
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Affiliation(s)
- Hongmin Cai
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China
| | - Xiaoqi Sheng
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China
| | - Guorong Wu
- Department of Psychiatry and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bin Hu
- School of Medical Technology at Beijing Institute of Technology, Beijing Institute of Technology, Beijing, China
| | - Yiu-Ming Cheung
- Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China
| | - Jiazhou Chen
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China
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Feng L, Li B, Yong SS, Wen X, Tian Z. The emerging role of exercise in Alzheimer's disease: Focus on mitochondrial function. Ageing Res Rev 2024; 101:102486. [PMID: 39243893 DOI: 10.1016/j.arr.2024.102486] [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: 07/18/2024] [Accepted: 08/31/2024] [Indexed: 09/09/2024]
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disease characterized by memory impairment and cognitive dysfunction, which eventually leads to the disability and mortality of older adults. Although the precise mechanisms by which age promotes the development of AD remains poorly understood, mitochondrial dysfunction plays a central role in the development of AD. Currently, there is no effective treatment for this debilitating disease. It is well accepted that exercise exerts neuroprotective effects by ameliorating mitochondrial dysfunction in the neurons of AD, which involves multiple mechanisms, including mitochondrial dynamics, biogenesis, mitophagy, transport, and signal transduction. In addition, exercise promotes mitochondria communication with other organelles in AD neurons, which should receive more attentions in the future.
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Affiliation(s)
- Lili Feng
- Department of Sports Science, College of Education, Zhejiang University, Hangzhou 310030, China.
| | - Bowen Li
- Department of Sports Science, College of Education, Zhejiang University, Hangzhou 310030, China
| | - Su Sean Yong
- Department of Sports Science, College of Education, Zhejiang University, Hangzhou 310030, China
| | - Xu Wen
- Department of Sports Science, College of Education, Zhejiang University, Hangzhou 310030, China.
| | - Zhenjun Tian
- Institute of Sports Biology, College of Physical Education, Shaanxi Normal University, Xi'an 710119, China.
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Maiella M, Mencarelli L, Casula EP, Borghi I, Assogna M, di Lorenzo F, Bonnì S, Pezzopane V, Martorana A, Koch G. Breakdown of TMS evoked EEG signal propagation within the default mode network in Alzheimer's disease. Clin Neurophysiol 2024; 167:177-188. [PMID: 39332078 DOI: 10.1016/j.clinph.2024.09.007] [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: 03/13/2024] [Revised: 09/09/2024] [Accepted: 09/13/2024] [Indexed: 09/29/2024]
Abstract
BACKGROUND The neural activity of the Default Mode Network (DMN) is disrupted in patients with In Alzheimer's disease (AD). OBJECTIVES We used a novel multimodal approach to track neural signal propagation within the DMN in AD patients. METHODS Twenty mild to moderate AD patients were recruited. We used transcranial magnetic stimulation (TMS) pulses to probe with a millisecond time resolution the propagation of evoked electroencephalography (EEG) signal following the neural activation of the Precuneus (PC), which is a key hub area of the DMN. Moreover, functional and structural magnetic resonance imaging (MRI) data were collected to reconstruct individual features of the DMN. RESULTS In AD patients a probe TMS pulse applied over the PC evokes an increased local activity unmasking underlying hyperexcitability. In contrast, the EEG evoked neural signal did not propagate efficiently within the DMN showing a remarkable breakdown of signal propagation. fMRI and structural tractography showed that impaired signal propagation was related to the same connectivity matrices derived from DMN BOLD signal and transferred by specific white matter bundles forming the cingulum. These features were not detectable stimulating other areas (left dorsolateral prefrontal cortex) or for different networks (fronto-parietal network). Finally, connectivity breakdown was associated with cognitive impairment, as measured with the Clinical Dementia Rating Scale sum of boxes (CDR-SB). CONCLUSIONS TMS-EEG in AD shows both local hyperexcitability and a lack of signal propagation within the DMN. These neurophysiological features also correlate with structural and cognitive attributes of the patients. SIGNIFICANCE Neuronavigated TMS-EEG may be used as a novel neurophysiological biomarker of DMN connectivity in AD patients.
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Affiliation(s)
- Michele Maiella
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Lucia Mencarelli
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Elias P Casula
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Ilaria Borghi
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | - Martina Assogna
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Francesco di Lorenzo
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Sonia Bonnì
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Valentina Pezzopane
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy
| | | | - Giacomo Koch
- Department of Behavioural and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, and Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara, Italy.
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Andrade K, Pacella V. The unique role of anosognosia in the clinical progression of Alzheimer's disease: a disorder-network perspective. Commun Biol 2024; 7:1384. [PMID: 39448784 PMCID: PMC11502706 DOI: 10.1038/s42003-024-07076-7] [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: 06/20/2024] [Accepted: 10/14/2024] [Indexed: 10/26/2024] Open
Abstract
Alzheimer's disease (AD) encompasses a long continuum from a preclinical phase, characterized by neuropathological alterations albeit normal cognition, to a symptomatic phase, marked by its clinical manifestations. Yet, the neural mechanisms responsible for cognitive decline in AD patients remain poorly understood. Here, we posit that anosognosia, emerging from an error-monitoring failure due to early amyloid-β deposits in the posterior cingulate cortex, plays a causal role in the clinical progression of AD by preventing patients from being aware of their deficits and implementing strategies to cope with their difficulties, thus fostering a vicious circle of cognitive decline.
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Affiliation(s)
- Katia Andrade
- Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Assistance Publique-Hôpitaux de Paris (AP-HP), Sorbonne University, Pitié-Salpêtrière Hospital, 75013, Paris, France.
- FrontLab, Paris Brain Institute (Institut du Cerveau, ICM), AP-HP, Pitié-Salpêtrière Hospital, 75013, Paris, France.
| | - Valentina Pacella
- IUSS Cognitive Neuroscience (ICON) Center, Scuola Universitaria Superiore IUSS, Pavia, 27100, Italy
- Brain Connectivity and Behaviour Laboratory, Paris, France
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Tang R, Franz CE, Hauger RL, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Williams ME, Elman JA, Kremen WS. Early Cortical Microstructural Changes in Aging Are Linked to Vulnerability to Alzheimer's Disease Pathology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:975-985. [PMID: 38878863 PMCID: PMC11756816 DOI: 10.1016/j.bpsc.2024.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/09/2024] [Accepted: 05/29/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND Early identification of Alzheimer's disease (AD) risk is critical for improving treatment success. Cortical thickness is a macrostructural measure used to assess neurodegeneration in AD. However, cortical microstructural changes appear to precede macrostructural atrophy and may improve early risk identification. Currently, whether cortical microstructural changes in aging are linked to vulnerability to AD pathophysiology remains unclear in nonclinical populations, who are precisely the target for early risk identification. METHODS In 194 adults, we calculated magnetic resonance imaging-derived maps of changes in cortical mean diffusivity (microstructure) and cortical thickness (macrostructure) over 5 to 6 years (mean age: time 1 = 61.82 years; time 2 = 67.48 years). Episodic memory was assessed using 3 well-established tests. We obtained positron emission tomography-derived maps of AD pathology deposition (amyloid-β, tau) and neurotransmitter receptors (cholinergic, glutamatergic) implicated in AD pathophysiology. Spatial correlational analyses were used to compare pattern similarity among maps. RESULTS Spatial patterns of cortical macrostructural changes resembled patterns of cortical organization sensitive to age-related processes (r = -0.31, p < .05), whereas microstructural changes resembled the patterns of tau deposition in AD (r = 0.39, p = .038). Individuals with patterns of microstructural changes that more closely resembled stereotypical tau deposition exhibited greater memory decline (β = 0.22, p = .029). Microstructural changes and AD pathology deposition were enriched in areas with greater densities of cholinergic and glutamatergic receptors (ps < .05). CONCLUSIONS Patterns of cortical microstructural changes were more AD-like than patterns of macrostructural changes, which appeared to reflect more general aging processes. Microstructural changes may better inform early risk prediction efforts as a sensitive measure of vulnerability to pathological processes prior to overt atrophy and cognitive decline.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California.
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California; Department of Neurosciences, University of California San Diego, La Jolla, California
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California; Desert Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California; Department of Radiology, University of California San Diego, La Jolla, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - McKenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
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Wang X, Zhou H, Yan CQ, Shi GX, Zhou P, Huo JW, Yang JW, Zhang YN, Wang L, Cao Y, Liu CZ. Cognitive and Hippocampal Changes in Older Adults With Subjective Cognitive Decline After Acupuncture Intervention. Am J Geriatr Psychiatry 2024; 32:1014-1027. [PMID: 38521736 DOI: 10.1016/j.jagp.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/01/2024] [Accepted: 03/02/2024] [Indexed: 03/25/2024]
Abstract
OBJECTIVE Converging evidence indicates that subjective cognitive decline (SCD) could be an early indicator of dementia. The hippocampus is the earliest affected region during the progression of cognitive impairment. However, little is known about whether and how acupuncture change the hippocampal structure and function of SCD individuals. METHODS Here, we used multi-modal MRI to reveal the mechanism of acupuncture in treating SCD. Seventy-two older participants were randomized into acupuncture or sham acupuncture group and treated for 12 weeks. RESULTS At the end of the intervention, compared to sham acupuncture, participants with acupuncture treatment showed improvement in composite Z score from multi-domain neuropsychological tests, as well as increased hippocampal volume and functional connectivity. Moreover, the greater white matter integrity of the fornix, which is the major output tract of the hippocampus, was shown in the acupuncture group. CONCLUSION These findings suggest that acupuncture may improve the cognitive function of SCD individuals, and increase hippocampal volume on the regional level and enhance the structural and functional connectivity of hippocampus on the connective level.
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Affiliation(s)
- Xu Wang
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China; School of Life Sciences (XW), Beijing University of Chinese Medicine, Beijing, China
| | - Hang Zhou
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Chao-Qun Yan
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Guang-Xia Shi
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Ping Zhou
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Jian-Wei Huo
- Department of Radiology (J-WH, Y-NZ), Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Dongcheng District, Beijing, China
| | - Jing-Wen Yang
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Ya-Nan Zhang
- Department of Radiology (J-WH, Y-NZ), Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Dongcheng District, Beijing, China
| | - Lu Wang
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Yan Cao
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China
| | - Cun-Zhi Liu
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina (XW, HZ, C-QY, G-XS, PZ, J-WY, LW, YC, C-ZL), Beijing University of Chinese Medicine, Beijing, China.
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9
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Sun L, Zhao T, Liang X, Xia M, Li Q, Liao X, Gong G, Wang Q, Pang C, Yu Q, Bi Y, Chen P, Chen R, Chen Y, Chen T, Cheng J, Cheng Y, Cui Z, Dai Z, Deng Y, Ding Y, Dong Q, Duan D, Gao JH, Gong Q, Han Y, Han Z, Huang CC, Huang R, Huo R, Li L, Lin CP, Lin Q, Liu B, Liu C, Liu N, Liu Y, Liu Y, Lu J, Ma L, Men W, Qin S, Qiu J, Qiu S, Si T, Tan S, Tang Y, Tao S, Wang D, Wang F, Wang J, Wang P, Wang X, Wang Y, Wei D, Wu Y, Xie P, Xu X, Xu Y, Xu Z, Yang L, Yuan H, Zeng Z, Zhang H, Zhang X, Zhao G, Zheng Y, Zhong S, He Y. Functional connectome through the human life span. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.12.557193. [PMID: 37745373 PMCID: PMC10515818 DOI: 10.1101/2023.09.12.557193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.
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Affiliation(s)
- Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Qian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chenxuan Pang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qian Yu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Pindong Chen
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Rui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Zhengjia Dai
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yao Deng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ruiwang Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, China
- Department of Education and Research, Taipei City Hospital, Taipei, China
| | - Qixiang Lin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Chao Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Yong Liu
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Jing Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji’nan, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haibo Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Suyu Zhong
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | | | | | | | | | | | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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10
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Meng Y, Kalia LV, Kalia SK, Hamani C, Huang Y, Hynynen K, Lipsman N, Davidson B. Current Progress in Magnetic Resonance-Guided Focused Ultrasound to Facilitate Drug Delivery across the Blood-Brain Barrier. Pharmaceutics 2024; 16:719. [PMID: 38931843 PMCID: PMC11206305 DOI: 10.3390/pharmaceutics16060719] [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: 03/19/2024] [Revised: 05/12/2024] [Accepted: 05/17/2024] [Indexed: 06/28/2024] Open
Abstract
This review discusses the current progress in the clinical use of magnetic resonance-guided focused ultrasound (MRgFUS) and other ultrasound platforms to transiently permeabilize the blood-brain barrier (BBB) for drug delivery in neurological disorders and neuro-oncology. Safety trials in humans have followed on from extensive pre-clinical studies, demonstrating a reassuring safety profile and paving the way for numerous translational clinical trials in Alzheimer's disease, Parkinson's disease, and primary and metastatic brain tumors. Future directions include improving ultrasound delivery devices, exploring alternative delivery approaches such as nanodroplets, and expanding the application to other neurological conditions.
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Affiliation(s)
- Ying Meng
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M4N 3M5, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Lorraine V. Kalia
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Suneil K. Kalia
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M4N 3M5, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), University Health Network, Toronto, ON M5T 1M8, Canada
- KITE Research Institute, University Health Network, Toronto, ON M5G 2A2, Canada
| | - Clement Hamani
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M4N 3M5, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Yuexi Huang
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | | | - Nir Lipsman
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M4N 3M5, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
| | - Benjamin Davidson
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON M4N 3M5, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada
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11
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Seoane S, van den Heuvel M, Acebes Á, Janssen N. The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis. Brain Commun 2024; 6:fcae128. [PMID: 38665961 PMCID: PMC11043657 DOI: 10.1093/braincomms/fcae128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 02/28/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.
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Affiliation(s)
- Sara Seoane
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Instituto Universitario de Neurociencia (IUNE), University of La Laguna, Tenerife 38200, Spain
| | - Martijn van den Heuvel
- Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
- Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam 1081 HV, The Netherlands
| | - Ángel Acebes
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Department of Basic Medical Sciences, University of La Laguna, Tenerife 38200, Spain
| | - Niels Janssen
- Institute of Biomedical Technologies (ITB), University of La Laguna, Tenerife 38200, Spain
- Instituto Universitario de Neurociencia (IUNE), University of La Laguna, Tenerife 38200, Spain
- Department of Cognitive, Social and Organizational Psychology, University of La Laguna, Tenerife 38200, Spain
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12
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Stocks J, Gibson E, Popuri K, Beg MF, Rosen H, Wang L. Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia. Alzheimer Dis Assoc Disord 2024; 38:112-119. [PMID: 38812447 PMCID: PMC11141524 DOI: 10.1097/wad.0000000000000611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 02/07/2024] [Indexed: 05/31/2024]
Abstract
PURPOSE Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited. METHODS Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA). RESULTS Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus. CONCLUSIONS This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
| | - Erin Gibson
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada, M4N 3M5
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
- Memorial University of Newfoundland, Department of Computer Science, St. John’s, NL, Canada
| | - Mirza Faisal Beg
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
| | - Howard Rosen
- School of Medicine, University of California, San Francisco, USA, 94143
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA 43210
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13
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Fonseca CS, Baker SL, Dobyns L, Janabi M, Jagust WJ, Harrison TM. Tau accumulation and atrophy predict amyloid independent cognitive decline in aging. Alzheimers Dement 2024; 20:2526-2537. [PMID: 38334195 PMCID: PMC11032527 DOI: 10.1002/alz.13654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/15/2023] [Accepted: 11/30/2023] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Amyloid beta (Aβ) and tau pathology are cross-sectionally associated with atrophy and cognitive decline in aging and Alzheimer's disease (AD). METHODS We investigated relationships between concurrent longitudinal measures of Aβ (Pittsburgh compound B [PiB] positron emission tomography [PET]), tau (flortaucipir [FTP] PET), atrophy (structural magnetic resonance imaging), episodic memory (EM), and non-memory (NM) in 78 cognitively healthy older adults (OA). RESULTS Entorhinal FTP change was correlated with EM decline regardless of Aβ, but meta-temporal FTP and global PiB change were only associated with EM and NM decline in Aβ+ OA. Voxel-wise analyses revealed significant associations between temporal lobe FTP change and EM decline in all groups. PiB and FTP change were not associated with structural change, suggesting a functional or microstructural mechanism linking these measures to cognitive decline. DISCUSSION Our results show that longitudinal Aβ is linked to cognitive decline only in the presence of elevated Aβ, but longitudinal temporal lobe tau is associated with memory decline regardless of Aβ status. HIGHLIGHTS Entorhinal tau change was associated with memory decline in older adults (OA), regardless of amyloid beta (Aβ). Greater meta-region of interest (ROI) tau change correlated with memory decline in Aβ+ OA. Voxel-wise temporal tau change correlated with memory decline, regardless of Aβ. Meta-ROI tau and global amyloid change correlated with non-memory change in Aβ+ OA. Tau and amyloid accumulation were not associated with structural change in OA.
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Affiliation(s)
- Corrina S. Fonseca
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Lindsey Dobyns
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Mustafa Janabi
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - William J. Jagust
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
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14
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Farokhi Larijani S, Hassanzadeh G, Zahmatkesh M, Radfar F, Farahmandfar M. Intranasal insulin intake and exercise improve memory function in amyloid-β induced Alzheimer's-like disease in rats: Involvement of hippocampal BDNF-TrkB receptor. Behav Brain Res 2024; 460:114814. [PMID: 38104636 DOI: 10.1016/j.bbr.2023.114814] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/13/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
The most prevalent type of dementia, Alzheimer's disease (AD), is a compelling illustration of the link between cognitive deficits and neurophysiological anomalies. We investigated the possible protective effect of intranasal insulin intake with exercise on amyloid-β (Aβ)-induced neuronal damage. The level of hippocampal brain-derived neurotrophic factor (BDNF) and tropomyosin-related kinase B (TrkB) were analyzed to understand the involvement of BDNF-TrkB pathway in this modulation. In this study, we induced AD-like pathology by amyloid-β (Aβ) administration. Then, we examined the impact of a 4-week pretreatment of moderate treadmill exercise and intranasal intake of insulin on working and spatial memory in male Wistar rats. We also analyzed the mechanisms of improved memory and anxiety through changes in the protein level of BDNF and TrkB. Results showed that animals received Aβ had impaired working memory, increased anxiety which were accompanied by lower protein levels of BDNF and TrkB in the hippocampus. The exercise training and intranasal insulin improved working memory deficits, decreased anxiety, and increased BDNF, and TrkB levels in the hippocampus of animals received Aβ. Our finding of improved memory performance after intranasal intake of insulin and exercise may be of significance for the treatment of memory impairments and anxiety-like behavior in AD.
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Affiliation(s)
- Setare Farokhi Larijani
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Gholamreza Hassanzadeh
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Zahmatkesh
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Forough Radfar
- Department of Behavioral and Cognitive Sciences in Sports, Sports and Health Sciences Faculty, University of Tehran, Tehran, Iran
| | - Maryam Farahmandfar
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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15
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Li W, Zhang M, Huang R, Hu J, Wang L, Ye G, Meng H, Lin X, Liu J, Li B, Zhang Y, Li Y. Topographic metabolism-function relationships in Alzheimer's disease: A simultaneous PET/MRI study. Hum Brain Mapp 2024; 45:e26604. [PMID: 38339890 DOI: 10.1002/hbm.26604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 12/20/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024] Open
Abstract
Disruptions of neural metabolism and function occur in parallel during Alzheimer's disease (AD). While many studies have shown diverse metabolic-functional relationships in specific brain regions, much less is known about how large-scale network-level functional activity is associated with the topology of metabolism in AD. In this study, we took the advantages of simultaneous PET/MRI and multivariate analyses to investigate the associations between AD-related stereotypical spatial patterns (topographies) of glucose metabolism, measured by fluorodeoxyglucose PET, and functional connectivity, measured by resting-state functional MRI. A total of 101 participants, including 37 patients with AD, 25 patients with mild cognitive impairment (MCI), and 39 cognitively normal controls, underwent PET/MRI scans and cognitive assessments. Three pairs of distinct but optimally correlated metabolic and functional topographies were identified, encompassing large-scale networks including the default-mode, executive and control, salience, attention, and subcortical networks. Importantly, the metabolic-functional associations were not only limited to one-to-one-corresponding regions, but also occur in remote and non-overlapping regions. Furthermore, both glucose metabolism and functional connectivity, as well as their linkages, exhibited various degrees of disruptions in patients with MCI and AD, and were correlated with cognitive decline. In conclusion, our results support distributed and heterogeneous topographic associations between metabolism and function, which are jeopardized by AD. Findings of this study may deepen our understanding of the pathological mechanism of AD through the perspectives of both local energy efficiency and long-term interactions between synaptic disruption and functional disconnection contributing to the clinical symptomatology in AD.
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Affiliation(s)
- Wenli Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruodong Huang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jialin Hu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Lijun Wang
- Department of Neurovascular Center, Changhai Hospital, Naval Medical University, Shanghai, China
| | - Guanyu Ye
- Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongping Meng
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaozhu Lin
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Ruijin Center, Shanghai, China
| | - Yaoyu Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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16
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Schaffer Aguzzoli C, Ferreira PCL, Povala G, Ferrari-Souza JP, Bellaver B, Soares Katz C, Zalzale H, Lussier FZ, Rohden F, Abbas S, Leffa DT, Scop Medeiros M, Therriault J, Benedet AL, Tissot C, Servaes S, Rahmouni N, Cassa Macedo A, Bezgin G, Kang MS, Stevenson J, Pallen V, Cohen A, Lopez OL, Tudorascu DL, Klunk WE, Villemagne VL, Soucy JP, Zimmer ER, Schilling LP, Karikari TK, Ashton NJ, Zetterberg H, Blennow K, Gauthier S, Valcour V, Miller BL, Rosa-Neto P, Pascoal TA. Neuropsychiatric Symptoms and Microglial Activation in Patients with Alzheimer Disease. JAMA Netw Open 2023; 6:e2345175. [PMID: 38010651 PMCID: PMC10682836 DOI: 10.1001/jamanetworkopen.2023.45175] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/15/2023] [Indexed: 11/29/2023] Open
Abstract
Importance Neuropsychiatric symptoms are commonly encountered and are highly debilitating in patients with Alzheimer disease. Understanding their underpinnings has implications for identifying biomarkers and treatment for these symptoms. Objective To evaluate whether glial markers are associated with neuropsychiatric symptoms in individuals across the Alzheimer disease continuum. Design, Setting, and Participants This cross-sectional study was conducted from January to June 2023, leveraging data from the Translational Biomarkers in Aging and Dementia cohort at McGill University, Canada. Recruitment was based on referrals of individuals from the community or from outpatient clinics. Exclusion criteria included active substance abuse, major surgery, recent head trauma, safety contraindications for positron emission tomography (PET) or magnetic resonance imaging, being currently enrolled in other studies, and having inadequately treated systemic conditions. Main Outcomes and Measures All individuals underwent assessment for neuropsychiatric symptoms (Neuropsychiatry Inventory Questionnaire [NPI-Q]), and imaging for microglial activation ([11C]PBR28 PET), amyloid-β ([18F]AZD4694 PET), and tau tangles ([18F]MK6240 PET). Results Of the 109 participants, 72 (66%) were women and 37 (34%) were men; the median age was 71.8 years (range, 38.0-86.5 years). Overall, 70 had no cognitive impairment and 39 had cognitive impairment (25 mild; 14 Alzheimer disease dementia). Amyloid-β PET positivity was present in 21 cognitively unimpaired individuals (30%) and in 31 cognitively impaired individuals (79%). The NPI-Q severity score was associated with microglial activation in the frontal, temporal, and parietal cortices (β = 7.37; 95% CI, 1.34-13.41; P = .01). A leave-one-out approach revealed that irritability was the NPI-Q domain most closely associated with the presence of brain microglial activation (β = 6.86; 95% CI, 1.77-11.95; P = .008). Furthermore, we found that microglia-associated irritability was associated with study partner burden measured by NPI-Q distress score (β = 5.72; 95% CI, 0.33-11.10; P = .03). Conclusions and Relevance In this cross-sectional study of 109 individuals across the AD continuum, microglial activation was associated with and a potential biomarker of neuropsychiatric symptoms in Alzheimer disease. Moreover, our findings suggest that the combination of amyloid-β- and microglia-targeted therapies could have an impact on relieving these symptoms.
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Affiliation(s)
- Cristiano Schaffer Aguzzoli
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Brain Institute of Rio Grande do Sul, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, RS, Brazil
- Global Brain Health Institute, University of California, San Francisco
| | - Pâmela C. L. Ferreira
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Guilherme Povala
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - João Pedro Ferrari-Souza
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Bruna Bellaver
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Carolina Soares Katz
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Hussein Zalzale
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Firoza Z. Lussier
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Francieli Rohden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Sarah Abbas
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Douglas T. Leffa
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Marina Scop Medeiros
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Andréa L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Arthur Cassa Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Vanessa Pallen
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Ann Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Dana L. Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - William E. Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Victor L. Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jean Paul Soucy
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Eduardo R. Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Brain Institute of Rio Grande do Sul, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Lucas P. Schilling
- Brain Institute of Rio Grande do Sul, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, RS, Brazil
- Department of Neurology, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Thomas K. Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, 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, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Victor Valcour
- Global Brain Health Institute, University of California, San Francisco
- Department of Neurology, University of California, San Francisco
| | - Bruce L. Miller
- Global Brain Health Institute, University of California, San Francisco
- Department of Neurology, University of California, San Francisco
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux de l’Ouest-de-l’Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Tharick A. Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
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17
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Pan D, Xu Y, Wang X, Wang L, Yan J, Shi D, Yang M, Chen M. Evaluation the in vivo behaviors of PM 2.5 in rats using noninvasive PET imaging with mimic particles. CHEMOSPHERE 2023; 339:139663. [PMID: 37506893 DOI: 10.1016/j.chemosphere.2023.139663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/20/2023] [Accepted: 07/25/2023] [Indexed: 07/30/2023]
Abstract
Inhaled PM2.5 particles is harmful to human health. However, real-time tracking of PM2.5 particles and dynamic evaluation of the pharmacokinetic behaviors in vivo are still challenging. Here, PET imaging is utilized to noninvasively monitor the in vivo behavior of PM2.5 particles in rats. To mimic aerosol PM2.5 particles suspended in ambient air, 89Zr-labeled melanin nanoparticles (89Zr-MNP) are nebulized into microscopic liquid particles with a mean size of 2.5 μm. Then, the 89Zr-labeled PM2.5 mimic particles (89Zr-PM2.5) are administrated into rats via inhalation. PET imaging showed that 89Zr-PM2.5 mainly accumulated in the lungs for up to 384 h after administration. Besides, we also observe that a small amount of 89Zr-PM2.5 can penetrate the brain through the inhalation. Further PET imaging showed that enhanced uptakes of 18F-FDG and 18F-DPA-714 were found in the brain of rats upon PM2.5 mimic particle exposure, which revealed that pulmonary exposure to PM2.5 could cause potential damages to the brain. Note that abnormal glucose metabolism was reversed, but the neuroinflammation was permanent and could not be alleviated after ceasing PM2.5 exposure. Our results demonstrate that PET is a sensitive and feasible tool for evaluating the in vivo behaviors of PM2.5.
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Affiliation(s)
- Donghui Pan
- Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China
| | - Yuping Xu
- Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China
| | - Xinyu Wang
- Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China
| | - Lizhen Wang
- Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China
| | - Junjie Yan
- Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China
| | - Dongjian Shi
- Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, 214122, China
| | - Min Yang
- Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, 214122, China; Key Laboratory of Nuclear Medicine, National Health Commission, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, 214063, China.
| | - Mingqing Chen
- Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi, 214122, China.
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18
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Gouilly D, Rafiq M, Nogueira L, Salabert AS, Payoux P, Péran P, Pariente J. Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology. Rev Neurol (Paris) 2023; 179:812-830. [PMID: 36906457 DOI: 10.1016/j.neurol.2022.12.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 10/02/2022] [Accepted: 12/02/2022] [Indexed: 03/13/2023]
Abstract
Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.
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Affiliation(s)
- D Gouilly
- Toulouse Neuroimaging Center, Toulouse, France.
| | - M Rafiq
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France
| | - L Nogueira
- Department of Cell Biology and Cytology, CHU Toulouse Purpan, France
| | - A-S Salabert
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France
| | - P Payoux
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
| | - P Péran
- Toulouse Neuroimaging Center, Toulouse, France
| | - J Pariente
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
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19
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Cai W, Li L, Sang S, Pan X, Zhong C. Physiological Roles of β-amyloid in Regulating Synaptic Function: Implications for AD Pathophysiology. Neurosci Bull 2023; 39:1289-1308. [PMID: 36443453 PMCID: PMC10387033 DOI: 10.1007/s12264-022-00985-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/02/2022] [Indexed: 11/29/2022] Open
Abstract
The physiological functions of endogenous amyloid-β (Aβ), which plays important role in the pathology of Alzheimer's disease (AD), have not been paid enough attention. Here, we review the multiple physiological effects of Aβ, particularly in regulating synaptic transmission, and the possible mechanisms, in order to decipher the real characters of Aβ under both physiological and pathological conditions. Some worthy studies have shown that the deprivation of endogenous Aβ gives rise to synaptic dysfunction and cognitive deficiency, while the moderate elevation of this peptide enhances long term potentiation and leads to neuronal hyperexcitability. In this review, we provide a new view for understanding the role of Aβ in AD pathophysiology from the perspective of physiological meaning.
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Affiliation(s)
- Wenwen Cai
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Linxi Li
- Basic Medical College, Nanchang University, Nanchang, 330031, China
| | - Shaoming Sang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xiaoli Pan
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Chunjiu Zhong
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- State Key Laboratory of Medical Neurobiology, Institutes of Brain Science & Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, 200032, China.
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20
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Martinez Villar G, Daneault V, Martineau-Dussault MÈ, Baril AA, Gagnon K, Lafond C, Gilbert D, Thompson C, Marchi NA, Lina JM, Montplaisir J, Carrier J, Gosselin N, André C. Altered resting-state functional connectivity patterns in late middle-aged and older adults with obstructive sleep apnea. Front Neurol 2023; 14:1215882. [PMID: 37470008 PMCID: PMC10353887 DOI: 10.3389/fneur.2023.1215882] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 06/05/2023] [Indexed: 07/21/2023] Open
Abstract
Introduction Obstructive sleep apnea (OSA) is increasingly recognized as a risk factor for cognitive decline, and has been associated with structural brain alterations in regions relevant to memory processes and Alzheimer's disease. However, it is unclear whether OSA is associated with disrupted functional connectivity (FC) patterns between these regions in late middle-aged and older populations. Thus, we characterized the associations between OSA severity and resting-state FC between the default mode network (DMN) and medial temporal lobe (MTL) regions. Second, we explored whether significant FC changes differed depending on cognitive status and were associated with cognitive performance. Methods Ninety-four participants [24 women, 65.7 ± 6.9 years old, 41% with Mild Cognitive Impairment (MCI)] underwent a polysomnography, a comprehensive neuropsychological assessment and a resting-state functional magnetic resonance imaging (MRI). General linear models were conducted between OSA severity markers (i.e., the apnea-hypopnea, oxygen desaturation and microarousal indices) and FC values between DMN and MTL regions using CONN toolbox. Partial correlations were then performed between OSA-related FC patterns and (i) OSA severity markers in subgroups stratified by cognitive status (i.e., cognitively unimpaired versus MCI) and (ii) cognitive scores in the whole sample. All analyzes were controlled for age, sex and education, and considered significant at a p < 0.05 threshold corrected for false discovery rate. Results In the whole sample, a higher apnea-hypopnea index was significantly associated with lower FC between (i) the medial prefrontal cortex and bilateral hippocampi, and (ii) the left hippocampus and both the posterior cingulate cortex and precuneus. FC patterns were not associated with the oxygen desaturation index, or micro-arousal index. When stratifying the sample according to cognitive status, all associations remained significant in cognitively unimpaired individuals but not in the MCI group. No significant associations were observed between cognition and OSA severity or OSA-related FC patterns. Discussion OSA severity was associated with patterns of lower FC in regions relevant to memory processes and Alzheimer's disease. Since no associations were found with cognitive performance, these FC changes could precede detectable cognitive deficits. Whether these FC patterns predict future cognitive decline over the long-term needs to be investigated.
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Affiliation(s)
- Guillermo Martinez Villar
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Véronique Daneault
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
| | - Marie-Ève Martineau-Dussault
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Andrée-Ann Baril
- Douglas Mental Health Institute, McGill University, Montréal, QC, Canada
| | - Katia Gagnon
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Laboratory and Sleep Clinic, Hôpital en Santé Mentale Rivière-des-Prairies, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
| | - Chantal Lafond
- Department of Pulmonology, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Medicine, Université de Montréal, Montreal, QC, Canada
| | - Danielle Gilbert
- Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, QC, Canada
- Department of Radiology, Hopital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l'Ile-de, Montréal, QC, Canada
| | - Cynthia Thompson
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
| | - Nicola Andrea Marchi
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
- Center for Investigation and Research in Sleep, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Marc Lina
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Département de Génie Electrique, École de Technologie Supérieure, Montréal, QC, Canada
| | - Jacques Montplaisir
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychiatry, Université de Montréal, Montréal, QC, Canada
| | - Julie Carrier
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Claire André
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montréal, QC, Canada
- Department of Psychology, Université de Montréal, Montréal, QC, Canada
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21
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Meng Y, Goubran M, Rabin JS, McSweeney M, Ottoy J, Pople CB, Huang Y, Storace A, Ozzoude M, Bethune A, Lam B, Swardfager W, Heyn C, Abrahao A, Davidson B, Hamani C, Aubert I, Zetterberg H, Ashton NJ, Karikari TK, Blennow K, Black SE, Hynynen K, Lipsman N. Blood-brain barrier opening of the default mode network in Alzheimer's disease with magnetic resonance-guided focused ultrasound. Brain 2023; 146:865-872. [PMID: 36694943 PMCID: PMC10226733 DOI: 10.1093/brain/awac459] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/13/2022] [Accepted: 11/06/2022] [Indexed: 01/26/2023] Open
Abstract
The blood-brain barrier (BBB) protects the brain but is also an important obstacle for the effective delivery of therapeutics in Alzheimer's disease and other neurodegenerative disorders. Transcranial magnetic resonance-guided focused ultrasound (MRgFUS) has been shown to reversibly disrupt the BBB. However, treatment of diffuse regions across the brain along with the effect on Alzheimer's disease relevant pathology need to be better characterized. This study is an open-labelled single-arm trial (NCT04118764) to investigate the feasibility of modulating BBB permeability in the default mode network and the impact on cognition, amyloid and tau pathology as well as BBB integrity. Nine participants [mean age 70.2 ± 7.2 years, mean Mini-Mental State Examination (MMSE) 21.9] underwent three biweekly procedures with follow-up visits up to 6 months. The BBB permeability of the bilateral hippocampi, anterior cingulate cortex and precuneus was transiently increased without grade 3 or higher adverse events. Participants did not experience worsening trajectory of cognitive decline (ADAS-cog11, MMSE). Whole brain vertex-based analysis of the 18F-florbetaben PET imaging demonstrated clusters of modest SUVR reduction in the right parahippocampal and inferior temporal lobe. However, CSF and blood biomarkers did not demonstrate any amelioration of Alzheimer's disease pathology (P-tau181, amyloid-β42/40 ratio), nor did it show persistent BBB dysfunction (plasma PDGFRbeta and CSF-to-plasma albumin ratio). This study provides neuroimaging and fluid biomarker data to characterize the safety profile of MRgFUS BBB modulation in neurodegeneration as a potential strategy for enhanced therapeutic delivery.
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Affiliation(s)
- Ying Meng
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Maged Goubran
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Jennifer S Rabin
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON M5G 1V7, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Melissa McSweeney
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Julie Ottoy
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Christopher B Pople
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Yuexi Huang
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Alexandra Storace
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Miracle Ozzoude
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Allison Bethune
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Benjamin Lam
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Walter Swardfager
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Chinthaka Heyn
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Agessandro Abrahao
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Benjamin Davidson
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Clement Hamani
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Isabelle Aubert
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at The University of Gothenburg, 405 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London W1T 7NF, UK
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at The University of Gothenburg, 405 30 Mölndal, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 405 30 Gothenburg, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London SE5 9RX, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London SE5 8AF, UK
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at The University of Gothenburg, 405 30 Mölndal, Sweden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at The University of Gothenburg, 405 30 Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
| | - Sandra E Black
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON M4N 3M5, Canada
| | - Kullervo Hynynen
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
| | - Nir Lipsman
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
- Hurvitz Brain Sciences Research Program, Harquail Centre for Neuromodulation, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON M4N 3M5, Canada
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22
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Stocks J, Heywood A, Popuri K, Beg MF, Rosen H, Wang L. Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum. J Alzheimers Dis 2023; 92:513-527. [PMID: 36776061 DOI: 10.3233/jad-220975] [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: 02/10/2023]
Abstract
BACKGROUND The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear. OBJECTIVE To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points. METHODS We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up. RESULTS In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12. CONCLUSION These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ashley Heywood
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Canada.,Memorial University of Newfoundland, Department of Computer Science, St. John's, NL, Canada
| | | | - Howie Rosen
- School of Medicine, University of California, San Francisco, CA, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA
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23
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Wang ZB, Ma YH, Sun Y, Tan L, Wang HF, Yu JT. Interleukin-3 is associated with sTREM2 and mediates the correlation between amyloid-β and tau pathology in Alzheimer's disease. J Neuroinflammation 2022; 19:316. [PMID: 36578067 PMCID: PMC9798566 DOI: 10.1186/s12974-022-02679-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/20/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Dysfunction of glial cell communication is involved in Alzheimer's disease (AD) pathogenesis, and the recent study reported that astrocytic secreted interleukin-3 (IL-3) participated in astrocyte-microglia crosstalk and restricted AD pathology in mice, but the effect of IL-3 on the pathological progression of AD in human is still unclear. METHODS A total of 311 participants with cerebrospinal fluid (CSF) IL-3, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), and AD biomarkers were included from the Alzheimer's disease Neuroimaging Initiative (ADNI). We assessed the associations of IL-3 with sTREM2 and AD biomarkers at baseline, and with cognitive change in longitudinal study. The mediation models were used to explore the potential mechanism of how IL-3 affects AD pathology. RESULTS We found that CSF IL-3 was significantly associated with CSF sTREM2 and CSF AD core biomarkers (Aβ42, p-tau, and t-tau) at baseline, and was also markedly related to cognitive decline in longitudinal analysis. Moreover, mediation analysis revealed that CSF IL-3 modulated the level of CSF sTREM2 and contributed to tau pathology (as measured by CSF p-tau/t-tau) and subsequent cognitive decline. In addition, Aβ pathology (as measured by CSF Aβ42) affected the development of tau pathology partly by modifying the levels of CSF IL-3 and CSF sTREM2. Furthermore, the effect of Aβ pathology on cognitive decline was partially mediated by the pathway from CSF IL-3 and CSF sTREM2 to tau pathology. CONCLUSIONS Our findings provide evidence to suggest that IL-3 is linked to sTREM2 and mediates the correlation between Aβ pathology to tau pathology. It indicates that IL-3 may be a major factor in the spreading from Aβ pathology to tau pathology to cognitive impairment.
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Affiliation(s)
- Zhi-Bo Wang
- grid.410645.20000 0001 0455 0905Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, China
| | - Ya-Hui Ma
- grid.410645.20000 0001 0455 0905Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, China
| | - Yan Sun
- grid.410645.20000 0001 0455 0905Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, China
| | - Lan Tan
- grid.410645.20000 0001 0455 0905Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, China
| | - Hui-Fu Wang
- grid.410645.20000 0001 0455 0905Department of Neurology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao, China ,grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jin-Tai Yu
- grid.8547.e0000 0001 0125 2443State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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24
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Liu Y, Feng H, Fu H, Wu Y, Nie B, Wang T. Altered functional connectivity and topology structures in default mode network induced by inflammatory exposure in aged rat: A resting-state functional magnetic resonance imaging study. Front Aging Neurosci 2022; 14:1013478. [DOI: 10.3389/fnagi.2022.1013478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/10/2022] [Indexed: 11/19/2022] Open
Abstract
Inflammatory stress in anesthesia management and surgical process has been reported to induce long-term cognitive dysfunction in vulnerable aged brain, while few studies focused on the network mechanism. The default mode network (DMN) plays a significant role in spontaneous cognitive function. Changes in topology structure and functional connectivity (FC) of DMN in vulnerable aged brain following inflammatory stress-induced long-term cognitive dysfunction are rarely studied. Eighty-eight aged male rats received intraperitoneal injection of lipopolysaccharide (LPS) as treatment or equal amount of normal saline (NS) as control. Morris Water Maze (MWM) was performed to assess short- (<7 days) and long-term (>30 days) learning and spatial working memory. Enzyme-linked immunosorbent assay (ELISA) was used to measure systemic and hippocampus inflammatory cytokines. Real-time polymerase chain reaction (RT-PCR) was used to measure the changes in gene level. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to exam brain function prior to MWM on days 3, 7, and 31 after LPS exposure. Graph theory analysis was used to analyze FC and topology structures in aged rat DMN. Aged rats treated with LPS showed short- and long-term impairment in learning and spatial working memory in MWM test. Graph theory analysis showed temporary DMN intrinsic connectivity increased on day 3 followed with subsequent DMN intrinsic connectivity significantly altered on day 7 and day 31 in LPS-exposed rats as compared with controls. Short- and long-term alterations were observed in FC, while alterations in topology structures were only observed on day 3. Rats with inflammatory stress exposure may cause short- and long-term alterations in intrinsic connectivity in aged rat’s DMN while the changes in topology structures only lasted for 3 days. Inflammatory stress has prolonged effects on FC, but not topology structures in venerable aged brain.
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Ng KP, Qian X, Ng KK, Ji F, Rosa-Neto P, Gauthier S, Kandiah N, Zhou JH. Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum. eLife 2022; 11:e77745. [PMID: 36053063 PMCID: PMC9477498 DOI: 10.7554/elife.77745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 09/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background Large-scale neuronal network breakdown underlies memory impairment in Alzheimer's disease (AD). However, the differential trajectories of the relationships between network organisation and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods Seven hundred and eight participants from the Alzheimer's Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F] fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. Results We showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode metabolic network on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. Conclusions Our findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage. Funding Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). We also acknowledge the funding support from the Duke NUS/Khoo Bridge Funding Award (KBrFA/2019-0020) and NMRC Open Fund Large Collaborative Grant (OFLCG09May0035).
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Affiliation(s)
- Kok Pin Ng
- Department of Neurology, National Neuroscience InstituteSingaporeSingapore
- Duke-NUS Medical SchoolSingaporeSingapore
- Lee Kong Chian School of Medicine, Nanyang Technological University SingaporeSingaporeSingapore
| | - Xing Qian
- Centre for Sleep and Cognition and Centre for Translational MR Research,Yong Loo Lin School of Medicine, National University of SingaporeSingaporeSingapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition and Centre for Translational MR Research,Yong Loo Lin School of Medicine, National University of SingaporeSingaporeSingapore
| | - Fang Ji
- Centre for Sleep and Cognition and Centre for Translational MR Research,Yong Loo Lin School of Medicine, National University of SingaporeSingaporeSingapore
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill UniversityMontrealCanada
- Montreal Neurological Institute, McGill UniversityMontrealCanada
| | - Serge Gauthier
- Department of Neurology & Neurosurgery, McGill UniversityMontrealCanada
| | - Nagaendran Kandiah
- Lee Kong Chian School of Medicine, Nanyang Technological University SingaporeSingaporeSingapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition and Centre for Translational MR Research,Yong Loo Lin School of Medicine, National University of SingaporeSingaporeSingapore
- Department of Electrical and Computer Engineering, National University of SingaporeSingaporeSingapore
- Integrative Sciences and Engineering Programme (ISEP), National University of SingaporeSingaporeSingapore
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Venkataraman AV, Mansur A, Rizzo G, Bishop C, Lewis Y, Kocagoncu E, Lingford-Hughes A, Huiban M, Passchier J, Rowe JB, Tsukada H, Brooks DJ, Martarello L, Comley RA, Chen L, Schwarz AJ, Hargreaves R, Gunn RN, Rabiner EA, Matthews PM. Widespread cell stress and mitochondrial dysfunction occur in patients with early Alzheimer's disease. Sci Transl Med 2022; 14:eabk1051. [PMID: 35976998 DOI: 10.1126/scitranslmed.abk1051] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Cell stress and impaired oxidative phosphorylation are central to mechanisms of synaptic loss and neurodegeneration in the cellular pathology of Alzheimer's disease (AD). In this study, we quantified the in vivo expression of the endoplasmic reticulum stress marker, sigma 1 receptor (S1R), using [11C]SA4503 positron emission tomography (PET), the mitochondrial complex I (MC1) with [18F]BCPP-EF, and the presynaptic vesicular protein SV2A with [11C]UCB-J in 12 patients with early AD and in 16 cognitively normal controls. We integrated these molecular measures with assessments of regional brain volumes and cerebral blood flow (CBF) measured with magnetic resonance imaging arterial spin labeling. Eight patients with AD were followed longitudinally to estimate the rate of change of the physiological and structural pathology markers with disease progression. The patients showed widespread increases in S1R (≤ 27%) and regional reduction in MC1 (≥ -28%) and SV2A (≥ -25%) radioligand binding, brain volume (≥ -23%), and CBF (≥ -26%). [18F]BCPP-EF PET MC1 binding (≥ -12%) and brain volumes (≥ -5%) showed progressive reductions over 12 to 18 months, suggesting that they both could be used as pharmacodynamic indicators in early-stage therapeutics trials. Associations of reduced MC1 and SV2A and increased S1R radioligand binding with reduced cognitive performance in AD, although exploratory, suggested a loss of metabolic functional reserve with disease. Our study thus provides in vivo evidence for widespread, clinically relevant cellular stress and bioenergetic abnormalities in early AD.
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Affiliation(s)
- Ashwin V Venkataraman
- Department of Brain Sciences, Imperial College London, London W12 0NN, UK.,UK Dementia Research Institute at Imperial College London, London W12 0NN, UK
| | | | - Gaia Rizzo
- Department of Brain Sciences, Imperial College London, London W12 0NN, UK.,Invicro LLC, London W12 0NN, UK
| | | | | | | | | | | | | | | | - Hideo Tsukada
- Hamamatsu Photonics, Hamakita, Hamamatsu, Shizuoka 4348601, Japan
| | - David J Brooks
- University of Newcastle upon Tyne, Newcastle NE2 4HH, UK.,Department of Clinical Medicine, Aarhus University, Aarhus 8200, Denmark
| | | | | | | | | | | | - Roger N Gunn
- Department of Brain Sciences, Imperial College London, London W12 0NN, UK.,Invicro LLC, London W12 0NN, UK
| | - Eugenii A Rabiner
- Invicro LLC, London W12 0NN, UK.,King's College London, London SE5 8AF, UK
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London W12 0NN, UK.,UK Dementia Research Institute at Imperial College London, London W12 0NN, UK
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27
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Myette-Côté É, Soto-Mota A, Cunnane SC. Ketones: potential to achieve brain energy rescue and sustain cognitive health during ageing. Br J Nutr 2022; 128:407-423. [PMID: 34581265 DOI: 10.1017/s0007114521003883] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Alzheimer’s disease (AD) is the most common major neurocognitive disorder of ageing. Although largely ignored until about a decade ago, accumulating evidence suggests that deteriorating brain energy metabolism plays a key role in the development and/or progression of AD-associated cognitive decline. Brain glucose hypometabolism is a well-established biomarker in AD but was mostly assumed to be a consequence of neuronal dysfunction and death. However, its presence in cognitively asymptomatic populations at higher risk of AD strongly suggests that it is actually a pre-symptomatic component in the development of AD. The question then arises as to whether progressive AD-related cognitive decline could be prevented or slowed down by correcting or bypassing this progressive ‘brain energy gap’. In this review, we provide an overview of research on brain glucose and ketone metabolism in AD and its prodromal condition – mild cognitive impairment (MCI) – to provide a clearer basis for proposing keto-therapeutics as a strategy for brain energy rescue in AD. We also discuss studies using ketogenic interventions and their impact on plasma ketone levels, brain energetics and cognitive performance in MCI and AD. Given that exercise has several overlapping metabolic effects with ketones, we propose that in combination these two approaches might be synergistic for brain health during ageing. As cause-and-effect relationships between the different hallmarks of AD are emerging, further research efforts should focus on optimising the efficacy, acceptability and accessibility of keto-therapeutics in AD and populations at risk of AD.
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Affiliation(s)
- Étienne Myette-Côté
- Montreal Clinical Research Institute, Montreal, QC, Canada
- Department of Medicine, McGill University, Montreal, QC, Canada
| | - Adrian Soto-Mota
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Stephen C Cunnane
- Research Center on Aging, CIUSSS de l'Estrie - CHUS, Sherbrooke, QC, Canada
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
- Department of Pharmacology & Physiology, Université de Sherbrooke, Sherbrooke, QC, Canada
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28
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Poulakis K, Pereira JB, Muehlboeck JS, Wahlund LO, Smedby Ö, Volpe G, Masters CL, Ames D, Niimi Y, Iwatsubo T, Ferreira D, Westman E. Multi-cohort and longitudinal Bayesian clustering study of stage and subtype in Alzheimer's disease. Nat Commun 2022; 13:4566. [PMID: 35931678 PMCID: PMC9355993 DOI: 10.1038/s41467-022-32202-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 07/18/2022] [Indexed: 11/08/2022] Open
Abstract
Understanding Alzheimer's disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity.
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Affiliation(s)
- Konstantinos Poulakis
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | - Joana B Pereira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmo, Sweden
| | - J-Sebastian Muehlboeck
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Örjan Smedby
- Department of Biomedical Engineering and Health Systems (MTH), KTH Royal Institute of Technology, Stockholm, Sweden
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Victoria, Australia
| | - David Ames
- Academic Unit for Psychiatry of Old Age, St George's Hospital, University of Melbourne, Melbourne, Victoria, Australia
- National Ageing Research Institute, Parkville, Victoria, Australia
| | - Yoshiki Niimi
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan
| | - Takeshi Iwatsubo
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Eric Westman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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29
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, DeCarli C, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Okonkwo O, Perrin RJ, Petersen RC, Rivera‐Mindt M, Saykin AJ, Shaw LM, Toga AW, Tosun D, Trojanowski JQ. Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease. Alzheimers Dement 2022; 18:824-857. [PMID: 34581485 PMCID: PMC9158456 DOI: 10.1002/alz.12422] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020. METHODS We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion. RESULTS Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity. DISCUSSION ADNI has had a profound impact in improving clinical trials for AD.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Laurel A. Beckett
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Charles DeCarli
- Department of Neurology and Center for NeuroscienceUniversity of California DavisDavisCaliforniaUSA
| | - Robert C. Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Broad Institute, Ariadne Labsand Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and Informatics, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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30
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Sengupta U, Kayed R. Amyloid β, Tau, and α-Synuclein aggregates in the pathogenesis, prognosis, and therapeutics for neurodegenerative diseases. Prog Neurobiol 2022; 214:102270. [DOI: 10.1016/j.pneurobio.2022.102270] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 01/28/2022] [Accepted: 04/13/2022] [Indexed: 12/11/2022]
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31
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Zhang SS, Zhu L, Peng Y, Zhang L, Chao FL, Jiang L, Xiao Q, Liang X, Tang J, Yang H, He Q, Guo YJ, Zhou CN, Tang Y. Long-term running exercise improves cognitive function and promotes microglial glucose metabolism and morphological plasticity in the hippocampus of APP/PS1 mice. J Neuroinflammation 2022; 19:34. [PMID: 35123512 PMCID: PMC8817568 DOI: 10.1186/s12974-022-02401-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 01/24/2022] [Indexed: 02/06/2023] Open
Abstract
Background The role of physical exercise in the prevention of Alzheimer’s disease (AD) has been widely studied. Microglia play an important role in AD. Triggering receptor expressed in myeloid cells 2 (TREM2) is expressed on microglia and is known to mediate microglial metabolic activity and brain glucose metabolism. However, the relationship between brain glucose metabolism and microglial metabolic activity during running exercise in APP/PS1 mice remains unclear. Methods Ten-month-old male APP/PS1 mice and wild-type mice were randomly divided into sedentary groups or running groups (AD_Sed, WT_Sed, AD_Run and WT_Run, n = 20/group). Running mice had free access to a running wheel for 3 months. Behavioral tests, [18]F-FDG-PET and hippocampal RNA-Seq were performed. The expression levels of microglial glucose transporter (GLUT5), TREM2, soluble TREM2 (sTREM2), TYRO protein tyrosine kinase binding protein (TYROBP), secreted phosphoprotein 1 (SPP1), and phosphorylated spleen tyrosine kinase (p-SYK) were estimated by western blot or ELISA. Immunohistochemistry, stereological methods and immunofluorescence were used to investigate the morphology, proliferation and activity of microglia. Results Long-term voluntary running significantly improved cognitive function in APP/PS1 mice. Although there were few differentially expressed genes (DEGs), gene set enrichment analysis (GSEA) showed enriched glycometabolic pathways in APP/PS1 running mice. Running exercise increased FDG uptake in the hippocampus of APP/PS1 mice, as well as the protein expression of GLUT5, TREM2, SPP1 and p-SYK. The level of sTREM2 decreased in the plasma of APP/PS1 running mice. The number of microglia, the length and endpoints of microglial processes, and the ratio of GLUT5+/IBA1+ microglia were increased in the dentate gyrus (DG) of APP/PS1 running mice. Running exercise did not alter the number of 5-bromo-2′-deoxyuridine (BrdU)+/IBA1+ microglia but reduced the immunoactivity of CD68 in the hippocampus of APP/PS1 mice. Conclusions Running exercise inhibited TREM2 shedding and maintained TREM2 protein levels, which were accompanied by the promotion of brain glucose metabolism, microglial glucose metabolism and morphological plasticity in the hippocampus of AD mice. Microglia might be a structural target responsible for the benefits of running exercise in AD. Promoting microglial glucose metabolism and morphological plasticity modulated by TREM2 might be a novel strategy for AD treatment. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02401-5.
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32
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Okuno T, Woodward A. Vector Auto-Regressive Deep Neural Network: A Data-Driven Deep Learning-Based Directed Functional Connectivity Estimation Toolbox. Front Neurosci 2021; 15:764796. [PMID: 34899167 PMCID: PMC8651499 DOI: 10.3389/fnins.2021.764796] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 10/19/2021] [Indexed: 11/13/2022] Open
Abstract
An important goal in neuroscience is to elucidate the causal relationships between the brain's different regions. This can help reveal the brain's functional circuitry and diagnose lesions. Currently there are a lack of approaches to functional connectome estimation that leverage the state-of-the-art in deep learning architectures and training methodologies. Therefore, we propose a new framework based on a vector auto-regressive deep neural network (VARDNN) architecture. Our approach consists of a set of nodes, each with a deep neural network structure. These nodes can be mapped to any spatial sub-division based on the data to be analyzed, such as anatomical brain regions from which representative neural signals can be obtained. VARDNN learns to reproduce experimental time series data using modern deep learning training techniques. Based on this, we developed two novel directed functional connectivity (dFC) measures, namely VARDNN-DI and VARDNN-GC. We evaluated our measures against a number of existing functional connectome estimation measures, such as partial correlation and multivariate Granger causality combined with large dimensionality counter-measure techniques. Our measures outperformed them across various types of ground truth data, especially as the number of nodes increased. We applied VARDNN to fMRI data to compare the dFC between 41 healthy control vs. 32 Alzheimer's disease subjects. Our VARDNN-DI measure detected lesioned regions consistent with previous studies and separated the two groups well in a subject-wise evaluation framework. Summarily, the VARDNN framework has powerful capabilities for whole brain dFC estimation. We have implemented VARDNN as an open-source toolbox that can be freely downloaded for researchers who wish to carry out functional connectome analysis on their own data.
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Affiliation(s)
- Takuto Okuno
- Connectome Analysis Unit, RIKEN Center for Brain Science, Wako, Japan
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33
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Venkataraman AV, Bai W, Whittington A, Myers JF, Rabiner EA, Lingford-Hughes A, Matthews PM. Boosting the diagnostic power of amyloid-β PET using a data-driven spatially informed classifier for decision support. Alzheimers Res Ther 2021; 13:185. [PMID: 34758867 PMCID: PMC8582159 DOI: 10.1186/s13195-021-00910-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 10/02/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer's disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD. METHODS Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology. RESULTS This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr. CONCLUSIONS The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings.
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Affiliation(s)
- Ashwin V Venkataraman
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK.
- UK Dementia Research Institute at Imperial College London, London, UK.
| | - Wenjia Bai
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
- Data Science Institute, Imperial College London, London, UK
| | | | - James F Myers
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
| | | | - Anne Lingford-Hughes
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
- UK Dementia Research Institute at Imperial College London, London, UK
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34
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Andersen JV, Skotte NH, Christensen SK, Polli FS, Shabani M, Markussen KH, Haukedal H, Westi EW, Diaz-delCastillo M, Sun RC, Kohlmeier KA, Schousboe A, Gentry MS, Tanila H, Freude KK, Aldana BI, Mann M, Waagepetersen HS. Hippocampal disruptions of synaptic and astrocyte metabolism are primary events of early amyloid pathology in the 5xFAD mouse model of Alzheimer's disease. Cell Death Dis 2021; 12:954. [PMID: 34657143 PMCID: PMC8520528 DOI: 10.1038/s41419-021-04237-y] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/14/2021] [Accepted: 09/24/2021] [Indexed: 12/23/2022]
Abstract
Alzheimer’s disease (AD) is an unremitting neurodegenerative disorder characterized by cerebral amyloid-β (Aβ) accumulation and gradual decline in cognitive function. Changes in brain energy metabolism arise in the preclinical phase of AD, suggesting an important metabolic component of early AD pathology. Neurons and astrocytes function in close metabolic collaboration, which is essential for the recycling of neurotransmitters in the synapse. However, this crucial metabolic interplay during the early stages of AD development has not been sufficiently investigated. Here, we provide an integrative analysis of cellular metabolism during the early stages of Aβ accumulation in the cerebral cortex and hippocampus of the 5xFAD mouse model of AD. Our electrophysiological examination revealed an increase in spontaneous excitatory signaling in the 5xFAD hippocampus. This hyperactive neuronal phenotype coincided with decreased hippocampal tricarboxylic acid (TCA) cycle metabolism mapped by stable 13C isotope tracing. Particularly, reduced astrocyte TCA cycle activity and decreased glutamine synthesis led to hampered neuronal GABA synthesis in the 5xFAD hippocampus. In contrast, the cerebral cortex of 5xFAD mice displayed an elevated capacity for oxidative glucose metabolism, which may suggest a metabolic compensation in this brain region. We found limited changes when we explored the brain proteome and metabolome of the 5xFAD mice, supporting that the functional metabolic disturbances between neurons and astrocytes are early primary events in AD pathology. In addition, synaptic mitochondrial and glycolytic function was selectively impaired in the 5xFAD hippocampus, whereas non-synaptic mitochondrial function was maintained. These findings were supported by ultrastructural analyses demonstrating disruptions in mitochondrial morphology, particularly in the 5xFAD hippocampus. Collectively, our study reveals complex regional and cell-specific metabolic adaptations in the early stages of amyloid pathology, which may be fundamental for the progressing synaptic dysfunctions in AD.
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Affiliation(s)
- Jens V Andersen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Niels H Skotte
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sofie K Christensen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Filip S Polli
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, CA, USA
| | - Mohammad Shabani
- Neuroscience Research Center, Neuropharmacology Institute, Kerman University of Medical Sciences, Kerman, Iran
| | - Kia H Markussen
- Department of Molecular and Cellular Biochemistry, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Henriette Haukedal
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Emil W Westi
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marta Diaz-delCastillo
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ramon C Sun
- Markey Cancer Center, Lexington, KY, USA.,Department of Neuroscience, College of Medicine, University of Kentucky, Lexington, KY, USA
| | - Kristi A Kohlmeier
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Arne Schousboe
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matthew S Gentry
- Department of Molecular and Cellular Biochemistry, College of Medicine, University of Kentucky, Lexington, KY, USA.,Markey Cancer Center, Lexington, KY, USA
| | - Heikki Tanila
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Kristine K Freude
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Blanca I Aldana
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helle S Waagepetersen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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35
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Zhang M, Sun W, Guan Z, Hu J, Li B, Ye G, Meng H, Huang X, Lin X, Wang J, Liu J, Li B, Zhang Y, Li Y. Simultaneous PET/fMRI Detects Distinctive Alterations in Functional Connectivity and Glucose Metabolism of Precuneus Subregions in Alzheimer's Disease. Front Aging Neurosci 2021; 13:737002. [PMID: 34630070 PMCID: PMC8498203 DOI: 10.3389/fnagi.2021.737002] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 08/30/2021] [Indexed: 11/13/2022] Open
Abstract
As a central hub in the interconnected brain network, the precuneus has been reported showing disrupted functional connectivity and hypometabolism in Alzheimer's disease (AD). However, as a highly heterogeneous cortical structure, little is known whether individual subregion of the precuneus is uniformly or differentially involved in the progression of AD. To this end, using a hybrid PET/fMRI technique, we compared resting-state functional connectivity strength (FCS) and glucose metabolism in dorsal anterior (DA_pcu), dorsal posterior (DP_pcu) and ventral (V_pcu) subregions of the precuneus among 20 AD patients, 23 mild cognitive impairment (MCI) patients, and 27 matched cognitively normal (CN) subjects. The sub-parcellation of precuneus was performed using a K-means clustering algorithm based on its intra-regional functional connectivity. For the whole precuneus, decreased FCS (p = 0.047) and glucose hypometabolism (p = 0.006) were observed in AD patients compared to CN subjects. For the subregions of the precuneus, decreased FCS was found in DP_pcu of AD patients compared to MCI patients (p = 0.011) and in V_pcu for both MCI (p = 0.006) and AD (p = 0.008) patients compared to CN subjects. Reduced glucose metabolism was found in DP_pcu of AD patients compared to CN subjects (p = 0.038) and in V_pcu of AD patients compared to both MCI patients (p = 0.045) and CN subjects (p < 0.001). For both FCS and glucose metabolism, DA_pcu remained relatively unaffected by AD. Moreover, only in V_pcu, disruptions in FCS (r = 0.498, p = 0.042) and hypometabolism (r = 0.566, p = 0.018) were significantly correlated with the cognitive decline of AD patients. Our results demonstrated a distinctively disrupted functional and metabolic pattern from ventral to dorsal precuneus affected by AD, with V_pcu and DA_pcu being the most vulnerable and conservative subregion, respectively. Findings of this study extend our knowledge on the differential roles of precuneus subregions in AD.
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Affiliation(s)
- Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wanqing Sun
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ziyun Guan
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jialin Hu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Binyin Li
- Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guanyu Ye
- Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongping Meng
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyun Huang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaozhu Lin
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jin Wang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Ruijin Center, Shanghai, China
| | - Yaoyu Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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36
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Ingala S, Tomassen J, Collij LE, Prent N, van 't Ent D, Ten Kate M, Konijnenberg E, Yaqub M, Scheltens P, de Geus EJC, Teunissen CE, Tijms B, Wink AM, Barkhof F, van Berckel BNM, Visser PJ, den Braber A. Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals. Brain Commun 2021; 3:fcab201. [PMID: 34617016 PMCID: PMC8490784 DOI: 10.1093/braincomms/fcab201] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 04/06/2021] [Accepted: 05/03/2021] [Indexed: 12/03/2022] Open
Abstract
Cortical accumulation of amyloid beta is one of the first events of Alzheimer’s disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer’s disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer’s disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline.
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Affiliation(s)
- Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Naomi Prent
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Faculty of Behavioral and Movement Sciences, Section Clinical Neuropsychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.,Vesalius, Centre for Neuropsychiatry, GGZ Altrecht, 3447 GM Woerden, The Netherlands
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Mara Ten Kate
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Elles Konijnenberg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Betty Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Institute of Neurology and Healthcare Engineering, University College London, WC1E 6BT London, UK
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
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37
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Therriault J, Pascoal TA, Sefranek M, Mathotaarachchi S, Benedet AL, Chamoun M, Lussier FZ, Tissot C, Bellaver B, Lukasewicz PS, Zimmer ER, Saha-Chaudhuri P, Gauthier S, Rosa-Neto P. Amyloid-dependent and amyloid-independent effects of Tau in individuals without dementia. Ann Clin Transl Neurol 2021; 8:2083-2092. [PMID: 34617688 PMCID: PMC8528464 DOI: 10.1002/acn3.51457] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 08/11/2021] [Accepted: 09/01/2021] [Indexed: 02/01/2023] Open
Abstract
Objective To investigate the relationship between the topography of amyloid‐β plaques, tau neurofibrillary tangles, and the overlap between the two, with cognitive dysfunction in individuals without dementia. Methods We evaluated 154 individuals who were assessed with amyloid‐β PET with [18F]AZD4694, tau‐PET with [18F]MK6240, structural MRI, and neuropsychological testing. We also evaluated an independent cohort of 240 individuals who were assessed with amyloid‐β PET with [18F]Florbetapir, tau‐PET with [18F]Flortaucipir, structural MRI, and neuropsychological testing. Using the VoxelStats toolbox, we conducted voxel‐wise linear regressions between amyloid‐PET, tau‐PET, and their interaction with cognitive function, correcting for age, sex, and years of education. Results In both cohorts, we observed that tau‐PET standardized uptake value ratio in medial temporal lobes was associated with clinical dementia rating Sum of Boxes (CDR‐SoB) scores independently of local amyloid‐PET uptake (FWE corrected at p < 0.001). We also observed in both cohorts that in regions of the neocortex, associations between neocortical tau‐PET and clinical function were dependent on local amyloid‐PET (FWE corrected at p < 0.001). Interpretation In medial temporal brain regions, characterized by the accumulation of tau pathology in the absence of amyloid‐β, tau had direct associations with cognitive dysfunction. In brain regions characterized by the accumulation of both amyloid‐β and tau pathologies such as the posterior cingulate and medial frontal cortices, tau’s relationship with cognitive dysfunction was dependent on local amyloid‐β concentrations. Our results provide evidence that amyloid‐β in Alzheimer’s disease influences cognition by potentiating the deleterious effects of tau pathology.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada
| | - Marcus Sefranek
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada
| | - Bruna Bellaver
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Pamela S Lukasewicz
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Department of Pharmacology, Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Serge Gauthier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Montreal, Canada.,Montreal Neurological Institute, Montreal, Canada.,Douglas Hospital Research Centre, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, McGill University, Montreal, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
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38
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Pascoal TA, Benedet AL, Tudorascu DL, Therriault J, Mathotaarachchi S, Savard M, Lussier FZ, Tissot C, Chamoun M, Kang MS, Stevenson J, Massarweh G, Guiot MC, Soucy JP, Gauthier S, Rosa-Neto P. Longitudinal 18F-MK-6240 tau tangles accumulation follows Braak stages. Brain 2021; 144:3517-3528. [PMID: 34515754 DOI: 10.1093/brain/awab248] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 05/26/2021] [Accepted: 06/17/2021] [Indexed: 11/13/2022] Open
Abstract
Tracking longitudinal tau tangles accumulation across the Alzheimer's disease continuum is crucial to better understand the natural history of tau pathology and for clinical trials. Although the available first-generation tau PET tracers detect tau accumulation in symptomatic individuals, their nanomolar affinity offers limited sensitivity to detect early tau accumulation in asymptomatic subjects. Here, we hypothesized the novel sub-nanomolar affinity tau tangles tracer [18F]MK-6240 can detect longitudinal tau accumulation in asymptomatic and symptomatic subjects. We studied 125 living individuals (65 cognitively unimpaired elderly amyloid-β negative, 22 cognitively unimpaired elderly amyloid-β positive, 21 mild cognitive impairment amyloid-β positive, 17 Alzheimer's disease dementia amyloid-β positive) with baseline amyloid-β [18F]AZD4694 PET and baseline and follow-up tau [18F]MK-6240 PET. [18F]MK-6240 standardized uptake value ratio (SUVR) was calculated at 90-110 min after tracer injection and used the cerebellar crus I as the reference region. In addition, we assessed in vivo [18F]MK-6240 SUVR and postmortem phosphorylated tau pathology in two Alzheimer's disease dementia participants who deceased after the PET scans. We found that cognitively unimpaired amyloid-β negative individuals had significant longitudinal tau accumulation confined to PET Braak-like stage I (3.9%) and II (2.8%) areas. Cognitively unimpaired amyloid-β positive showed greater tau accumulation in Braak-like stage I (8.9%), compared to later Braak stages. Mild cognitive impairment and Alzheimer's dementia amyloid-β positive patients showed tau accumulation in Braak III-VI, but not in Braak I-II regions. Cognitively impaired amyloid-β positive individuals that were Braak II-IV at baseline showed 4.6-7.5% annual increase in tau accumulation in Braak III-IV regions, whereas cognitively impaired amyloid-β positive Braak V-VI at baseline had 8.3-10.7% annual increase in Braak V-VI regions. Neuropathological assessments confirmed the PET-based Braak stages V-VI observed in the two brain donors. Our results suggest that [18F]MK-6240 SUVR is able to detect longitudinal tau accumulation in asymptomatic and symptomatic Alzheimer's disease. The highest magnitude of [18F]MK-6240 SUVR accumulation moved from medial temporal to sensorimotor cortex across the disease clinical spectrum. Trials using [18F]MK-6240 SUVR in cognitively unimpaired would be required to use regions-of-interest corresponding to early Braak stages, whereas trials in cognitively impaired would benefit from using regions-of-interest in late Braak stages. Anti-tau trials should take into consideration individuals' baseline PET Braak-like stage to minimize the variability introduced by the hierarchical accumulation of tau tangles in the human brain. Finally, our postmortem findings supported [18F]MK-6240 SUVR as a biomarker to stage tau pathology in Alzheimer's disease patients.
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Affiliation(s)
- Tharick A Pascoal
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Melissa Savard
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Min Su Kang
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Gassan Massarweh
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, The McGill University Research Centre for Studies in Aging, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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Malkov A, Popova I, Ivanov A, Jang SS, Yoon SY, Osypov A, Huang Y, Zilberter Y, Zilberter M. Aβ initiates brain hypometabolism, network dysfunction and behavioral abnormalities via NOX2-induced oxidative stress in mice. Commun Biol 2021; 4:1054. [PMID: 34504272 PMCID: PMC8429759 DOI: 10.1038/s42003-021-02551-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 08/12/2021] [Indexed: 12/30/2022] Open
Abstract
A predominant trigger and driver of sporadic Alzheimer’s disease (AD) is the synergy of brain oxidative stress and glucose hypometabolism starting at early preclinical stages. Oxidative stress damages macromolecules, while glucose hypometabolism impairs cellular energy supply and antioxidant defense. However, the exact cause of AD-associated glucose hypometabolism and its network consequences have remained unknown. Here we report NADPH oxidase 2 (NOX2) activation as the main initiating mechanism behind Aβ1-42-related glucose hypometabolism and network dysfunction. We utilize a combination of electrophysiology with real-time recordings of metabolic transients both ex- and in-vivo to show that Aβ1-42 induces oxidative stress and acutely reduces cellular glucose consumption followed by long-lasting network hyperactivity and abnormalities in the animal behavioral profile. Critically, all of these pathological changes were prevented by the novel bioavailable NOX2 antagonist GSK2795039. Our data provide direct experimental evidence for causes and consequences of AD-related brain glucose hypometabolism, and suggest that targeting NOX2-mediated oxidative stress is a promising approach to both the prevention and treatment of AD. Anton Malkov, Irina Popova et al. demonstrate that beta-amyloid application induces oxidative stress and reduces glucose consumption in the mouse brain, leading to network hyperactivity and behavioral changes—pathologies similar to those observed early on in Alzheimer’s disease patients. Inhibition of NADPH oxidase 2 (NOX2) rescued these phenotypes, suggesting that NOX2 may represent an important therapeutic target for Alzheimer’s disease.
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Affiliation(s)
- Anton Malkov
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Russia
| | - Irina Popova
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Russia
| | - Anton Ivanov
- Aix Marseille Université, Inserm, Marseille, France
| | - Sung-Soo Jang
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
| | - Seo Yeon Yoon
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA
| | - Alexander Osypov
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Russia.,Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia
| | - Yadong Huang
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA.,Department of Neurology, University of California, San Francisco, CA, USA
| | | | - Misha Zilberter
- Gladstone Institute of Neurological Disease, San Francisco, CA, USA.
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40
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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41
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Pascoal TA, Benedet AL, Ashton NJ, Kang MS, Therriault J, Chamoun M, Savard M, Lussier FZ, Tissot C, Karikari TK, Ottoy J, Mathotaarachchi S, Stevenson J, Massarweh G, Schöll M, de Leon MJ, Soucy JP, Edison P, Blennow K, Zetterberg H, Gauthier S, Rosa-Neto P. Microglial activation and tau propagate jointly across Braak stages. Nat Med 2021; 27:1592-1599. [PMID: 34446931 DOI: 10.1038/s41591-021-01456-w] [Citation(s) in RCA: 271] [Impact Index Per Article: 67.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 06/28/2021] [Indexed: 11/09/2022]
Abstract
Compelling experimental evidence suggests that microglial activation is involved in the spread of tau tangles over the neocortex in Alzheimer's disease (AD). We tested the hypothesis that the spatial propagation of microglial activation and tau accumulation colocalize in a Braak-like pattern in the living human brain. We studied 130 individuals across the aging and AD clinical spectrum with positron emission tomography brain imaging for microglial activation ([11C]PBR28), amyloid-β (Aβ) ([18F]AZD4694) and tau ([18F]MK-6240) pathologies. We further assessed microglial triggering receptor expressed on myeloid cells 2 (TREM2) cerebrospinal fluid (CSF) concentrations and brain gene expression patterns. We found that [11C]PBR28 correlated with CSF soluble TREM2 and showed regional distribution resembling TREM2 gene expression. Network analysis revealed that microglial activation and tau correlated hierarchically with each other following Braak-like stages. Regression analysis revealed that the longitudinal tau propagation pathways depended on the baseline microglia network rather than the tau network circuits. The co-occurrence of Aβ, tau and microglia abnormalities was the strongest predictor of cognitive impairment in our study population. Our findings support a model where an interaction between Aβ and activated microglia sets the pace for tau spread across Braak stages.
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Affiliation(s)
- Tharick A Pascoal
- Departments of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. .,Departments of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. .,Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada. .,Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley, NHS Foundation, London, UK
| | - Min Su Kang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada.,Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Melissa Savard
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Julie Ottoy
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.,LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Sulantha Mathotaarachchi
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Gassan Massarweh
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Michael Schöll
- 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, University of Gothenburg, Gothenburg, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Mony J de Leon
- Department of Radiology Weill Medical Center Brain Health Imaging Institute, Cornell University, Ithaca, NY, USA
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Paul Edison
- Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,UK Dementia Research Institute at UCL, London, UK
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal, and Departments of Neurology, Neurosurgery, Psychiatry, Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada. .,Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
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Strom A, Iaccarino L, Edwards L, Lesman-Segev OH, Soleimani-Meigooni DN, Pham J, Baker SL, Landau S, Jagust WJ, Miller BL, Rosen HJ, Gorno-Tempini ML, Rabinovici GD, La Joie R. Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease. Brain 2021; 145:713-728. [PMID: 34373896 PMCID: PMC9014741 DOI: 10.1093/brain/awab294] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 07/09/2021] [Accepted: 07/21/2021] [Indexed: 11/14/2022] Open
Abstract
Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.
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Affiliation(s)
- Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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43
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Pritschet L, Taylor CM, Santander T, Jacobs EG. Applying dense-sampling methods to reveal dynamic endocrine modulation of the nervous system. Curr Opin Behav Sci 2021; 40:72-78. [DOI: 10.1016/j.cobeha.2021.01.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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44
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Lyra E Silva NM, Gonçalves RA, Pascoal TA, Lima-Filho RAS, Resende EDPF, Vieira ELM, Teixeira AL, de Souza LC, Peny JA, Fortuna JTS, Furigo IC, Hashiguchi D, Miya-Coreixas VS, Clarke JR, Abisambra JF, Longo BM, Donato J, Fraser PE, Rosa-Neto P, Caramelli P, Ferreira ST, De Felice FG. Pro-inflammatory interleukin-6 signaling links cognitive impairments and peripheral metabolic alterations in Alzheimer's disease. Transl Psychiatry 2021; 11:251. [PMID: 33911072 PMCID: PMC8080782 DOI: 10.1038/s41398-021-01349-z] [Citation(s) in RCA: 161] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 02/25/2021] [Accepted: 03/19/2021] [Indexed: 12/22/2022] Open
Abstract
Alzheimer's disease (AD) is associated with memory impairment and altered peripheral metabolism. Mounting evidence indicates that abnormal signaling in a brain-periphery metabolic axis plays a role in AD pathophysiology. The activation of pro-inflammatory pathways in the brain, including the interleukin-6 (IL-6) pathway, comprises a potential point of convergence between memory dysfunction and metabolic alterations in AD that remains to be better explored. Using T2-weighted magnetic resonance imaging (MRI), we observed signs of probable inflammation in the hypothalamus and in the hippocampus of AD patients when compared to cognitively healthy control subjects. Pathological examination of post-mortem AD hypothalamus revealed the presence of hyperphosphorylated tau and tangle-like structures, as well as parenchymal and vascular amyloid deposits surrounded by astrocytes. T2 hyperintensities on MRI positively correlated with plasma IL-6, and both correlated inversely with cognitive performance and hypothalamic/hippocampal volumes in AD patients. Increased IL-6 and suppressor of cytokine signaling 3 (SOCS3) were observed in post-mortem AD brains. Moreover, activation of the IL-6 pathway was observed in the hypothalamus and hippocampus of AD mice. Neutralization of IL-6 and inhibition of the signal transducer and activator of transcription 3 (STAT3) signaling in the brains of AD mouse models alleviated memory impairment and peripheral glucose intolerance, and normalized plasma IL-6 levels. Collectively, these results point to IL-6 as a link between cognitive impairment and peripheral metabolic alterations in AD. Targeting pro-inflammatory IL-6 signaling may be a strategy to alleviate memory impairment and metabolic alterations in the disease.
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Affiliation(s)
- Natalia M Lyra E Silva
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Rafaella A Gonçalves
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
| | - Tharick A Pascoal
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Ricardo A S Lima-Filho
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Elisa de Paula França Resende
- Behavioral and Cognitive Neurology Research Group, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
- Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Erica L M Vieira
- Centre of Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Antonio L Teixeira
- Neuropsychiatry Program, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Santa Casa BH Ensino e Pesquisa, Belo Horizonte, MG, Brazil
| | - Leonardo C de Souza
- Behavioral and Cognitive Neurology Research Group, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
- Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Julyanna A Peny
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Juliana T S Fortuna
- Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Isadora C Furigo
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Debora Hashiguchi
- Department of Physiology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Vivian S Miya-Coreixas
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Julia R Clarke
- School of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Jose F Abisambra
- Department of Neuroscience, Center for Translational Research in Neurodegenerative Disease University of Florida, Gainesville, FL, USA
| | - Beatriz M Longo
- Department of Physiology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Jose Donato
- Department of Physiology and Biophysics, Institute of Biomedical Sciences, University of São Paulo, São Paulo, SP, Brazil
| | - Paul E Fraser
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Paulo Caramelli
- Behavioral and Cognitive Neurology Research Group, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Sergio T Ferreira
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
- Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
| | - Fernanda G De Felice
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
- Department of Psychiatry, Queen's University, Kingston, ON, Canada.
- Department of Biomedical and Molecuar Sciences, Queen's University, Kingston, ON, Canada.
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45
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Zou X, Himbert S, Dujardin A, Juhasz J, Ros S, Stöver HDH, Rheinstädter MC. Curcumin and Homotaurine Suppress Amyloid-β 25-35 Aggregation in Synthetic Brain Membranes. ACS Chem Neurosci 2021; 12:1395-1405. [PMID: 33826295 DOI: 10.1021/acschemneuro.1c00057] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Amyloid-β (Aβ) peptides spontaneously aggregate into β- and cross-β-sheets in model brain membranes. These nanometer sized can fuse into larger micrometer sized clusters and become extracellular and serve as nuclei for further plaque and fibril growth. Curcumin and homotaurine represent two different types of Aβ aggregation inhibitors. While homotaurine is a peptic antiaggregant that binds to amyloid peptides, curcumin is a nonpeptic molecule that can inhibit aggregation by changing membrane properties. By using optical and fluorescent microscopy, X-ray diffraction, and UV-vis spectroscopy, we study the effect of curcumin and homotaurine on Aβ25-35 aggregates in synthetic brain membranes. Both molecules partition spontaneously and uniformly in membranes and do not lead to observable membrane defects or disruption in our experiments. Both curcumin and homotaurine were found to significantly reduce the number of small, nanoscopic Aβ aggregates and the corresponding β- and cross-β-sheet signals. While a number of research projects focus on potential drug candidates that target Aβ peptides directly, membrane-lipid therapy explores membrane-mediated pathways to suppress peptide aggregation. Based on the results obtained, we conclude that membrane active drugs can be as efficient as peptide targeting drugs in inhibiting amyloid aggregation in vitro.
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Affiliation(s)
- Xingyuan Zou
- Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1, Canada
- Origins Institute, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Sebastian Himbert
- Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1, Canada
- Origins Institute, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Alix Dujardin
- Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1, Canada
- Origins Institute, McMaster University, Hamilton, ON L8S 4L8, Canada
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Janos Juhasz
- Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1, Canada
- Department of Medical Physics, Juravinski Cancer Centre, Hamilton, ON L8V 5C2, Canada
| | - Samantha Ros
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Harald D. H. Stöver
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Maikel C. Rheinstädter
- Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1, Canada
- Origins Institute, McMaster University, Hamilton, ON L8S 4L8, Canada
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46
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Nakano M, Mitsuishi Y, Liu L, Watanabe N, Hibino E, Hata S, Saito T, Saido TC, Murayama S, Kasuga K, Ikeuchi T, Suzuki T, Nishimura M. Extracellular Release of ILEI/FAM3C and Amyloid-β Is Associated with the Activation of Distinct Synapse Subpopulations. J Alzheimers Dis 2021; 80:159-174. [PMID: 33492290 DOI: 10.3233/jad-201174] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Brain amyloid-β (Aβ) peptide is released into the interstitial fluid (ISF) in a neuronal activity-dependent manner, and Aβ deposition in Alzheimer's disease (AD) is linked to baseline neuronal activity. Although the intrinsic mechanism for Aβ generation remains to be elucidated, interleukin-like epithelial-mesenchymal transition inducer (ILEI) is a candidate for an endogenous Aβ suppressor. OBJECTIVE This study aimed to access the mechanism underlying ILEI secretion and its effect on Aβ production in the brain. METHODS ILEI and Aβ levels in the cerebral cortex were monitored using a newly developed ILEI-specific ELISA and in vivo microdialysis in mutant human Aβ precursor protein-knockin mice. ILEI levels in autopsied brains and cerebrospinal fluid (CSF) were measured using ELISA. RESULTS Extracellular release of ILEI and Aβ was dependent on neuronal activation and specifically on tetanus toxin-sensitive exocytosis of synaptic vesicles. However, simultaneous monitoring of extracellular ILEI and Aβ revealed that a spontaneous fluctuation of ILEI levels appeared to inversely mirror that of Aβ levels. Selective activation and inhibition of synaptic receptors differentially altered these levels. The evoked activation of AMPA-type receptors resulted in opposing changes to ILEI and Aβ levels. Brain ILEI levels were selectively decreased in AD. CSF ILEI concentration correlated with that of Aβ and were reduced in AD and mild cognitive impairment. CONCLUSION ILEI and Aβ are released from distinct subpopulations of synaptic terminals in an activity-dependent manner, and ILEI negatively regulates Aβ production in specific synapse types. CSF ILEI might represent a surrogate marker for the accumulation of brain Aβ.
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Affiliation(s)
- Masaki Nakano
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Yachiyo Mitsuishi
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Lei Liu
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Naoki Watanabe
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Emi Hibino
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
| | - Saori Hata
- Laboratory of Neuroscience, Graduate School of Pharmaceutical Sciences, Hokkaido University, Hokkaido, Japan.,Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
| | - Takashi Saito
- Laboratory for Proteolytic Neuroscience, RIKEN Brain Science Institute, Saitama, Japan.,Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Science, Nagoya, Japan
| | - Takaomi C Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Brain Science Institute, Saitama, Japan
| | - Shigeo Murayama
- Department of Neurology and Neuropathology (the Brain Bank for Aging Research), Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Toshiharu Suzuki
- Laboratory of Neuroscience, Graduate School of Pharmaceutical Sciences, Hokkaido University, Hokkaido, Japan
| | - Masaki Nishimura
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Shiga, Japan
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47
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Iaccarino L, La Joie R, Edwards L, Strom A, Schonhaut DR, Ossenkoppele R, Pham J, Mellinger T, Janabi M, Baker SL, Soleimani-Meigooni D, Rosen HJ, Miller BL, Jagust WJ, Rabinovici GD. Spatial Relationships between Molecular Pathology and Neurodegeneration in the Alzheimer's Disease Continuum. Cereb Cortex 2021; 31:1-14. [PMID: 32808011 PMCID: PMC7727356 DOI: 10.1093/cercor/bhaa184] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/01/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
A deeper understanding of the spatial relationships of β-amyloid (Aβ), tau, and neurodegeneration in Alzheimer's disease (AD) could provide insight into pathogenesis and clinical trial design. We included 81 amyloid-positive patients (age 64.4 ± 9.5) diagnosed with AD dementia or mild cognitive impairment due to AD and available 11C-PiB (PIB), 18F-Flortaucipir (FTP),18F-FDG-PET, and 3T-MRI, and 31 amyloid-positive, cognitively normal participants (age 77.3 ± 6.5, no FDG-PET). W-score voxel-wise deviation maps were created and binarized for each imaging-modality (W > 1.64, P < 0.05) adjusting for age, sex, and total intracranial volume (sMRI-only) using amyloid-negative cognitively normal adults. For symptomatic patients, FDG-PET and atrophy W-maps were combined into neurodegeneration maps (ND). Aβ-pathology showed the greatest proportion of cortical gray matter suprathreshold voxels (spatial extent) for both symptomatic and asymptomatic participants (median 94-55%, respectively), followed by tau (79-11%) and neurodegeneration (41-3%). Amyloid > tau > neurodegeneration was the most frequent hierarchy for both groups (79-77%, respectively), followed by tau > amyloid > neurodegeneration (13-10%) and amyloid > neurodegeneration > tau (6-13%). For symptomatic participants, most abnormal voxels were PIB+/FTP+/ND- (median 35%), and the great majority of ND+ voxels (91%) colocalized with molecular pathology. Amyloid spatially exceeded tau and neurodegeneration, with individual heterogeneities. Molecular pathology and neurodegeneration showed a progressive overlap along AD course, indicating shared vulnerabilities or synergistic toxic mechanisms.
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Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Daniel R Schonhaut
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
| | - Rik Ossenkoppele
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurology and Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam 1081 HV, The Netherlands
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Taylor Mellinger
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Mustafa Janabi
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94158, USA
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Jura B, Młoźniak D, Goszczyńska H, Blinowska K, Biendon N, Macrez N, Meyrand P, Bem T. Reconfiguration of the cortical-hippocampal interaction may compensate for Sharp-Wave Ripple deficits in APP/PS1 mice and support spatial memory formation. PLoS One 2020; 15:e0243767. [PMID: 33382724 PMCID: PMC7774978 DOI: 10.1371/journal.pone.0243767] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/25/2020] [Indexed: 12/28/2022] Open
Abstract
Hippocampal-cortical dialogue, during which hippocampal ripple oscillations support information transfer, is necessary for long-term consolidation of spatial memories. Whereas a vast amount of work has been carried out to understand the cellular and molecular mechanisms involved in the impairments of memory formation in Alzheimer's disease (AD), far less work has been accomplished to understand these memory deficiencies at the network-level interaction that may underlie memory processing. We recently demonstrated that freely moving 8 to 9-month-old APP/PS1 mice, a model of AD, are able to learn a spatial reference memory task despite a major deficit in Sharp-Wave Ripples (SWRs), the integrity of which is considered to be crucial for spatial memory formation. In order to test whether reconfiguration of hippocampal-cortical dialogue could be responsible for the maintenance of this ability for memory formation, we undertook a study to identify causal relations between hippocampal and cortical circuits in epochs when SWRs are generated in hippocampus. We analyzed the data set obtained from multielectrode intracranial recording of transgenic and wild-type mice undergoing consolidation of spatial memory reported in our previous study. We applied Directed Transfer Function, a connectivity measure based on Granger causality, in order to determine effective coupling between distributed circuits which express oscillatory activity in multiple frequency bands. Our results showed that hippocampal-cortical coupling in epochs containing SWRs was expressed in the two frequency ranges corresponding to ripple (130-180 Hz) and slow gamma (20-60 Hz) band. The general features of connectivity patterns were similar in the 8 to 9-month-old APP/PS1 and wild-type animals except that the coupling in the slow gamma range was stronger and spread to more cortical sites in APP/PS1 mice than in the wild-type group. During the occurrence of SWRs, the strength of effective coupling from the cortex to hippocampus (CA1) in the ripple band undergoes sharp increase, involving cortical areas that were different in the two groups of animals. In the wild-type group, retrosplenial cortex and posterior cingulate cortex interacted with the hippocampus most strongly, whereas in the APP/PS1 group more anterior structures interacted with the hippocampus, that is, anterior cingulate cortex and prefrontal cortex. This reconfiguration of cortical-hippocampal interaction pattern may be an adaptive mechanism responsible for supporting spatial memory consolidation in AD mice model.
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Affiliation(s)
- Bartosz Jura
- Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Dariusz Młoźniak
- Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Hanna Goszczyńska
- Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Katarzyna Blinowska
- Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
- Department of Biomedical Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland
| | - Nathalie Biendon
- Institut des Maladies Neurodégénératives, Université de Bordeaux, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Nathalie Macrez
- Institut des Maladies Neurodégénératives, Université de Bordeaux, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
| | - Pierre Meyrand
- Institut des Maladies Neurodégénératives, Université de Bordeaux, UMR 5293, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- INSERM, Neurocentre Magendie, Bordeaux, France
| | - Tiaza Bem
- Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
- * E-mail:
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49
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Lam J, Lee J, Liu CY, Lozano AM, Lee DJ. Deep Brain Stimulation for Alzheimer's Disease: Tackling Circuit Dysfunction. Neuromodulation 2020; 24:171-186. [PMID: 33377280 DOI: 10.1111/ner.13305] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/07/2020] [Accepted: 10/12/2020] [Indexed: 02/06/2023]
Abstract
OBJECTIVES Treatments for Alzheimer's disease are urgently needed given its enormous human and economic costs and disappointing results of clinical trials targeting the primary amyloid and tau pathology. On the other hand, deep brain stimulation (DBS) has demonstrated success in other neurological and psychiatric disorders leading to great interest in DBS as a treatment for Alzheimer's disease. MATERIALS AND METHODS We review the literature on 1) circuit dysfunction in Alzheimer's disease and 2) DBS for Alzheimer's disease. Human and animal studies are reviewed individually. RESULTS There is accumulating evidence of neural circuit dysfunction at the structural, functional, electrophysiological, and neurotransmitter level. Recent evidence from humans and animals indicate that DBS has the potential to restore circuit dysfunction in Alzheimer's disease, similarly to other movement and psychiatric disorders, and may even slow or reverse the underlying disease pathophysiology. CONCLUSIONS DBS is an intriguing potential treatment for Alzheimer's disease, targeting circuit dysfunction as a novel therapeutic target. However, further exploration of the basic disease pathology and underlying mechanisms of DBS is necessary to better understand how circuit dysfunction can be restored. Additionally, robust clinical data in the form of ongoing phase III clinical trials are needed to validate the efficacy of DBS as a viable treatment.
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Affiliation(s)
- Jordan Lam
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA.,Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA
| | - Justin Lee
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA.,Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA
| | - Charles Y Liu
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA.,Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA
| | - Andres M Lozano
- Division of Neurological Surgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, ON, M5T 2S8, Canada
| | - Darrin J Lee
- USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA.,Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, 90033, USA
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50
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Lana D, Ugolini F, Giovannini MG. Space-Dependent Glia-Neuron Interplay in the Hippocampus of Transgenic Models of β-Amyloid Deposition. Int J Mol Sci 2020; 21:E9441. [PMID: 33322419 PMCID: PMC7763751 DOI: 10.3390/ijms21249441] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/03/2020] [Accepted: 12/09/2020] [Indexed: 12/14/2022] Open
Abstract
This review is focused on the description and discussion of the alterations of astrocytes and microglia interplay in models of Alzheimer's disease (AD). AD is an age-related neurodegenerative pathology with a slowly progressive and irreversible decline of cognitive functions. One of AD's histopathological hallmarks is the deposition of amyloid beta (Aβ) plaques in the brain. Long regarded as a non-specific, mere consequence of AD pathology, activation of microglia and astrocytes is now considered a key factor in both initiation and progression of the disease, and suppression of astrogliosis exacerbates neuropathology. Reactive astrocytes and microglia overexpress many cytokines, chemokines, and signaling molecules that activate or damage neighboring cells and their mutual interplay can result in virtuous/vicious cycles which differ in different brain regions. Heterogeneity of glia, either between or within a particular brain region, is likely to be relevant in healthy conditions and disease processes. Differential crosstalk between astrocytes and microglia in CA1 and CA3 areas of the hippocampus can be responsible for the differential sensitivity of the two areas to insults. Understanding the spatial differences and roles of glia will allow us to assess how these interactions can influence the state and progression of the disease, and will be critical for identifying therapeutic strategies.
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Affiliation(s)
- Daniele Lana
- Department of Health Sciences, Section of Clinical Pharmacology and Oncology, University of Florence, Viale Pieraccini 6, 50139 Firenze, Italy;
| | - Filippo Ugolini
- Department of Health Sciences, Section of Anatomopathology, University of Florence, Viale Pieraccini 6, 50139 Firenze, Italy;
| | - Maria Grazia Giovannini
- Department of Health Sciences, Section of Clinical Pharmacology and Oncology, University of Florence, Viale Pieraccini 6, 50139 Firenze, Italy;
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